A method and system for siting an offshore wind energy resource observation station

Abstract

The application discloses a kind of offshore wind energy resource observation site location method and system, method includes: setting target sea area and collecting its internal grid wind field reanalysis data, it is judged to obtain grid historical wind field time series data using pre-set data condition;Every grid point is traversed and is analyzed to obtain each grid point correlation coefficient data set, and respectively with pre-set grid point between wind field time series data correlation coefficient threshold value is compared to determine the representative radius of grid point;Collect the position information of existing wind energy resource observation site in target sea area and the corresponding observed data, the representative radius of existing observation site is obtained based on the aforementioned spatial correlation analysis to grid data, and with all grid points representative radius in target sea area is evaluated to obtain the arrangement position of observation site.The site location method and system provided by the application can avoid unnecessary site duplication construction, improve the representativeness and application range of observation site.

Description

Technical Field

[0001] This invention relates to the fields of new energy and meteorological observation technology, specifically to a method and system for selecting sites for offshore wind energy resource observation stations. Background Technology

[0002] Wind energy, as a clean and pollution-free green energy source, is an important component of my country's energy structure. my country has a vast territory and abundant wind energy resources, and its wind power industry has developed rapidly in the past decade, with installed capacity increasing year by year. Offshore wind power, with its abundant resources, high utilization efficiency, and environmental friendliness, is expected to become the mainstay of the wind power industry. In the early stages of wind energy resource development, it is usually necessary to accurately assess wind energy resources in the area to be developed by collecting existing observation data or deploying observation stations. This is to determine the economic benefits of the project and serve the planning and design of the wind farm project. However, deploying observation stations at sea presents challenges such as high construction difficulty, long construction period, and high investment costs, which become more pronounced with increasing water depth. More and more projects are constrained by project implementation time and cost, and without offshore wind measurement or with incomplete wind measurement data, feasibility studies and even engineering construction are conducted using unrepresentative data. This results in unreasonable selection and layout of wind turbine units, which seriously affects the overall wind energy resource utilization efficiency and power generation level of the wind farm.

[0003] Existing technologies mainly rely on the experience of technical personnel to select observation sites, failing to fully utilize meteorological data modeling methods or meteorological reanalysis data to scientifically analyze and judge the spatial consistency of offshore wind energy resources. This results in existing observation sites in the wind energy resource assessment area not being used correctly and effectively, and the representativeness and applicability of newly added observation site selection are insufficient. Summary of the Invention

[0004] Therefore, this invention provides a method and system for selecting offshore wind energy resource observation sites, which can overcome the problems of insufficient representativeness and adaptability in the existing offshore wind energy resource observation site selection process. Considering the good spatial consistency of offshore wind energy resource distribution, by combining gridded meteorological numerical simulation results or reanalysis data with spatial correlation analysis, it can scientifically identify the applicable scope of existing wind energy resource observation sites, determine representative observation site selection schemes, and improve the representativeness and applicability of site selection for wind farm wind energy resource assessment or other environmental factor assessment.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] In a first aspect, embodiments of the present invention provide a method for selecting the site of an offshore wind energy resource observation station, comprising:

[0007] Set the target sea area and collect gridded wind field reanalysis data of the target sea area based on a preset distance range;

[0008] Based on preset data usage conditions, the gridded wind field reanalysis data is evaluated to obtain gridded historical wind field time series data.

[0009] Based on the gridded historical wind field time series data, each grid point is traversed and spatial correlation analysis is performed on it to obtain a dataset of correlation coefficients between each grid point and other grid points.

[0010] The correlation coefficient dataset obtained for each grid point is compared with the preset correlation coefficient threshold of wind field time series data between grid points. The representative radius of the wind energy resources centered on the grid point with spatial consistency is determined when the grid point meets the threshold. The representative radius of all grid points in the target sea area is obtained, where the representative radius is used to characterize the spatial range of wind energy resources of the surrounding grid points that the grid point can represent.

[0011] Collect the location information and corresponding observation data of existing wind energy resource observation stations in the target sea area. Based on the aforementioned spatial correlation analysis and comparison of correlation coefficient thresholds, obtain the representative radius of the existing observation stations for the gridded data corresponding to the existing observation stations.

