CN112579980A - Wind field data processing method, device, equipment and storage medium - Google Patents
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Abstract
The application provides a wind field data processing method, a device, equipment and a storage medium, wherein the wind field data processing method comprises the following steps: acquiring multi-source remote sensing data and laser radar wind measurement data aiming at a target wind field; performing space-time matching on the analysis result of the multi-source remote sensing data and the analysis result of the laser radar wind measurement data to obtain a wind field data pair of the target wind field in the same time period and the same position; and analyzing the target wind field according to the wind field data pair to obtain an analysis result of the target wind field, and visualizing the wind field data pair and the analysis result. The wind field can be analyzed by combining multi-source remote sensing data and laser radar wind measurement data, so that the data analysis accuracy of the wind field is improved. On the other hand, by visualizing the wind field data pairs and the analysis results, the analysis staff can conveniently observe and analyze.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to a method, an apparatus, a device, and a storage medium for processing wind farm data.
Background
The wind field observation has great significance in improving the accuracy of long-term weather forecast and storm forecast, improving climate research models, military environment forecast and the like. In addition, under the background of global warming, low-carbon economy based on low energy consumption and low pollution becomes a global hotspot, wind energy is spotlighted due to the advantages of easy acquisition, reproducibility, wide distribution and the like, and the accurate observation and analysis of the wind farm has important significance for the site selection of the wind farm.
The traditional wind measuring mode mainly comes from ship meteorological observation, oil platform meteorological observation, buoy, island meteorological station observation and scientific investigation observation.
On the other hand, with the development of the space remote sensing technology, the satellite remote sensing data plays more and more important roles in wind field observation and research by virtue of the advantages of wide space coverage, uniform distribution, objective data and the like. But the wind field observation based on the satellite data also has the following defects that (1) the time resolution is low, and the observation frequency of most satellites does not exceed 1 time/day. (2) The horizontal resolution is low, and the data resolution of other satellites is generally 25km × 25km except that SAR satellites can reach the horizontal resolution of 500m × 500 m. (3) Due to the fact that factors such as the zigzag distribution of the coastline, the complexity of weather conditions, sea wind and land wind and the like can obviously affect the accuracy of the satellite to invert wind field data, and the adaptability of the satellite to a research area needs to be considered when inversion data are used. (4) The satellite data is a wind field of a 10m height layer, and the change conditions of the wind field at different heights cannot be reflected.
Disclosure of Invention
An object of the embodiments of the present application is to provide a method, an apparatus, a device, and a storage medium for processing wind field data, which are used to combine multi-source remote sensing data and laser radar wind measurement data to analyze a wind field, so as to improve data analysis accuracy of the wind field.
To this end, the present application discloses in a first aspect a method for processing wind farm data, the method comprising:
acquiring multi-source remote sensing data and laser radar wind measurement data aiming at a target wind field;
performing space-time matching on the analysis result of the multi-source remote sensing data and the analysis result of the laser radar wind measurement data to obtain a wind field data pair of the target wind field in the same time period and the same position;
and analyzing the target wind field according to the wind field data to obtain an analysis result of the target wind field.
In the first aspect of the application, multi-source remote sensing data and laser radar wind measurement data for a target wind field are obtained, so that the analysis result of the multi-source remote sensing data and the analysis result of the laser radar wind measurement data can be subjected to space-time matching, and the wind field data pairs of the target wind field in the same time period and the same position are obtained, so that the target wind field can be analyzed according to the wind field data pairs, and the analysis result of the target wind field is obtained. On the other hand, by visualizing the wind field data pairs and the analysis results, the analysis staff can conveniently observe and analyze.
In the first aspect of the present application, as an optional implementation manner, the analyzing the target wind field according to the wind field data and obtaining an analysis result of the target wind field includes:
calculating the root mean square error of the wind field data pair;
calculating the average deviation of the wind field data pairs;
calculating the standard deviation of the wind field data pair;
calculating a correlation coefficient of the wind field data pair;
and taking the root error, the average deviation, the standard deviation and the correlation coefficient as an analysis result of the target wind field.
In this alternative embodiment, the analysis result of the wind field can be determined according to the root mean square error, the average deviation, the standard deviation and the correlation coefficient of the wind field data pair.
