Wind turbine location selection method for wind farm, and related apparatus

Abstract

A wind turbine location selection method for a wind farm, and a related apparatus. The method comprises: obtaining, by anemometer towers, wind resource fixed measurement data at a plurality of fixed locations in a reference area and obtaining a fixed measurement reference value of a target wind resource index; a surveying device performing surveying multiple times in the reference area along a plurality of surveying paths for data collection to obtain a plurality of sets of wind resource dynamic measurement data; calculating dynamic measurement reference values of the target wind resource index; determining a target surveying path on the basis of the matching between the dynamic measurement reference values and the fixed measurement reference value; constructing a surveying path in a non-reference area on the basis of the target surveying path, and the surveying device performing surveying along the path for data collection to obtain wind resource dynamic measurement data in the non-reference area; and on the basis of the wind resource dynamic measurement data in the reference area and the wind resource dynamic measurement data in the non-reference area, by analyzing wind power output, wind power generation cost , and grid electricity revenue, determining, in a wind farm area to be constructed, a plurality of wind turbine locations to be constructed.

Description

A method for selecting wind turbine locations in a wind farm and related equipment.

[0001] This invention claims priority to Chinese Patent Application No. 202411887523.2, filed on December 19, 2024, with the application title “A Method for Selecting Wind Turbine Locations in a Wind Farm and Related Devices”, the entire contents of which are incorporated herein by reference. Technical Field

[0002] This invention relates to the field of wind power generation technology, and in particular to a method and related apparatus for selecting wind turbine locations in a wind farm. Background Technology

[0003] Wind power generation (abbreviated as wind power) refers to converting the kinetic energy of wind into electrical energy. As a clean and pollution-free renewable energy source, wind energy has enormous potential and high application prospects in power generation. As one of the new energy sources for power generation, wind power has already occupied a relatively major position in the development of new energy sources. As of the end of June 2023, China's installed wind power capacity was approximately 390 million kilowatts, a year-on-year increase of 13.7%. According to the National Bureau of Statistics, wind power growth was 7.4% in December 2023.

[0004] In the wind power sector, the site selection for wind farms and wind turbines (hereinafter referred to as wind turbines) largely determines wind power output. Currently, the common method for wind turbine site selection is to set up meteorological towers at several fixed locations to measure parameters such as wind speed, thereby determining wind power output (which can be characterized by wind power), thus achieving turbine site selection. However, for large-scale wind farms, to achieve effective turbine site selection, a significant investment is needed to construct a large number of meteorological towers to obtain data from numerous different locations. High cost has become the biggest problem in wind turbine site selection.

[0005] Furthermore, a key challenge in wind power forecasting lies in the fluctuating and intermittent nature of wind power, which places higher demands on the detection performance of sensors, data transmission performance, and the continuity of network communication—all uncontrollable factors. Data obtained from fixed-point wind measurement towers only reflects the situation at that specific location, failing to comprehensively represent the situation at other locations in the planned development area, resulting in limited information. Moreover, it cannot be transformed into data assets for application to similar construction needs. In summary, existing methods for measuring wind power at fixed points are costly, yield low-utility data, and hinder accurate and advantageous wind turbine site selection. Summary of the Invention

[0006] The present invention discloses the following technical solutions:

[0007] The first aspect of this invention provides a method for selecting wind turbine locations in a wind farm, the method comprising:

[0008] By setting up multiple wind measurement towers in the reference area within the wind farm construction area, fixed measurement data of wind resources at multiple fixed points are obtained.

[0009] Based on fixed wind resource measurement data from multiple fixed locations, a fixed measurement reference value for a target wind resource indicator within the reference area is determined; the target wind resource indicator is one of several types of wind resource indicators in the fixed wind resource measurement data.

[0010] By controlling a mobile patrol device to conduct multiple patrols within the reference area using various patrol paths, the mobile patrol device collects data during the patrol, obtaining multiple sets of dynamic wind resource measurement data for the reference area; the mobile patrol device is equipped with one or more sensors for collecting wind resource index data; each set of dynamic wind resource measurement data corresponds to a patrol path used in a single patrol within the reference area.

