Complementation method, device and equipment for anemometer tower data and storage medium

Abstract

The invention provides an anemometer tower data complementing method, device and equipment and a storage medium, and relates to the technical field of wind power plant wind resource analysis. The method comprises the following steps: acquiring wind measurement data of a target wind measurement tower; analyzing the wind measurement data to obtain multiple groups of data; wherein the plurality of groups of data are data obtained by dividing the wind measurement data based on a plurality of preset height ranges; when the first group of data is incomplete, supplementing the first group of data based on the correlation between the first group of data and the data of the preferred meteorological station to obtain the complemented first group of data; wherein the first group of data is the minimum height range in different preset height ranges; when the target group data is incomplete, performing layer-by-layer interpolation on the target group data based on the complemented first group data; the target group of data is any group of data except the first group of data in the multiple groups of data. According to the invention, the data accuracy can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of wind resource analysis in wind farms, and in particular to a method, device, equipment and storage medium for completing wind tower data. Background Art

[0002] A wind tower is a tall structure used to measure wind parameters. It's a tower-shaped structure designed to observe and record near-ground airflow. Previously, it was mostly built by wind power companies, meteorological agencies, and environmental protection departments for meteorological observation and atmospheric environmental monitoring.

[0003] Meteorological towers play a crucial role in wind energy assessment and weather forecasting. Data such as their height, wind speed, and direction are crucial for accurately understanding wind resources and guiding wind farm construction and operation. However, in actual operation, the integrity of meteorological tower data is often affected by various factors, such as equipment failure, environmental interference, and improper data processing methods, resulting in missing or abnormal data.

[0004] The traditional data completion method uses data from surrounding meteorological stations to perform a linear correlation with the existing data from the wind tower. The data for the missing periods is then calculated using the station data, and the calculated data is then used to supplement the original data. However, this traditional data completion method is highly dependent on the data from surrounding meteorological stations and cannot accurately supplement the data. Summary of the Invention

[0005] The embodiments of the present invention provide a method, apparatus, device and storage medium for completing wind tower data, so as to solve the problem that the current method for completing wind tower data is inaccurate.

[0006] In a first aspect, an embodiment of the present invention provides a method for completing wind tower data, comprising:

[0007] Obtain wind measurement data from the target wind tower;

[0008] The wind measurement data is parsed to obtain multiple sets of data; wherein the multiple sets of data are data obtained by dividing the wind measurement data based on multiple preset height ranges;

[0009] When the first set of data is incomplete, the first set of data is supplemented based on the correlation between the first set of data and the data of the preferred weather station to obtain a supplemented first set of data; wherein the first set of data is the minimum altitude range within the different preset altitude ranges;

[0010] When the target group data is incomplete, the target group data is interpolated layer by layer based on the completed first group data; wherein the target group data is any group of data among the multiple groups of data except the first group of data.

[0011] In one possible implementation, based on the correlation between the first set of data and the data of the preferred weather station, the first set of data is supplemented, including:

[0012] Based on the geographical location and climatic conditions of the target wind tower, the best weather station is selected from multiple candidate weather stations;

[0013] Based on the correlation between the first set of data and the data of the preferred weather station, the first set of data is supplemented.

[0014] In one possible implementation, based on the geographical location and climatic conditions of the target wind tower, the optimal weather station is selected from multiple candidate weather stations, including:

[0015] Based on the distance between the target wind tower and the target weather station, the terrain similarity between the target wind tower and the target weather station, and the climatic condition similarity between the target wind tower and the target weather station, the optimal weather station is selected from multiple candidate weather stations; wherein the target weather station is any one of the multiple candidate weather stations.

[0016] In one possible implementation, when the target group data is incomplete, interpolation of the target group data layer by layer is performed based on the completed first group data, including:

[0017] When it is determined that the Nth group of data is incomplete, determining whether the N-1th group of data is complete; wherein N is an integer greater than 2;

[0018] When it is determined that the N-1th group of data is complete, a correlation calculation is performed based on the N-1th group of data and the Nth group of data to obtain the completed Nth group of data.

[0019] In a possible implementation, when the target group data is incomplete, interpolating the target group data layer by layer based on the completed first group data further includes:

[0020] When it is determined that the N-1th group of data is incomplete, a correlation calculation is performed based on the completed N-1th group of data and the Nth group of data to obtain the completed Nth group of data; wherein, the completed N-1th group of data is obtained based on the correlation calculation between the N-1th group of data and the N-2th group of data or the completed N-2th group of data.