In the first aspect of the present application, as an optional implementation manner, the calculation formula for calculating the root mean square error of the wind field data pair is:
and the calculation formula for calculating the average deviation of the wind field data pair is as follows:
and the calculation formula for calculating the standard deviation of the wind field data pair is as follows:
and calculating the correlation coefficient of the wind field data pair by the following calculation formula:
wherein RMSE is the root mean square error, Bias is the mean deviation, S is the standard deviation, R is the correlation coefficient, xiFor the lidar wind data, yiAnd delta x is the difference value of the remote sensing data and the laser radar data.
In this alternative embodiment, the root mean square error, the average deviation, the standard deviation, and the correlation coefficient of the wind field can be accurately calculated by the above formula.
In the first aspect of the present application, as an optional implementation manner, after the obtaining of the multi-source remote sensing data and the lidar anemometry data for the target wind field, before performing space-time matching on an analysis result of the multi-source remote sensing data and an analysis result of the lidar anemometry data and obtaining a wind field data pair of the target wind field at the same time period and the same position, the method further includes:
analyzing the multi-source remote sensing data to obtain an analysis result of the multi-source remote sensing data;
and analyzing the laser radar wind measurement data to obtain an analysis result of the laser radar wind measurement data.
In this optional embodiment, by analyzing the multi-source remote sensing data, an analysis result of the multi-source remote sensing data can be obtained. On the other hand, the analytical result of the laser radar wind measurement data is obtained by analyzing the laser radar wind measurement data.
In the first aspect of the present application, as an optional implementation manner, the analyzing the multi-source remote sensing data to obtain an analysis result of the multi-source remote sensing data includes:
reading first spatial position information, first wind field information and first time information in the multi-source remote sensing data;
carrying out data gridding processing on the first spatial position information and the first wind field information so as to enable the first spatial position information and the first wind field information to be regularly arranged in a uniform distribution mode;
taking the first time information, the first spatial position information and the first wind field information as analysis results of the multi-source remote sensing data;
and analyzing the laser radar wind measurement data to obtain an analysis result of the laser radar wind measurement data, wherein the analysis result comprises the following steps:
reading second time information, second spatial position information and second wind field information in the laser radar wind measurement data;
and taking the second time information, the second spatial position information and the second wind field information as the analysis result of the laser radar wind measurement data.
In this optional embodiment, by reading first spatial position information, first wind field information, and first time information in the multi-source remote sensing data, data gridding processing can be performed on the first spatial position information and the first wind field information, so that the first spatial position information and the first wind field information are regularly arranged in a uniform size distribution manner, and the first time information, the first spatial position information, and the first wind field information can be used as an analysis result of the multi-source remote sensing data. On the other hand, by reading second time information, second spatial position information and second wind field information in the lidar wind measurement data, the second time information, the second spatial position information and the second wind field information can be used as analysis results of the lidar wind measurement data.
In the first aspect of the present application, as an optional implementation manner, the performing time-space matching on the analysis result of the multi-source remote sensing data and the analysis result of the lidar anemometry data to obtain a wind field data pair of the target wind field in the same time period and the same position includes:
determining the wind field data pair in the same time period according to the first time information and the second time information;
determining the wind field data pair at the same position according to the first spatial position information and the second spatial position information;
and determining the wind farm data pair at the same position according to the first spatial position information and the second spatial position information, comprising:
calculating the row and column number of the laser radar position in the remote sensing data according to the first spatial position information and the second spatial position information;
and determining the wind field data pairs at the same positions according to the row and column numbers.
In this optional embodiment, the wind farm data pairs in the same time period can be determined according to the first time information and the second time information, and further, the wind farm data pairs in the same position can be determined according to the first spatial position information and the second spatial position information. On the other hand, the row and column numbers of the laser radar positions in remote sensing data can be calculated according to the first spatial position information and the second spatial position information, and then the wind field data pairs at the same positions can be determined according to the row and column numbers.
In the first aspect of the present application, as an optional implementation manner, the calculation formula for calculating the row and column numbers of the lidar position in the remote sensing data according to the first spatial position information and the second spatial position information is as follows:
wherein L is a line number, C is a column number, Lat and Lon are the second spatial position information, LatulAnd LonulRes is the resolution of the remote sensing data, namely the grid size of the gridding data.
In this optional embodiment, the row and column numbers of the laser radar position in the remote sensing data can be accurately calculated through the above formula.