[0012] The representative radii of the target sea area and all grid points within it are evaluated based on the representative radii of existing observation stations to determine the location of offshore wind energy resource observation stations.

[0013] Preferably, the target sea area is set based on the intended use of the offshore wind energy resource observation station, including: offshore wind power planning, offshore wind power project development, and offshore wind energy resource environmental survey. The process of setting the target sea area includes: if the offshore wind energy resource observation station is used for offshore wind power planning, then the target sea area is the sea area to be planned; if the offshore wind energy resource observation station is used for offshore wind power project development, then the target sea area is the site area approved by the development unit; if the offshore wind energy resource observation station is used for offshore wind energy resource environmental survey, then the target sea area is the sea area to be surveyed for wind energy resources.

[0014] Preferably, the gridded wind field reanalysis data includes wind speed data elements and wind direction data elements.

[0015] Preferably, the preset data usage conditions need to meet spatial resolution conditions, temporal resolution conditions, and data accuracy requirements. Specifically, the spatial resolution condition is no less than 5 kilometers, the temporal resolution condition is no less than daily, and the data accuracy requirement is the data accuracy widely used in the industry or the data accuracy verified by actual measurement data.

[0016] Preferably, the process of obtaining gridded historical wind field time series data includes: when the collected reanalysis data meets the preset judgment conditions, obtaining gridded historical wind field time series data based on the reanalysis data; when the collected reanalysis data does not meet the preset judgment conditions, using a mesoscale meteorological model to simulate the historical wind field of the target sea area to obtain gridded historical wind field time series data.

[0017] Preferably, the process of evaluating the representative radius of the target sea area and all grid points within it based on the representative radius of existing observation stations includes: if the target sea area is within the representative radius of existing observation stations, then no new offshore wind energy resource observation station will be built at this location; if the target sea area is not within the representative radius of existing observation stations, then based on the representative radii of all grid points within the target sea area, the location of the grid point with the largest representative radius or the one closest to the center and with a relatively large representative radius will be selected as the proposed location for the offshore wind energy resource observation station, and a new offshore wind energy resource observation station will be built at this location.

[0018] Preferably, the present invention provides a method for selecting offshore wind energy resource observation stations, which further includes: for sea areas where no target sea area has been set and which are not within the representative radius of existing observation stations, according to actual engineering needs, selecting the grid point with the largest representative radius of wind energy resource spatial consistency to arrange observation stations for subsequent offshore wind power planning, offshore wind power project development and offshore wind energy resource environmental survey.

[0019] Secondly, embodiments of the present invention provide a site selection system for offshore wind energy resource observation stations, comprising:

[0020] The data collection module is used to set the target sea area and collect gridded wind field reanalysis data of the target sea area based on a preset distance range;

[0021] The data judgment module is used to judge the gridded wind field reanalysis data based on preset data usage conditions to obtain gridded historical wind field time series data;

[0022] The data analysis module is used to traverse each grid point and perform spatial correlation analysis on the gridded historical wind field time series data to obtain a dataset of correlation coefficients between each grid point and other grid points.

[0023] The target sea area grid point representative radius acquisition module is used to compare the correlation coefficient dataset obtained for each grid point with the preset correlation coefficient threshold of wind field time series data between grid points, determine the representative radius of the wind energy resources centered on the grid point when the grid point meets the threshold, and obtain the representative radius of all grid points in the target sea area. The representative radius is used to characterize the spatial range of wind energy resources of the surrounding grid points that the grid point can represent.

[0024] The module for obtaining the representative radius of existing observation stations is used to collect the location information and corresponding observation data of existing wind energy resource observation stations in the target sea area. Based on the aforementioned spatial correlation analysis and comparison of correlation coefficient thresholds, the representative radius of existing observation stations is obtained for the gridded data corresponding to the existing observation stations.

[0025] The evaluation module is used to evaluate the representative radius of the target sea area and all grid points within it based on the representative radius of existing observation stations, so as to obtain the location of offshore wind energy resource observation stations.

[0026] Thirdly, embodiments of the present invention provide a computer device, including: at least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to cause the at least one processor to execute a method for selecting a site for offshore wind energy resource observation stations according to the first aspect of the present invention.