[0021] In one possible implementation, the wind measurement data includes wind speed and wind direction;

[0022] The wind measurement data is analyzed to obtain multiple sets of data, including:

[0023] Analyze the wind measurement data to obtain wind measurement data at all heights;

[0024] Based on multiple preset height ranges and wind measurement data at all heights, the wind measurement data at all heights are divided into multiple groups of data.

[0025] In a second aspect, an embodiment of the present invention provides a device for completing wind tower data, comprising:

[0026] A data acquisition module is used to obtain wind measurement data of a target wind measurement tower;

[0027] A data grouping module is used to analyze the wind measurement data to obtain multiple groups of data; wherein the multiple groups of data are data obtained by dividing the wind measurement data based on multiple preset height ranges;

[0028] A first supplementing module is configured to supplement the first set of data based on the correlation between the first set of data and the data of the preferred weather station when the first set of data is incomplete, thereby obtaining a supplemented first set of data; wherein the first set of data is a minimum altitude range within different preset altitude ranges;

[0029] The layer-by-layer supplementation module is used to interpolate the target group data layer by layer based on the supplemented first group of data when the target group data is incomplete; wherein the target group data is any group of data among the multiple groups of data except the first group of data.

[0030] In a third aspect, an embodiment of the present invention provides an electronic device comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the method in the first aspect or any possible implementation of the first aspect is implemented.

[0031] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the method in the first aspect or any possible implementation of the first aspect.

[0032] In a fifth aspect, an embodiment of the present invention provides a computer program product, including a computer program, which, when executed by a processor, implements the method in the first aspect or any possible implementation of the first aspect.

[0033] In an embodiment of the present invention, in order to improve the accuracy of data completion, first, the wind measurement data of the target wind measurement tower can be obtained. Then, the wind measurement data is parsed to obtain multiple groups of data. Then, when the first group of data is incomplete, based on the correlation between the first group of data and the data of the preferred meteorological station, the first group of data is supplemented to obtain the supplemented first group of data. Finally, when the target group data is incomplete, the target group data is interpolated layer by layer based on the supplemented first group of data. Thus, by using the data of the optimal meteorological station to supplement the first group of data, and using the supplemented first group of data to supplement all the target group data, the consistency and accuracy of the data can be guaranteed. In this way, the integrity and reliability of the wind measurement data of the wind measurement tower can be improved, and more accurate data support can be provided for wind resource assessment, wind farm planning and operation, etc. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 This is a flow chart of an implementation method for completing wind tower data provided by an embodiment of the present invention;

[0035] Figure 2 1 is a schematic structural diagram of a device for completing wind tower data provided by an embodiment of the present invention;

[0036] Figure 3 is a schematic diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0037] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0038] As described in the background, wind tower data processing is a crucial step in wind farm resource assessment and a prerequisite for analyzing wind resource conditions within a wind farm. Only by accurately processing wind tower data can a precise assessment of a wind farm's wind resource conditions be achieved. However, wind tower data can be easily incomplete or erroneous due to issues such as photoelectric converter anomalies, sensor failures, fiber optic ring network communication failures, data acquisition interface failures, and hardware and software downtime. Accurately processing wind tower data is the technical challenge addressed in this application.

[0039] See also Figure 1 , which shows a flow chart of the implementation of the method for completing wind tower data provided by an embodiment of the present invention, and is described in detail as follows:

[0040] S110: Obtain wind measurement data from a target wind measurement tower.

[0041] Read the data from the target wind tower.

[0042] Wind measurement data can be obtained in real time or periodically from sensors on target wind towers, such as anemometers and wind vanes. These data may include wind speed, wind direction, and other wind-related parameters.

[0043] The frequency of data collection can be set according to actual needs and is not limited here. For example, data can be collected every 10 minutes.

[0044] In some embodiments, to ensure the stability and accuracy of the data collection system, a preliminary quality check is performed on the collected data, such as whether the data exceeds a reasonable range, whether there are obvious errors, etc. Data that does not meet the quality requirements can be marked or eliminated.

[0045] In this embodiment, the wind tower data can be screened using rule deletion, correlation deletion, and logical deletion methods, which can maximize the deletion of unreasonable wind measurement data and retain reasonable data, thereby reducing the probability of accidental deletion.

[0046] S120: Analyze the wind measurement data to obtain multiple groups of data.

[0047] The multiple groups of data are data obtained by dividing the wind measurement data based on multiple preset height ranges.