A second aspect of the present application discloses a wind farm data processing apparatus, the apparatus comprising:
the acquisition module is used for acquiring multi-source remote sensing data and laser radar wind measurement data aiming at a target wind field;
the data matching module is used for performing space-time matching on the analysis result of the multi-source remote sensing data and the analysis result of the laser radar wind measurement data and obtaining a wind field data pair of the target wind field in the same time period and the same position;
and the data analysis module is used for analyzing the target wind field according to the wind field data and obtaining an analysis result of the target wind field.
The device on the second surface can perform space-time matching on the analysis result of the multi-source remote sensing data and the analysis result of the laser radar wind measurement data and obtain the wind field data pair of the target wind field in the same time period and the same position by acquiring the multi-source remote sensing data and the laser radar wind measurement data aiming at the target wind field, so that the target wind field can be analyzed according to the wind field data pair and the analysis result of the target wind field can be obtained. On the other hand, by visualizing the wind field data pairs and the analysis results, the analysis staff can conveniently observe and analyze.
A third aspect of the present application discloses a wind farm data processing apparatus, the apparatus comprising:
a processor; and
a memory configured to store machine readable instructions which, when executed by the processor, cause the processor to perform the wind park data processing method of the first aspect of the application.
According to the device, multi-source remote sensing data and laser radar wind measurement data for a target wind field are obtained, so that the analysis result of the multi-source remote sensing data and the analysis result of the laser radar wind measurement data can be subjected to space-time matching, and the wind field data pairs of the target wind field in the same time period and the same position are obtained, so that the target wind field can be analyzed according to the wind field data pairs, and the analysis result of the target wind field is obtained. On the other hand, by visualizing the wind field data pairs and the analysis results, the analysis staff can conveniently observe and analyze.
A fourth aspect of the present application discloses a storage medium storing a computer program for execution by a processor of the wind farm data processing method disclosed in the first aspect of the present application.
According to the storage medium of the fourth aspect of the application, multi-source remote sensing data and laser radar wind measurement data for a target wind field are obtained, so that the analysis result of the multi-source remote sensing data and the analysis result of the laser radar wind measurement data can be subjected to space-time matching, the pair of wind field data of the target wind field in the same time period and the same position is obtained, and therefore the target wind field can be analyzed and the analysis result of the target wind field can be obtained according to the pair of the wind field data. On the other hand, by visualizing the wind field data pairs and the analysis results, the analysis staff can conveniently observe and analyze.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and that those skilled in the art can also obtain other related drawings based on the drawings without inventive efforts.
Fig. 1 is a schematic flow chart of a wind farm data processing method disclosed in an embodiment of the present application;
FIG. 2 is a schematic illustration of a visualization of a wind farm data pair disclosed in an embodiment of the present application;
FIG. 3 is a schematic illustration of a visualization of another wind farm data pair disclosed in embodiments of the present application;
FIG. 4 is a schematic illustration of a visualization of an analysis result disclosed in an embodiment of the present application;
FIG. 5 is a schematic structural diagram of a wind farm data processing apparatus disclosed in an embodiment of the present application;
fig. 6 is a schematic structural diagram of a wind farm data processing device disclosed in an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application.
Example one
Referring to fig. 1, fig. 1 is a schematic flow chart of a wind farm data processing method disclosed in an embodiment of the present application. As shown in fig. 1, the method of the embodiment of the present application includes the steps of:
101. acquiring multi-source remote sensing data and laser radar wind measurement data aiming at a target wind field;
102. performing space-time matching on the analysis result of the multi-source remote sensing data and the analysis result of the laser radar wind measurement data to obtain a wind field data pair of a target wind field in the same time period and the same position;
103. analyzing the target wind field according to the wind field data and obtaining an analysis result of the target wind field;
104. and visualizing the wind field data pairs and the analysis result.
In the embodiment of the application, the multi-source remote sensing data and the laser radar wind measurement data aiming at the target wind field are obtained, so that the analysis result of the multi-source remote sensing data and the analysis result of the laser radar wind measurement data can be subjected to space-time matching, and the wind field data pairs of the target wind field in the same time period and the same position are obtained, so that the target wind field can be analyzed according to the wind field data, and the analysis result of the target wind field is obtained. On the other hand, by visualizing the wind field data pair and the analysis result, an analyst can conveniently observe and analyze.
In the embodiment of the present application, optionally, as shown in fig. 2, 3, and 4, a scatter diagram may be used for the wind field data pair, and a bar graph or a line graph may be used for the analysis result.