[0027] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing computer instructions for causing a computer to execute a method for selecting a site for offshore wind energy resource observation stations according to the first aspect of the present invention.

[0028] The technical solution of this invention has the following advantages:

[0029] This invention provides a method and system for selecting offshore wind energy resource observation sites. The method includes: setting a target sea area and collecting gridded wind field reanalysis data of the target sea area based on a preset distance range; judging the gridded wind field reanalysis data based on preset data usage conditions to obtain gridded historical wind field time series data; traversing each grid point and performing spatial correlation analysis on the gridded historical wind field time series data to obtain a correlation coefficient dataset between each grid point and other grid points; comparing the correlation coefficient dataset obtained for each grid point with a preset correlation coefficient threshold for wind field time series data between grid points to determine the representative radius of the wind energy resources centered on the grid point when the grid point meets the threshold, thus obtaining the representative radius of all grid points in the target sea area; collecting the location information and corresponding observation data of existing wind energy resource observation sites in the target sea area, and obtaining the representative radius of existing observation sites based on the aforementioned spatial correlation analysis and correlation coefficient threshold comparison for the gridded data corresponding to the existing observation sites; evaluating the representative radius of the target sea area and all grid points within it based on the representative radius of the existing observation sites to obtain the location of the offshore wind energy resource observation sites. The site selection method and system provided by this invention can more efficiently determine the location of offshore wind energy resource observation stations, avoid unnecessary duplication of construction, and improve the representativeness and applicability of offshore wind energy resource observation stations. Attached Figure Description

[0030] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0031] Figure 1 A flowchart illustrating the method for selecting offshore wind energy resource observation sites provided in this embodiment of the invention;

[0032] Figure 2 The grid points provided in this embodiment of the invention represent a structural schematic diagram with a defined radius;

[0033] Figure 3 A schematic diagram of the specific structure of the offshore wind energy resource observation site selection method provided in this embodiment of the invention;

[0034] Figure 4 A schematic diagram of the module composition of the offshore wind energy resource observation site site selection system provided in this embodiment of the invention;

[0035] Figure 5 A composition diagram of a specific example of a computer device provided in an embodiment of the present invention.

[0036] Explanation of reference numerals in the attached figures:

[0037] 1. Coastline; 2. Existing observation stations; 3. Representative radius of existing observation stations; 4. Target sea area; 5. Proposed location of observation stations. Detailed Implementation

[0038] To enable those skilled in the art to better understand the present invention, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, not all of them, and are not intended to limit the scope of the present invention. Furthermore, in the following description, descriptions of well-known structures and technologies are omitted to avoid unnecessary confusion regarding the concepts disclosed in the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0039] Furthermore, the technical features involved in the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0040] Example 1

[0041] This invention provides a method for selecting sites for offshore wind energy resource observation stations, such as... Figure 1 As shown, the method includes:

[0042] Step S1: Set the target sea area and collect gridded wind field reanalysis data of the target sea area based on the preset distance range.

[0043] In this embodiment, the target sea area is set based on the intended use of the offshore wind energy resource observation station, including: offshore wind power planning, offshore wind power project development, and offshore wind energy resource environmental survey. The process of setting the target sea area includes: if the offshore wind energy resource observation station is used for offshore wind power planning, then the target sea area is the sea area to be planned; if the offshore wind energy resource observation station is used for offshore wind power project development, then the target sea area is the site area approved by the development unit; if the offshore wind energy resource observation station is used for offshore wind energy resource environmental survey, then the target sea area is the sea area to be surveyed for wind energy resources.

[0044] In this embodiment, the preset distance range includes the target sea area and the surrounding sea area within a radius of tens to hundreds of kilometers. This is only an example and can be modified according to actual needs.

[0045] It should be noted that the gridded reanalysis data refers to historical meteorological element analysis datasets such as ERA5 and MERRA2, established by relevant meteorological institutions, enterprises, or research institutes according to a certain spatial resolution. In this embodiment, the gridded wind field reanalysis data includes wind speed data elements and wind direction data elements.

[0046] Step S2: Based on the preset data usage conditions, the gridded wind field reanalysis data is judged to obtain gridded historical wind field time series data.