[0011] For each set of dynamic wind resource measurement data in the multiple sets of dynamic wind resource measurement data, a dynamic measurement reference value for the target wind resource index is calculated.

[0012] Based on the matching between the calculated dynamic measurement reference values ​​of the target wind resource index and the fixed measurement reference values ​​of the target wind resource index, a target cruise path is determined from the multiple cruise paths.

[0013] Based on the target cruise path, a cruise path for a non-reference area is constructed within the wind farm construction area, and the mobile cruise device is controlled to cruise within the non-reference area based on the constructed cruise path, so that the mobile cruise device can collect data during the cruise and obtain dynamic measurement data of wind resources in the non-reference area.

[0014] Based on the dynamic measurement data of wind resources in the reference area and the dynamic measurement data of wind resources in the non-reference area, multiple wind turbine locations to be built are determined in the area where the wind farm is to be built by analyzing wind power output, wind power cost and grid electricity cost.

[0015] In one possible implementation, the method further includes:

[0016] Determine the expected wind power generation scale and geographical environmental characteristics of the area where the wind farm is to be built;

[0017] Based on the expected wind power generation scale and the geographical environment characteristics, a reference area and a non-reference area are delineated within the area to be built in the wind farm, and a layout scheme for the fixed points of the wind measurement towers in the reference area is generated.

[0018] In one possible implementation, the step of delineating reference and non-reference areas within the proposed wind farm construction area based on the expected wind power generation scale and the geographical environmental characteristics, and generating a fixed location layout scheme for the wind measurement towers in the reference area, includes:

[0019] If the expected wind power generation scale is the first level scale, then the number of fixed points of the wind measurement tower is set based on the expected wind power generation scale. Based on the number and the geographical environmental characteristics of the wind farm to be built area, the location information of the fixed points of the wind measurement tower is set. Based on the location information, the land area where the fixed points of the wind measurement tower are located in the wind farm to be built area is used as the reference area, and the remaining areas are used as non-reference areas.

[0020] If the expected wind power generation scale is the second-level scale, then the area to be built for the wind farm is divided into multiple zones based on the expected wind power generation scale; the expected wind power generation scale corresponding to each zone is determined based on the expected wind power generation scale and the number of zones; based on the geographical environmental characteristics of the area to be built for the wind farm, one or more zones are selected as reference areas, and the connected areas of the remaining zones are designated as non-reference areas; the number of fixed points for wind measurement towers is set based on the expected wind power generation scale corresponding to the reference areas; a wind measurement tower fixed point layout scheme is generated according to the geographical environmental characteristics of the reference areas; the second-level scale is larger than the first-level scale.

[0021] In one possible implementation, setting the location information of the fixed points of the wind measurement tower based on the quantity and the geographical environmental characteristics of the wind farm construction area includes:

[0022] If the geographical environment characteristics of the wind farm construction area indicate that the wind farm construction area includes special areas, then the fixed points of the wind measurement towers shall be set in the special areas first.

[0023] The step of selecting one or more zones as reference areas based on the geographical environmental characteristics of the wind farm construction area includes: if the geographical environmental characteristics of the wind farm construction area indicate that the wind farm construction area contains special areas, then the zones that overlap with the special areas are preferentially selected as reference areas.

[0024] In one possible implementation, the special region is at least one of the following types of regions:

[0025] A wind gap is a region where the elevation changes abruptly, and where the air density changes abruptly.

[0026] In one possible implementation, determining the expected wind power generation capacity of the area to be developed for the wind farm includes:

[0027] Obtain the expected installed wind power capacity within the area to be built of the wind farm;

[0028] Based on the mapping relationship between the range of wind power capacity and the scale of wind power generation, the expected scale of wind power generation in the area where the wind farm is to be built is determined.