In the embodiment of the present application, as an optional implementation manner, the steps of: analyzing the target wind field according to the wind field data and obtaining an analysis result of the target wind field, wherein the analysis result comprises the following steps:
calculating the root mean square error of the wind field data pair;
calculating the average deviation of the wind field data pairs;
calculating the standard deviation of the wind field data pair;
calculating a correlation coefficient of the wind field data pair;
and taking root errors, average deviation, standard deviation and correlation coefficients as analysis results of the target wind field.
In this alternative embodiment, the analysis result of the wind field can be determined according to the root mean square error, the average deviation, the standard deviation and the correlation coefficient of the wind field data pair.
In the embodiment of the present application, as an optional implementation manner, a calculation formula for calculating the root mean square error of the wind field data pair is:
and calculating the average deviation of the wind field data pair by the following formula:
and calculating the standard deviation of the wind field data pair by the following formula:
and calculating the correlation coefficient of the wind field data pair by the following formula:
wherein RMSE is root mean square error, Bias is mean deviation, S is standard deviation, R is correlation coefficient, xiFor lidar wind data, yiAnd delta x is remote sensing wind field data and a difference value between the remote sensing data and the laser radar data.
In this alternative embodiment, the root mean square error, the average deviation, the standard deviation, and the correlation coefficient of the wind field can be accurately calculated by the above formula.
In the embodiment of the present application, as an optional implementation manner, in the step: after multi-source remote sensing data and laser radar wind measurement data aiming at a target wind field are obtained, the method comprises the following steps: before performing space-time matching on the analysis result of the multi-source remote sensing data and the analysis result of the laser radar wind measurement data and obtaining a wind field data pair of a target wind field in the same time period and the same position, the method of the embodiment of the application further comprises the following steps:
analyzing the multi-source remote sensing data to obtain an analysis result of the multi-source remote sensing data;
and analyzing the laser radar wind measurement data to obtain an analysis result of the laser radar wind measurement data.
In the optional embodiment, the analysis result of the multi-source remote sensing data can be obtained by analyzing the multi-source remote sensing data. On the other hand, the analytical result of the laser radar wind measurement data is obtained by analyzing the laser radar wind measurement data.
In this embodiment of the present application, as an optional implementation manner, analyzing the multi-source remote sensing data to obtain an analysis result of the multi-source remote sensing data includes:
reading first spatial position information, first wind field information and first time information in multi-source remote sensing data;
carrying out data gridding processing on the first spatial position information and the first wind field information so as to enable the first spatial position information and the first wind field information to be regularly arranged in a uniform distribution mode;
taking the first time information, the first spatial position information and the first wind field information as analysis results of the multi-source remote sensing data;
and analyzing the laser radar wind measurement data to obtain an analysis result of the laser radar wind measurement data, wherein the analysis result comprises the following steps:
reading second time information, second spatial position information and second wind field information in the laser radar wind measurement data;
and taking the second time information, the second spatial position information and the second wind field information as the analysis result of the laser radar wind measurement data.
In this optional embodiment, by reading the first spatial position information, the first wind field information, and the first time information in the multi-source remote sensing data, the first spatial position information and the first wind field information can be subjected to data gridding processing, so that the first spatial position information and the first wind field information are regularly arranged in a uniform size distribution manner, and the first time information, the first spatial position information, and the first wind field information can be used as an analysis result of the multi-source remote sensing data. On the other hand, the second time information, the second spatial position information and the second wind field information in the lidar wind measurement data are read, so that the second time information, the second spatial position information and the second wind field information can be used as the analysis result of the lidar wind measurement data.
In the embodiment of the present application, as an optional implementation manner, the steps of: carrying out space-time matching on the analysis result of the multi-source remote sensing data and the analysis result of the laser radar wind measurement data to obtain a wind field data pair of a target wind field in the same time period and the same position, wherein the method comprises the following steps:
determining a wind field data pair in the same time period according to the first time information and the second time information;
determining a wind field data pair at the same position according to the first spatial position information and the second spatial position information;
and determining a wind field data pair at the same position according to the first spatial position information and the second spatial position information, including:
calculating the row and column number of the laser radar position in the remote sensing data according to the first spatial position information and the second spatial position information;
and determining the wind field data pairs at the same positions according to the row and column numbers.