[0047] In this embodiment, the preset data usage conditions must meet spatial resolution, temporal resolution, and data accuracy requirements. Specifically, the spatial resolution is no less than 5 kilometers, the temporal resolution is no less than daily, and the data accuracy requirement is either widely used in the industry or verified by measured data. It should be noted that the time range of the gridded wind field reanalysis data in this embodiment of the invention includes at least one full year, which helps ensure the effectiveness and reliability of the reanalysis wind field data.

[0048] Step S3: Based on the gridded historical wind field time series data, traverse each grid point and perform spatial correlation analysis on it to obtain the correlation coefficient dataset between each grid point and other grid points.

[0049] In this embodiment, when the collected reanalysis data meets the preset judgment conditions, gridded historical wind field time series data is obtained based on the reanalysis data; when the collected reanalysis data does not meet the preset judgment conditions, historical wind field simulation of the target sea area is performed using a mesoscale meteorological model to obtain gridded historical wind field time series data. It should be noted that mesoscale meteorological models are commonly used techniques in this field, including WRF model, MM5 model, and ARPS model. These are only illustrative examples and are not intended to limit the application; adaptive modifications can be made based on actual applications.

[0050] Specifically, in this embodiment, the formula for calculating the correlation coefficient ρ is as follows:

[0051]

[0052] Among them, A i＝1,2,…N and B i＝1,2,…N These are time series wind field data for points A and B, consisting of N observations, μ A and σ A These are the mean and standard deviation of the wind field time series data at point A, respectively, μ B and σ B These are the mean and standard deviation of the wind field time series data at point B, respectively.

[0053] Step S4: Compare the correlation coefficient dataset obtained for each grid point with the preset correlation coefficient threshold of wind field time series data between grid points to determine the representative radius of the wind energy resources centered on the grid point when the grid point meets the threshold. Obtain the representative radius of all grid points in the target sea area, where the representative radius is used to characterize the spatial range of wind energy resources of the surrounding grid points that the grid point can represent.

[0054] In this embodiment, the threshold for the correlation coefficient of wind field time series data between preset grid points can be set to 0.95 or 0.90. It should be noted that the above threshold values ​​are only illustrative examples and are not intended to be limiting. The specific threshold can be determined according to the accuracy requirements of the project for wind resource analysis.

[0055] The grid points provided in this embodiment of the invention represent a structural schematic diagram with a defined radius, as shown below. Figure 2 As shown, taking grid point A as an example, the correlation coefficient between grid point A and all grid points in the range layer containing grid point B (i.e., the other 8 grid points within range B excluding grid point A) is calculated one by one using the correlation coefficient ρ formula. If the correlation coefficients between all grid points in the range layer containing grid point B and grid point A are higher than the selected correlation coefficient threshold, the correlation coefficients between grid point A and all grid points in the range layer containing grid point C are calculated one by one using the same method. If the correlation coefficients between all grid points in the range layer containing grid point C and grid point A are higher than the selected correlation coefficient threshold, the calculation continues to the outermost grid layer. If there is a grid point in the outermost grid layer containing grid point C with a correlation coefficient lower than the selected threshold, the calculation terminates. This determines the distance between the range layer containing grid point B and the starting grid point as the representative radius of grid point A. Applying the above method for determining the representative radius of grid points to the calculation of all grid points yields the representative radii of all grid points within the target area.

[0056] Step S5: Collect the location information and corresponding observation data of existing wind energy resource observation stations in the target sea area. Based on the aforementioned spatial correlation analysis and comparison of correlation coefficient thresholds, obtain the representative radius of the existing observation stations for the gridded data corresponding to the existing observation stations.

[0057] It should be noted that the method for determining the representative radius of existing observation stations is the same as the method for determining the representative radius of grid points mentioned above, and will not be repeated here.

[0058] Step S6: Evaluate the representative radii of the target sea area and all grid points within it based on the representative radii of existing observation stations to obtain the location of offshore wind energy resource observation stations.