[0029] In one possible implementation, determining a target cruise path from the multiple cruise paths based on the matching between the calculated dynamic measurement reference values ​​of the target wind resource index and the fixed measurement reference values ​​of the target wind resource index includes:

[0030] Calculate the absolute value of the difference between multiple dynamic measurement reference values ​​of the target wind resource index and the fixed measurement reference value respectively;

[0031] Based on the correspondence between dynamic wind resource measurement data and cruise paths, the cruise path corresponding to the dynamic measurement reference value with the smallest absolute value of the difference from the fixed measurement reference value is determined as the target cruise path.

[0032] In one possible implementation, each cruise path includes multiple location points with the same longitude and latitude but different elevations, so that the mobile cruise device can collect data at multiple different elevations for location points with the same longitude and latitude during the cruise.

[0033] The fixed wind resource measurement data for each fixed location includes wind resource measurement data at different elevations at the longitude and latitude indicated by that fixed location.

[0034] In one possible implementation, the target wind resource index is wind speed;

[0035] The determination of fixed measurement reference values ​​for target wind resource indicators within the reference area based on fixed wind resource measurement data from multiple fixed locations includes:

[0036] Wind speed measurements at multiple fixed points are extracted from the fixed wind resource measurement data at these multiple fixed points.

[0037] The median or average of the wind speed measurements at multiple fixed points is taken as the fixed reference value for wind speed in the reference area.

[0038] In one possible implementation, the step of calculating a dynamic measurement reference value for the target wind resource index for each set of dynamic wind resource measurement data in the plurality of sets of dynamic wind resource measurement data includes:

[0039] From each set of dynamic wind resource measurement data, extract the dynamic measurement data dataset of wind speed;

[0040] For each dynamic measurement dataset, the average wind speed is calculated and used as the dynamic measurement reference value for the wind speed corresponding to that set of dynamic wind resource measurement data.

[0041] In one possible implementation, both the fixed wind resource measurement data and the dynamic wind resource measurement data include the following types of wind resource indicators:

[0042] Latitude and longitude coordinates, wind speed, air density, and elevation;

[0043] The dynamic wind resource measurement data based on the reference area and the non-reference area, through analysis of wind power output, wind power cost, and grid electricity cost, determines multiple potential wind turbine locations within the wind farm development area, specifically including:

[0044] Based on the dynamic wind resource measurement data of the reference area and the dynamic wind resource measurement data of the non-reference area, multiple wind turbine site construction plans are generated; the wind turbine site construction plan includes: the latitude and longitude coordinates, elevation and annual power generation of multiple wind turbines to be constructed; wherein, the annual power generation is calculated based on wind speed and air density;

[0045] Based on annual power generation, wind power cost and grid electricity cost, the feasibility of the multiple wind turbine site construction plans is analyzed; multiple wind turbine sites to be built are determined according to the wind turbine site construction plan with the highest feasibility.

[0046] A second aspect of the present invention provides a wind turbine location selection device for a wind farm, the device comprising:

[0047] The fixed data acquisition module is used to obtain fixed measurement data of wind resources at multiple fixed points by setting up multiple meteorological towers in the reference area of ​​the wind farm to be built.

[0048] The fixed measurement reference value determination module is used to determine the fixed measurement reference value of the target wind resource index within the reference area based on fixed wind resource measurement data from multiple fixed points; the target wind resource index is one of several types of wind resource indices in the fixed wind resource measurement data.

[0049] The cruise control module is used to control a mobile cruise device to cruise multiple times within the reference area along various cruise paths, so that the mobile cruise device can collect data during the cruise and obtain multiple sets of dynamic wind resource measurement data of the reference area; the mobile cruise device is equipped with one or more sensors for collecting wind resource index data; a set of dynamic wind resource measurement data corresponds to the cruise path used in one cruise within the reference area.

[0050] The dynamic measurement reference value calculation module is used to calculate the dynamic measurement reference value of the target wind resource index for each set of dynamic measurement data of wind resources in the multiple sets of dynamic measurement data.

[0051] The path determination module is used to determine a target cruise path from the multiple cruise paths based on the matching between multiple dynamic measurement reference values ​​of the target wind resource index and the fixed measurement reference value of the target wind resource index.