[0048] In order to improve the accuracy of the supplemented data, the wind measurement data can be divided according to different preset height ranges after parsing the wind measurement data.

[0049] In some embodiments, the wind measurement data may be first parsed to obtain wind measurement data at all altitudes.

[0050] Then, based on multiple preset height ranges and the wind measurement data at all heights, the wind measurement data at all heights are divided into multiple groups of data.

[0051] In this embodiment, the preset height range can be set based on the actual conditions of the wind tower and application requirements. For example, every 10 meters can be used as a level. The height range can be divided into different intervals such as 0-10 meters, 10-20 meters, 20-30 meters, and 30-40 meters.

[0052] In some embodiments, each group of data may be reorganized after grouping to further ensure the consistency and reliability of the data.

[0053] In this embodiment, a data statistical analysis method, such as calculating the average value, standard deviation, etc., may be used to perform a preliminary analysis on the data characteristics of each height range.

[0054] S130: When the first set of data is incomplete, based on the correlation between the first set of data and the data of the preferred weather station, the first set of data is supplemented to obtain a supplemented first set of data.

[0055] The first set of data is the smallest height range within the different preset height ranges. For example, the height ranges are divided into 0-10 meters, 10-20 meters, 20-30 meters, 30-40 meters, etc. The first set of data here is the data from 0-10 meters.

[0056] In some embodiments, the integrity and validity of the first set of data need to be determined first.

[0057] In this embodiment, it is possible to determine which data are unreasonable and invalid based on the magnitude of the wind speed, the value of the wind speed change in adjacent time periods, and the difference in wind speed at adjacent heights and in the same time period, and thus eliminate them.

[0058] In this embodiment, the data integrity is calculated. If the data integrity rate is greater than or equal to the reliable integrity rate, the first set of data is considered valid and reliable, and no wind data supplementation is required. If the data integrity rate is less than the reliable integrity rate, the first set of data is considered unreliable and wind data supplementation is required.

[0059] In some embodiments, the wind measurement data of the optimal weather station may be selected to complete the first set of data. First, based on the geographical location and climatic conditions of the target wind tower, the optimal weather station may be selected from multiple candidate weather stations.

[0060] Then, based on the correlation between the first set of data and the data of the preferred weather station, the first set of data is supplemented.

[0061] In this embodiment, an optimal weather station is selected from multiple candidate weather stations based on the distance between the target wind tower and the target weather station, the terrain similarity between the target wind tower and the target weather station, and the climate similarity between the target wind tower and the target weather station. The target weather station is any one of the multiple candidate weather stations.

[0062] Specifically, scores can be assigned based on the distance between the target wind tower and the target weather station, the terrain similarity between the target wind tower and the target weather station, and the climate similarity between the target wind tower and the target weather station. A higher score indicates a closer match to the target wind tower's data. This allows one of the candidate weather stations to be selected as the optimal one.

[0063] Alternatively, the correlation between each candidate weather station and the target wind tower may be determined, such as the Pearson correlation coefficient, and the weather station with the highest correlation coefficient may be selected as the preferred weather station.

[0064] After the optimal weather station is determined, the first set of data can be supplemented based on the relevant data of the optimal weather station.

[0065] In some embodiments, the first set of data may be supplemented based on the correlation analysis and the relevant data of the optimal weather station to obtain a supplemented first set of data.

[0066] In this embodiment, a correlation analysis can be performed on the first set of data and the data of the preferred weather station to establish a complementary model between the two. For example, linear regression, nonlinear regression, etc. can be used to fit the functional relationship between the two based on known data points.

[0067] After the supplementary model is built, the missing parts of the first set of data can be supplemented with the complete data from the selected weather station. When supplementing the data, the time correspondence of the data should be considered to ensure that the supplemented data is consistent with the time series of the first set of data.

[0068] S140: When the target group data is incomplete, interpolate the target group data layer by layer based on the completed first group data.

[0069] The target group data is any set of data except the first set of data in the multiple sets of data. Still taking the above altitude range divided into different intervals such as 0-10 meters, 10-20 meters, 20-30 meters, and 30-40 meters as an example, the target group data here is any set of data between 10-20 meters, 20-30 meters, and 30-40 meters.

[0070] In some embodiments, when it is determined that the Nth group of data is incomplete, it may be determined whether the N-1th group of data is complete, where N is an integer greater than 2.