[0059] In this embodiment, if the target sea area is within the representative radius of an existing observation station, a new offshore wind energy resource observation station will not be constructed at this location; that is, the proposed observation station location will remain unchanged. Figure 3 As shown, if the target sea area 4 is not within the representative radius of an existing observation station, then based on the representative radii of all grid points within the target sea area 4, the location of the grid point with the largest representative radius or the one closest to the center and with a relatively large representative radius is selected as the proposed location 5 for the offshore wind energy resource observation station, and a new offshore wind energy resource observation station is constructed at this location 5. It should be noted that the offshore wind energy resource observation station site selection method provided in this embodiment of the invention, in addition to satisfying the above applications, can also be applied to areas where no target sea area has been designated (i.e.,...) according to actual needs. Figure 3 The target sea area 4 in the figure does not have a specific range (it can be any sea area in the figure) and is not within the representative radius 3 of the existing observation stations. According to the actual engineering needs, the grid point with the largest representative radius of wind energy resource spatial consistency is selected to set up observation station 5 for subsequent offshore wind power planning, offshore wind power project development and offshore wind energy resource environmental survey, which improves the universality and scalability of the offshore wind energy resource observation station site selection method.

[0060] The method for selecting offshore wind energy resource observation sites provided by the embodiments of the present invention can scientifically and efficiently determine the location of offshore wind energy resource observation sites, avoid unnecessary duplication of observation sites, and improve the representativeness and applicability of offshore wind energy resource observation sites.

[0061] Example 2

[0062] This invention provides a system for selecting offshore wind energy resource observation sites, such as... Figure 4 As shown, it includes:

[0063] The data collection module is used to set the target sea area and collect gridded wind field reanalysis data of the target sea area based on a preset distance range; this module performs the method described in step S1 of embodiment 1, which will not be repeated here.

[0064] The data judgment module is used to judge the gridded wind field reanalysis data based on preset data usage conditions to obtain gridded historical wind field time series data; this module executes the method described in step S2 of embodiment 1, which will not be repeated here.

[0065] The data analysis module is used to traverse each grid point and perform spatial correlation analysis on it based on the gridded historical wind field time series data to obtain the correlation coefficient dataset between each grid point and other grid points; this module executes the method described in step S3 of embodiment 1, which will not be repeated here.

[0066] The target sea area grid point representative radius acquisition module is used to compare the correlation coefficient dataset obtained for each grid point with the preset correlation coefficient threshold of wind field time series data between grid points, and determine the representative radius of the wind energy resources centered on the grid point when the grid point meets the threshold. The representative radius of all grid points in the target sea area is obtained, where the representative radius is used to characterize the spatial range of wind energy resources of the surrounding grid points that the grid point can represent. This module executes the method described in step S4 of embodiment 1, which will not be repeated here.

[0067] The module for obtaining the representative radius of existing observation stations is used to collect the location information of existing wind energy resource observation stations and the corresponding observation data within the target sea area. Based on the aforementioned spatial correlation analysis and comparison of correlation coefficient thresholds, the representative radius of the existing observation stations is obtained for the gridded data corresponding to the existing observation stations. This module executes the method described in step S5 of embodiment 1, which will not be repeated here.

[0068] The evaluation module is used to evaluate the representative radius of the target sea area and all grid points within it based on the representative radius of the existing observation stations, so as to obtain the location of the offshore wind energy resource observation stations. This module performs the method described in step S6 of embodiment 1, which will not be repeated here.

[0069] The offshore wind energy resource observation station site selection system provided by this invention can overcome the problems of insufficient representativeness and adaptability in the existing offshore wind energy resource observation station site selection process. Considering the good spatial consistency of offshore wind energy resource distribution, the system can scientifically identify the applicable scope of existing wind energy resource observation stations and determine representative observation station site selection schemes by combining gridded meteorological numerical simulation results or reanalysis data with spatial correlation analysis. This improves the representativeness and applicability of site selection for wind farm wind energy resource assessment or other environmental factor assessment.

[0070] Example 3

[0071] This invention provides a computer device, such as... Figure 5As shown, the system includes: at least one processor 501, at least one communication interface 503, a memory 504, and at least one communication bus 502. The communication bus 502 is used to enable communication between these components. The communication interface 503 may include a display screen and a keyboard; optionally, the communication interface 503 may also include a standard wired interface or a wireless interface. The memory 504 may be a high-speed volatile random access memory, an unstable memory, or at least one storage device located remotely from the processor 501. The processor 501 can execute the offshore wind energy resource observation site selection method of Embodiment 1. The memory 504 stores a set of program code, and the processor 501 calls the program code stored in the memory 504 to execute the offshore wind energy resource observation site selection method of Embodiment 1.