[0052] The cruise control module is also used to construct a cruise path for a non-reference area within the wind farm construction area based on the target cruise path, and control the mobile cruise device to cruise within the non-reference area based on the constructed cruise path, so that the mobile cruise device can collect data during the cruise and obtain dynamic measurement data of wind resources in the non-reference area.

[0053] The module for determining the location of wind turbines to be built is used to determine multiple locations of wind turbines to be built within the area to be built of the wind farm by analyzing the dynamic measurement data of wind resources in the reference area and the dynamic measurement data of wind resources in the non-reference area, as well as the wind power output, wind power cost and electricity charges and the grid electricity charges.

[0054] Compared with the prior art, the present invention has the following beneficial effects:

[0055] In this invention, fixed wind resource measurement data at multiple fixed points within a reference area are obtained using a wind measurement tower. Based on this, a fixed measurement reference value for the target wind resource index within the reference area can be obtained. Furthermore, multiple sets of dynamic wind resource measurement data are collected through multiple cruises within the reference area using a cruise device with various cruise paths, and the dynamic measurement reference value for the target wind resource index is calculated. Based on the matching between the dynamic and fixed measurement reference values, a target cruise path is determined from the multiple cruise paths. Then, a cruise path is constructed in a non-reference area based on the target cruise path, and the cruise device is guided along this path to collect data, obtaining dynamic wind resource measurement data for the non-reference area. Finally, based on the dynamic wind resource measurement data from both the reference and non-reference areas, multiple potential wind turbine locations are determined within the wind farm development area by analyzing wind power output, wind power cost, and grid electricity costs.

[0056] This scheme uses a fixed measurement reference value of the target wind resource index determined in the reference area as a reference, and compares it with the data collected by actual dynamic cruise to achieve the screening of the cruise path. Furthermore, based on the screened target cruise path, cruise and data collection are carried out in non-reference areas. This method does not require setting up wind measurement towers throughout the wind farm construction area; it only requires setting up towers in a limited reference area. The dynamic measurement method in the reference area is used as an example and extended to non-reference areas, achieving effective reuse of the cruise path and enabling the selection of wind turbine locations within the entire wind farm construction area. Therefore, this invention reduces the number of wind measurement towers, lowers measurement costs, and improves the utility of measurement data. By using a limited number of fixed-point measurements from a few wind measurement towers and dynamic data measurement from mobile cruise equipment, wind turbine location selection can be easily achieved. Since the target cruise path is determined after analyzing the matching between dynamic and fixed measurement reference values, the accuracy of the final selected wind turbine locations can be guaranteed, which is beneficial to the power production work in wind power scenarios. Attached Figure Description

[0057] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0058] Figure 1 is a flowchart of a wind turbine location selection method for a wind farm provided by an embodiment of the present invention;

[0059] Figure 2A is a flowchart illustrating an example of how to delineate reference and non-reference areas and generate a fixed point layout scheme for the wind measurement towers in the reference area when the expected wind power generation scale is the first level.

[0060] Figure 2B is a schematic diagram of the reference area and the non-reference area formed in the wind farm construction area when the expected wind power generation scale is the first level scale.

[0061] Figure 3A is a flowchart illustrating an example implementation of delineating reference and non-reference areas and generating a fixed point layout scheme for the wind measurement towers in the reference area when the expected wind power generation scale is the second level.

[0062] Figure 3B is a schematic diagram of the reference area and non-reference area formed in the area to be built of the wind farm when the expected wind power generation scale is the second level scale.

[0063] Figure 3C is a schematic diagram of the effect of the fixed point layout scheme of the wind measurement tower in the reference area;

[0064] Figure 4 is a flowchart of another method for selecting wind turbine locations in a wind farm provided by an embodiment of the present invention;

[0065] Figure 5 is a schematic diagram of wind turbine location selection in a wind farm based on deep learning and reinforcement learning;

[0066] Figure 6 is a schematic diagram of a wind turbine location selection device for a wind farm provided in an embodiment of the present invention. Detailed Implementation

[0067] Currently, in the field of wind power technology, it is generally necessary to rely extensively on meteorological towers to measure parameters at many fixed points. However, meteorological towers are expensive, and building a large number of them would obviously require a considerable expense for large-scale power plants. Therefore, the high cost of wind turbine site selection is currently a major obstacle to promoting wind turbine site selection.