[0071] When it is determined that the N-1th group of data is complete, a correlation calculation is performed based on the N-1th group of data and the Nth group of data to obtain the completed Nth group of data.

[0072] However, when it is determined that the N-1th group of data is incomplete, a correlation calculation is performed based on the completed N-1th group of data and the Nth group of data to obtain the completed Nth group of data. The completed N-1th group of data is obtained by performing a correlation calculation based on the N-1th group of data and the N-2th group of data or the completed N-2th group of data.

[0073] In this embodiment, only the first set of data needs to be supplemented based on the data of the optimal weather station, and the remaining sets of data are supplemented based on the underlying data and do not need to be supplemented using the data of the optimal weather station.

[0074] Concrete, when determining that the data of 30-40 meter group is incomplete, the data of 20-30 meter group can be used to complete.When using the data of 20-30 meter group to complete, need, first judge the integrity of the data of 20-30 meter group.When determining that the data of 20-30 meter group is complete, the dependency based on the data of 20-30 meter group and the data of 30-40 meter group is completed, obtain the data of the 30-40 meter group after the completion.When determining that the data of 20-30 meter group is incomplete, need at first the data of 20-30 meter group is completed, the dependency based on the data of 20-30 meter group and the data of 30-40 meter group is completed, obtain the data of the 30-40 meter group after the completion. When completing the data of the 20-30 meter group, first determine the integrity of the data of the 10-20 meter group. When it is determined that the data of the 10-20 meter group is complete, complete the data based on the correlation between the data of the 20-30 meter group and the data of the 10-20 meter group to obtain the completed data of the 20-30 meter group. When it is determined that the data of the 10-20 meter group is incomplete, complete the data based on the correlation between the first group of completed data and the data of the 10-20 meter group to obtain the completed data of the 10-20 meter group.

[0075] Of course, when performing layer-by-layer interpolation, it is also possible to establish a vertical distribution model based on the wind speed and wind direction parameters between different altitude layers based on the atmospheric boundary layer theory, and combine it with the correlation method to complete the target group data at the same time to provide the accuracy of the completion.

[0076] During the interpolation process, the spatial and temporal continuity of the data must be considered. For data from adjacent altitudes, the interpolated data must have a reasonable spatial gradient. For data from different time points at the same altitude, the temporal continuity of the data must be ensured to avoid sudden changes.

[0077] After all wind measurement data are supplemented, the supplemented data needs to be verified to ensure the accuracy of the data.

[0078] The method for completing wind tower data provided by the present invention can, in order to improve the accuracy of data completion, first obtain the wind measurement data of the target wind tower. Then, the wind measurement data is parsed to obtain multiple groups of data. Then, when the first group of data is incomplete, the first group of data is supplemented based on the correlation between the first group of data and the data of the preferred meteorological station to obtain the completed first group of data. Finally, when the target group data is incomplete, the target group data is interpolated layer by layer based on the completed first group of data. Thus, by using the data of the optimal meteorological station to complete the first group of data, and using the completed first group of data to complete all the target group data, the consistency and accuracy of the data can be guaranteed. In this way, the integrity and reliability of the wind measurement data of the wind tower can be improved, and more accurate data support can be provided for wind resource assessment, wind farm planning and operation, etc.

[0079] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0080] The following are device embodiments of the present invention. For details not fully described therein, reference may be made to the corresponding method embodiments described above.

[0081] Figure 2 A schematic diagram of the structure of a device for completing wind tower data provided by an embodiment of the present invention is shown. For ease of explanation, only the parts related to the embodiment of the present invention are shown, which are described in detail as follows:

[0082] like Figure 2 As shown, the wind tower data supplementation device 200 includes:

[0083] A data acquisition module 210 is used to acquire wind measurement data of a target wind measurement tower;

[0084] The data grouping module 220 is used to analyze the wind measurement data to obtain multiple groups of data; wherein the multiple groups of data are data obtained by dividing the wind measurement data based on multiple preset height ranges;

[0085] A first supplementing module 230 is configured to supplement the first set of data, when the first set of data is incomplete, based on the correlation between the first set of data and the data of the preferred weather station, to obtain a supplemented first set of data; wherein the first set of data is the smallest altitude range within different preset altitude ranges;

[0086] The layer-by-layer supplementation module 240 is used to perform layer-by-layer interpolation on the target group data based on the supplemented first group data when the target group data is incomplete; wherein the target group data is any group of data among the multiple groups of data except the first group of data.