[0072] The communication bus 502 can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The communication bus 502 can be divided into an address bus, a data bus, and a control bus, etc. For ease of representation, Figure 5 The symbol is represented by only one line, but this does not mean that there is only one bus or one type of bus.

[0073] The memory 504 may include volatile memory, such as random access memory (RAM); the memory may also include non-volatile memory, such as flash memory, hard disk drive (HDD) or solid-state drive (SSD); the memory 504 may also include a combination of the above types of memory.

[0074] The processor 501 can be a central processing unit (CPU), a network processor (NP), or a combination of a CPU and an NP.

[0075] The processor 501 may further include a hardware chip. This hardware chip may be an Application-Specific Integrated Circuit (ASIC), a Programmable Logic Device (PLD), or a combination thereof. The PLD may be a Complex Programmable Logic Device (CPLD), a Field Programmable Gate Array (FPGA), a Generic Array Logic (GAL), or any combination thereof.

[0076] Optionally, the memory 504 is also used to store program instructions. The processor 501 can call the program instructions to implement the offshore wind energy resource observation site selection method as described in Embodiment 1 of the present invention.

[0077] This invention also provides a computer-readable storage medium storing computer-executable instructions that can execute the offshore wind energy resource observation site selection method of Embodiment 1. The storage medium may be a magnetic disk, optical disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk drive (HDD), or solid-state drive (SSD), etc.; the storage medium may also include combinations of the above types of memory.

[0078] Obviously, the above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. A method for selecting sites for offshore wind energy resource observation stations, characterized in that, include: A target sea area is set and gridded wind field reanalysis data of the target sea area is collected based on a preset distance range. The gridded wind field reanalysis data includes wind speed data elements and wind direction data elements. The gridded wind field reanalysis data is judged based on preset data usage conditions to obtain gridded historical wind field time series data; Based on the gridded historical wind field time series data, each grid point is traversed and spatial correlation analysis is performed on it to obtain a dataset of correlation coefficients between each grid point and other grid points. The correlation coefficient dataset obtained for each grid point is compared with the preset correlation coefficient threshold of wind field time series data between grid points. The representative radius of the wind energy resources centered on the grid point with spatial consistency is determined when the grid point meets the threshold. The representative radius of all grid points in the target sea area is obtained, where the representative radius is used to characterize the spatial range of wind energy resources of the surrounding grid points that the grid point can represent. Collect the location information and corresponding observation data of existing wind energy resource observation stations in the target sea area. Based on the aforementioned spatial correlation analysis and comparison of correlation coefficient thresholds, obtain the representative radius of the existing observation stations for the gridded data corresponding to the existing observation stations. The representative radii of the target sea area and all grid points within it are evaluated based on the representative radii of existing observation stations to obtain the location of offshore wind energy resource observation stations. The formula for calculating the correlation coefficient ρ is as follows: Among them, A i=1,2,…N and B i=1,2,…N These are time series wind field data for points A and B, consisting of N observations, μ A and σ A These are the mean and standard deviation of the wind field time series data at point A, respectively, μ B and σ B These are the mean and standard deviation of the wind field time series data at point B, respectively. The process of evaluating the representative radius of the target sea area and all grid points within it based on the representative radius of existing observation stations includes: if the target sea area is within the representative radius of existing observation stations, then no new offshore wind energy resource observation station will be built at this location; if the target sea area is not within the representative radius of existing observation stations, then based on the representative radii of all grid points within the target sea area, the location of the grid point with the largest representative radius or the grid point that is close to the center and has a relatively large representative radius will be selected as the proposed location for the offshore wind energy resource observation station, and a new offshore wind energy resource observation station will be built at this location.