In this optional embodiment, the wind field data pairs in the same time period can be determined according to the first time information and the second time information, and further, the wind field data pairs in the same position can be determined according to the first spatial position information and the second spatial position information. On the other hand, the row and column numbers of the laser radar positions in the remote sensing data can be calculated according to the first spatial position information and the second spatial position information, and further the wind field data pairs at the same positions can be determined according to the row and column numbers.
In the embodiment of the present application, as an optional implementation manner, a calculation formula for calculating a row number and a column number of a laser radar position in remote sensing data according to the first spatial position information and the second spatial position information is as follows:
wherein L is a row number, C is a column number, Lat and Lon are second spatial position information, LatulAnd LonulAnd Res is the remote sensing data resolution, namely the grid size of the gridding data.
In this optional embodiment, the row and column numbers of the laser radar position in the remote sensing data can be accurately calculated through the above formula.
Example two
Referring to fig. 5, fig. 5 is a schematic structural diagram of a wind farm data processing apparatus disclosed in the embodiment of the present application. As shown in fig. 5, the apparatus of the embodiment of the present application includes:
the acquiring module 201 is used for acquiring multi-source remote sensing data and laser radar wind measurement data aiming at a target wind field;
the data matching module 202 is used for performing space-time matching on the analysis result of the multi-source remote sensing data and the analysis result of the laser radar wind measurement data and obtaining a wind field data pair of a target wind field in the same time period and the same position;
the data analysis module 203 is used for analyzing the target wind field according to the wind field data and obtaining an analysis result of the target wind field;
and the display module 204 is used for visualizing the wind field data pairs and the analysis result.
The device of the embodiment of the application can perform space-time matching on the analysis result of the multi-source remote sensing data and the analysis result of the laser radar wind measurement data and obtain the wind field data pairs of the target wind field in the same time period and the same position by acquiring the multi-source remote sensing data and the laser radar wind measurement data aiming at the target wind field, so that the target wind field can be analyzed according to the wind field data and the analysis result of the target wind field can be obtained. On the other hand, by visualizing the wind field data pair and the analysis result, an analyst can conveniently observe and analyze.
Please refer to the first embodiment of the present application for other descriptions related to the embodiments of the present application, which are not described in detail herein.
EXAMPLE III
Referring to fig. 6, fig. 6 is a schematic structural diagram of a wind farm data processing apparatus according to an embodiment of the present application. As shown in fig. 6, the apparatus of the embodiment of the present application includes:
a processor 601; and
the memory 602 is configured to store machine readable instructions, which when executed by the processor 601, cause the processor 601 to execute the wind farm data processing method according to the first embodiment of the present application.
The device provided by the embodiment of the application can perform space-time matching on the analysis result of the multi-source remote sensing data and the analysis result of the laser radar wind measurement data and obtain the wind field data pairs of the target wind field in the same time period and the same position by acquiring the multi-source remote sensing data and the laser radar wind measurement data aiming at the target wind field, so that the target wind field can be analyzed according to the wind field data and the analysis result of the target wind field can be obtained. On the other hand, by visualizing the wind field data pair and the analysis result, an analyst can conveniently observe and analyze.
Example four
The embodiment of the application discloses a storage medium, wherein a computer program is stored in the storage medium, and the computer program is executed by a processor to execute the wind field data processing method disclosed by the first aspect of the application.
The storage medium of the embodiment of the application can perform space-time matching on the analysis result of the multi-source remote sensing data and the analysis result of the lidar anemometry data and obtain the wind field data pair of the target wind field in the same time period and the same position by acquiring the multi-source remote sensing data and the lidar anemometry data aiming at the target wind field, so that the target wind field can be analyzed according to the wind field data pair and the analysis result of the target wind field can be obtained. On the other hand, by visualizing the wind field data pair and the analysis result, an analyst can conveniently observe and analyze.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.
In addition, units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
Furthermore, the functional modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
It should be noted that the functions, if implemented in the form of software functional modules and sold or used as independent products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
In this document, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions.
The above description is only an example of the present application and is not intended to limit the scope of the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (10)
1. A wind farm data processing method, characterized in that the method comprises:
acquiring multi-source remote sensing data and laser radar wind measurement data aiming at a target wind field;
performing space-time matching on the analysis result of the multi-source remote sensing data and the analysis result of the laser radar wind measurement data to obtain a wind field data pair of the target wind field in the same time period and the same position;
analyzing the target wind field according to the wind field data and obtaining an analysis result of the target wind field;
visualizing the wind farm data pair and the analysis result.