[0087] In one possible implementation, the first supplementing module 230 is configured to select an optimal weather station from a plurality of candidate weather stations based on the geographical location and climatic conditions of the target wind tower;

[0088] Based on the correlation between the first set of data and the data of the preferred weather station, the first set of data is supplemented.

[0089] In one possible implementation, the first supplementary module 230 is used to select the optimal weather station from multiple candidate weather stations based on the distance between the target wind tower and the target weather station, the terrain similarity between the target wind tower and the target weather station, and the climatic condition similarity between the target wind tower and the target weather station; wherein the target weather station is any one of the multiple candidate weather stations.

[0090] In one possible implementation, the layer-by-layer supplementation module 240 is configured to determine whether the N-1th group of data is complete when it is determined that the Nth group of data is incomplete; wherein N is an integer greater than 2;

[0091] When it is determined that the N-1th group of data is complete, a correlation calculation is performed based on the N-1th group of data and the Nth group of data to obtain the completed Nth group of data.

[0092] In one possible implementation, the layer-by-layer supplementation module 240 is used to perform a correlation calculation based on the supplemented N-1th group of data and the Nth group of data to obtain the supplemented Nth group of data when it is determined that the N-1th group of data is incomplete; wherein the supplemented N-1th group of data is obtained by performing a correlation calculation based on the N-1th group of data and the N-2th group of data or the supplemented N-2th group of data.

[0093] In one possible implementation, the wind measurement data includes wind speed and wind direction;

[0094] The data grouping module 220 is used to analyze the wind measurement data to obtain wind measurement data at all heights;

[0095] Based on multiple preset height ranges and wind measurement data at all heights, the wind measurement data at all heights are divided into multiple groups of data.

[0096] The device for completing wind tower data provided by the present invention can, in order to improve the accuracy of data completion, first obtain the wind measurement data of the target wind tower. Then, the wind measurement data is parsed to obtain multiple groups of data. Then, when the first group of data is incomplete, the first group of data is supplemented based on the correlation between the first group of data and the data of the preferred meteorological station to obtain the completed first group of data. Finally, when the target group data is incomplete, the target group data is interpolated layer by layer based on the completed first group of data. Thus, by using the data of the optimal meteorological station to complete the first group of data, and using the completed first group of data to complete all the target group data, the consistency and accuracy of the data can be guaranteed. Thus, the integrity and reliability of the wind measurement data of the wind tower can be improved, and more accurate data support can be provided for wind resource assessment, wind farm planning and operation, etc.

[0097] Figure 3 Schematic diagram of an electronic device provided by an embodiment of the present invention. Figure 3 As shown, the electronic device 3 of this embodiment includes a processor 30 and a memory 31. The memory 31 stores a computer program 32. When the processor 30 executes the computer program 32, the steps of the above-described method embodiments are implemented. Alternatively, when the processor 30 executes the computer program 32, the functions of the modules / units in the above-described device embodiments are implemented.

[0098] Exemplarily, the computer program 32 may be divided into one or more modules / units, which are stored in the memory 31 and executed by the processor 30 to implement the present invention. The one or more modules / units may be a series of computer program instruction segments capable of implementing specific functions, and the instruction segments are used to describe the execution process of the computer program 32 in the electronic device 3.

[0099] The electronic device 3 may include, but is not limited to, a processor 30 and a memory 31. Those skilled in the art will appreciate that Figure 3 It is only an example of electronic device 3 and does not constitute a limitation of electronic device 3. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, electronic device 3 may also include input and output devices, network access devices, buses, etc.

[0100] The processor 30 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0101] The memory 31 can be an internal storage unit of the electronic device 3, such as a hard disk or memory of the electronic device 3. The memory 31 can also be an external storage device of the electronic device 3, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a flash memory card, etc. equipped on the electronic device 3. Furthermore, the memory 31 can also include both an internal storage unit of the electronic device 3 and an external storage device. The memory 31 is used to store the computer program 32 and other programs and data required by the electronic device 3. The memory 31 can also be used to temporarily store data that has been output or is about to be output.

[0102] For the sake of convenience and brevity, the division of the above functional modules / units is only used as an example. In actual applications, the above functions can be assigned to different functional modules / units as needed. The above modules / units can be implemented in the form of hardware, software, or a combination of hardware and software.

[0103] An embodiment of the present invention further provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the methods in the above-mentioned method embodiments.

[0104] An embodiment of the present invention further provides a computer program product, including a computer program, which, when executed by a processor, implements the methods in the above-mentioned method embodiments.