2. The method for selecting sites for offshore wind energy resource observation stations according to claim 1, characterized in that, The target sea area is set based on the intended use of the offshore wind energy resource observation station, including: offshore wind power planning, offshore wind power project development, and offshore wind energy resource environmental survey. The process of setting the target sea area includes: if the offshore wind energy resource observation station is used for offshore wind power planning, then the target sea area is the sea area to be planned; if the offshore wind energy resource observation station is used for offshore wind power project development, then the target sea area is the site area approved by the development unit; if the offshore wind energy resource observation station is used for offshore wind energy resource environmental survey, then the target sea area is the sea area to be surveyed for wind energy resources.

3. The method for selecting sites for offshore wind energy resource observation stations according to claim 1, characterized in that, The preset data usage conditions must meet spatial resolution, temporal resolution, and data accuracy requirements. Specifically, the spatial resolution is no less than 5 kilometers, the temporal resolution is no less than daily, and the data accuracy requirement is either widely used in the industry or verified by actual measured data.

4. The method for selecting sites for offshore wind energy resource observation stations according to claim 3, characterized in that, The process of obtaining gridded historical wind field time series data includes: when the collected reanalysis data meets the preset judgment conditions, obtaining gridded historical wind field time series data based on the reanalysis data; when the collected reanalysis data does not meet the preset judgment conditions, using a mesoscale meteorological model to simulate the historical wind field of the target sea area to obtain gridded historical wind field time series data.

5. The method for selecting sites for offshore wind energy resource observation stations according to claim 1, characterized in that, Also includes: For sea areas where no target sea area has been set and which are not within the representative radius of existing observation stations, observation stations will be set up at grid points with the largest representative radius of wind energy resource spatial consistency, based on actual engineering needs, for subsequent offshore wind power planning, offshore wind power project development, and offshore wind energy resource environmental surveys.

6. A site selection system for offshore wind energy resource observation stations, characterized in that, include: The data collection module is used to set a target sea area and collect gridded wind field reanalysis data of the target sea area based on a preset distance range. The gridded wind field reanalysis data includes wind speed data elements and wind direction data elements. The data judgment module is used to judge the gridded wind field reanalysis data based on preset data usage conditions to obtain gridded historical wind field time series data. The data analysis module is used to traverse each grid point and perform spatial correlation analysis on it based on the gridded historical wind field time series data to obtain a dataset of correlation coefficients between each grid point and other grid points. The target sea area grid point representative radius acquisition module is used to compare the correlation coefficient dataset obtained for each grid point with the preset correlation coefficient threshold of wind field time series data between grid points, determine the representative radius of the wind energy resources centered on the grid point when the grid point meets the threshold, and obtain the representative radius of all grid points in the target sea area, wherein the representative radius is used to characterize the spatial range of wind energy resources of the surrounding grid points that the grid point can represent; The module for obtaining the representative radius of existing observation stations is used to collect the location information and corresponding observation data of existing wind energy resource observation stations in the target sea area. Based on the aforementioned spatial correlation analysis and comparison of correlation coefficient thresholds, the representative radius of existing observation stations is obtained for the gridded data corresponding to the existing observation stations. The evaluation module is used to evaluate the representative radius of the target sea area and all grid points within it based on the representative radius of existing observation stations, so as to obtain the location of the offshore wind energy resource observation stations. The formula for calculating the correlation coefficient ρ is as follows: Among them, A i=1,2,…N and B i=1,2,…N These are time series wind field data for points A and B, consisting of N observations, μ A and σ A These are the mean and standard deviation of the wind field time series data at point A, respectively, μ B and σ B These are the mean and standard deviation of the wind field time series data at point B, respectively. The process of evaluating the representative radius of the target sea area and all grid points within it based on the representative radius of existing observation stations includes: if the target sea area is within the representative radius of existing observation stations, then no new offshore wind energy resource observation station will be built at this location; if the target sea area is not within the representative radius of existing observation stations, then based on the representative radii of all grid points within the target sea area, the location of the grid point with the largest representative radius or the grid point that is close to the center and has a relatively large representative radius will be selected as the proposed location for the offshore wind energy resource observation station, and a new offshore wind energy resource observation station will be built at this location.

7. A computer device, characterized in that, include: At least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to cause the at least one processor to perform the offshore wind energy resource observation site site selection method according to any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to execute the offshore wind energy resource observation site selection method according to any one of claims 1-5.

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