2. The method of claim 1, wherein the analyzing the target wind farm from the wind farm data and obtaining the analysis of the target wind farm comprises:
calculating the root mean square error of the wind field data pair;
calculating the average deviation of the wind field data pairs;
calculating the standard deviation of the wind field data pair;
calculating a correlation coefficient of the wind field data pair;
and taking the root error, the average deviation, the standard deviation and the correlation coefficient as an analysis result of the target wind field.
3. The method of claim 2, wherein the calculation of the root mean square error of the wind farm data pair is by:
and the calculation formula for calculating the average deviation of the wind field data pair is as follows:
and the calculation formula for calculating the standard deviation of the wind field data pair is as follows:
and calculating the correlation coefficient of the wind field data pair by the following calculation formula:
wherein RMSE is the root mean square error, Bias is the mean deviation, S is the standard deviation, R is the correlation coefficient, xiFor the lidar wind data, yiAnd delta x is the difference value of the remote sensing data and the laser radar data.
4. The method of claim 1, wherein after the obtaining of the multi-source remote sensing data and the lidar anemometry data for the target wind field, before the performing the space-time matching on the analytic result of the multi-source remote sensing data and the analytic result of the lidar anemometry data and obtaining the wind field data pairs of the target wind field at the same time period and the same position, the method further comprises:
analyzing the multi-source remote sensing data to obtain an analysis result of the multi-source remote sensing data;
and analyzing the laser radar wind measurement data to obtain an analysis result of the laser radar wind measurement data.
5. The method of claim 1, wherein the parsing the multi-source remote sensing data to obtain a parsing result of the multi-source remote sensing data comprises:
reading first spatial position information, first wind field information and first time information in the multi-source remote sensing data;
carrying out data gridding processing on the first spatial position information and the first wind field information so as to enable the first spatial position information and the first wind field information to be regularly arranged in a uniform distribution mode;
taking the first time information, the first spatial position information and the first wind field information as analysis results of the multi-source remote sensing data;
and analyzing the laser radar wind measurement data to obtain an analysis result of the laser radar wind measurement data, wherein the analysis result comprises the following steps:
reading second time information, second spatial position information and second wind field information in the laser radar wind measurement data;
and taking the second time information, the second spatial position information and the second wind field information as the analysis result of the laser radar wind measurement data.
6. The method of claim 5, wherein the performing the space-time matching on the analytic result of the multi-source remote sensing data and the analytic result of the lidar anemometry data to obtain a wind field data pair of the target wind field in the same time period and the same position comprises:
determining the wind field data pair in the same time period according to the first time information and the second time information;
determining the wind field data pair at the same position according to the first spatial position information and the second spatial position information;
and determining the wind farm data pair at the same position according to the first spatial position information and the second spatial position information, comprising:
calculating the row and column number of the laser radar position in the remote sensing data according to the first spatial position information and the second spatial position information;
and determining the wind field data pairs at the same positions according to the row and column numbers.
7. The method of claim 6, wherein the calculation of the line and column number of the lidar position in the remote sensing data from the first spatial position information and the second spatial position information is by:
wherein L is a line number, C is a column number, Lat and Lon are the second spatial position information, LatulAnd LonulRes is the remote sensing data resolution, namely the grid size of the gridding data.
8. A wind farm data processing apparatus, the apparatus comprising:
the acquisition module is used for acquiring multi-source remote sensing data and laser radar wind measurement data aiming at a target wind field;
the data matching module is used for performing space-time matching on the analysis result of the multi-source remote sensing data and the analysis result of the laser radar wind measurement data and obtaining a wind field data pair of the target wind field in the same time period and the same position;
the data analysis module is used for analyzing the target wind field according to the wind field data and obtaining an analysis result of the target wind field;
and the display module is used for visualizing the wind field data pair and the analysis result.
9. A wind farm data processing apparatus, characterized in that the apparatus comprises:
a processor; and
a memory configured to store machine readable instructions that, when executed by the processor, cause the processor to perform the wind farm data processing method of any of claims 1-7.
10. A storage medium, characterized in that the storage medium stores a computer program which is executed by a processor to perform the wind farm data processing method according to any one of claims 1 to 7.
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