[0105] The computer program includes computer program code, which may be in source code form, object code form, executable file, or some intermediate form. Computer-readable media may include any entity or device capable of carrying computer program code, recording media, USB flash drives, mobile hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunications signals, and software distribution media.

[0106] In the above embodiments, the descriptions of each embodiment have their own focus. For parts not described or recorded in detail in one embodiment, please refer to the relevant descriptions of other embodiments. Unless otherwise specified or there is a logical conflict, the terms and / or descriptions between different embodiments are consistent and can be referenced to each other. The technical features of different embodiments can be combined to form new embodiments based on their inherent logical relationships.

[0107] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention, and should all be included in the scope of protection of the present invention.

Claims

1. A method for completing wind tower data, characterized in that: include: Obtain wind measurement data from the target wind tower; The wind measurement data is parsed to obtain multiple sets of data; wherein the multiple sets of data are data obtained by dividing the wind measurement data based on multiple preset height ranges; When the first set of data is incomplete, the first set of data is supplemented based on the correlation between the first set of data and the data of the preferred weather station to obtain a supplemented first set of data; wherein the first set of data is the smallest altitude range within different preset altitude ranges; When the target group data is incomplete, the target group data is interpolated layer by layer based on the completed first group data; wherein the target group data is any group of data among the multiple groups of data except the first group of data.

2. The method for completing wind tower data according to claim 1, characterized in that: The supplementing of the first set of data based on the correlation between the first set of data and the data of the preferred weather station includes: Selecting an optimal weather station from a plurality of candidate weather stations based on the geographical location and climatic conditions of the target wind tower; Based on the correlation between the first set of data and the data of the preferred weather station, the first set of data is supplemented.

3. The method for completing wind tower data according to claim 2, characterized in that: The selecting of the optimal weather station from a plurality of candidate weather stations based on the geographical location and climatic conditions of the target wind tower comprises: Based on the distance between the target wind tower and the target weather station, the terrain similarity between the target wind tower and the target weather station, and the climatic condition similarity between the target wind tower and the target weather station, the optimal weather station is selected from multiple candidate weather stations; wherein the target weather station is any one of the multiple candidate weather stations.

4. The method for completing wind tower data according to claim 1, characterized in that: When the target group data is incomplete, interpolating the target group data layer by layer based on the completed first group data includes: When it is determined that the Nth group of data is incomplete, determining whether the N-1th group of data is complete; wherein N is an integer greater than 2; When it is determined that the N-1th group of data is complete, a correlation calculation is performed based on the N-1th group of data and the Nth group of data to obtain the completed Nth group of data.

5. The method for completing wind tower data according to claim 4, characterized in that: When the target group data is incomplete, interpolating the target group data layer by layer based on the completed first group data further includes: When it is determined that the N-1th group of data is incomplete, a correlation calculation is performed based on the completed N-1th group of data and the Nth group of data to obtain the completed Nth group of data; wherein, the completed N-1th group of data is obtained based on a correlation calculation between the N-1th group of data and the N-2th group of data or the completed N-2th group of data.

6. The method for completing wind tower data according to any one of claims 1 to 5, characterized in that: The wind measurement data includes wind speed and wind direction; The wind measurement data is parsed to obtain multiple sets of data, including: Analyzing the wind measurement data to obtain wind measurement data at all heights; Based on the multiple preset height ranges and the wind measurement data at all heights, the wind measurement data at all heights are divided into multiple groups of data.

7. A device for completing wind tower data, characterized in that: include: A data acquisition module is used to obtain wind measurement data of a target wind measurement tower; A data grouping module is used to analyze the wind measurement data to obtain multiple groups of data; wherein the multiple groups of data are data obtained by dividing the wind measurement data based on multiple preset height ranges; a first supplementing module, configured to supplement the first set of data, when the first set of data is incomplete, based on a correlation between the first set of data and data of a preferred weather station, to obtain a supplemented first set of data; wherein the first set of data is a minimum altitude range within different preset altitude ranges; A layer-by-layer supplementation module is used to interpolate the target group data layer by layer based on the supplemented first group of data when the target group data is incomplete; wherein the target group data is any group of data among the multiple groups of data except the first group of data.

8. An electronic device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the method according to any one of claims 1 to 6 is implemented.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

10. A computer program product, characterized in that The invention comprises a computer program, which implements the method according to any one of claims 1 to 6 when the computer program is executed by a processor.

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