[0068] To address this problem, the inventors have proposed a method and related apparatus for selecting wind turbine locations in wind farms. This scheme uses fixed measurement reference values ​​of target wind resource indicators determined in a reference area as a benchmark, and compares these with data collected during actual dynamic patrols to achieve path selection. Based on the selected target patrol path, patrols and data collection are conducted in non-reference areas. This eliminates the need to deploy wind measurement towers throughout the proposed wind farm area; towers are only required within a limited reference area. This effectively reduces the number of towers needed, lowers measurement costs, saves on tower investment, and makes wind turbine location selection easier.

[0069] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0070] Figure 1 is a flowchart of a wind turbine location selection method for a wind farm according to an embodiment of the present invention. As shown in Figure 1, the wind turbine location selection method for a wind farm includes:

[0071] S101. Obtain fixed wind resource measurement data at multiple fixed points by setting up multiple wind measurement towers in the reference area within the wind farm construction area.

[0072] In this embodiment of the invention, the wind farm construction area refers to the area where a wind farm is planned to be built. Within this area, wind turbine locations need to be selected, and then wind turbines are subsequently installed at the corresponding locations to achieve the actual construction of the wind farm. In this embodiment, steps S101 to S107 describe the specific process for selecting suitable wind turbine locations.

[0073] In practical applications, based on wind power generation needs, the initial selection of wind farm construction areas can be made by considering factors such as wind energy resources, topography, climate conditions, transportation conditions, and grid connection conditions in different regions. Furthermore, the required area and geographical scope of the wind farm to be inspected can be determined based on the anticipated wind power generation scale.

[0074] In a specific implementation of this invention, in order to reduce the investment cost of wind resource measurement, it is proposed to first set up a wind measurement tower in the reference area of ​​the wind farm to be built, and then carry out patrol and data collection work in the non-reference area based on the actual measurement of wind resources in the reference area (including fixed measurement and dynamic measurement of patrol equipment).

[0075] To facilitate understanding of the reference area settings, the following section will explain the selection of the reference area.

[0076] In this invention, the reference area refers to the area where wind measurement towers need to be installed, while non-reference areas do not require wind measurement towers, thus saving on the cost of wind resource measurement. Furthermore, the wind measurement towers within the reference area can be installed according to a generated fixed-point layout plan, rather than randomly or without basis. This orderly arrangement of wind measurement towers also facilitates the planning of multiple cruise paths within the reference area.

[0077] Therefore, before obtaining fixed wind resource measurement data at multiple fixed points by setting multiple wind measurement towers in a reference area within the wind farm construction area, the present invention may further include: determining the expected wind power generation scale and geographical environmental characteristics of the wind farm construction area; delineating a reference area and a non-reference area within the wind farm construction area based on the expected wind power generation scale and geographical environmental characteristics, and generating a wind measurement tower fixed point layout scheme for the reference area.

[0078] In other words, in the technical solution of this invention, the delineation of the reference area and the generation of the fixed point layout scheme of the wind measurement tower mainly depend on the specific circumstances of the expected wind power generation scale and geographical environment characteristics.

[0079] In this embodiment of the invention, the method for determining the expected wind power generation capacity of the area where the wind farm is to be built includes:

[0080] Obtain the expected installed wind power capacity within the area where the wind farm is to be built; then, based on the mapping relationship between the range of wind power capacity and the scale of wind power generation, determine the expected scale of wind power generation in the area where the wind farm is to be built.

[0081] For example, several mapping relationships between wind power capacity and wind power generation scale can be pre-defined. For instance: wind power capacity below 100MW corresponds to the first-level wind power generation scale (referred to as the first-level scale); wind power capacity above 500MW corresponds to the second-level wind power generation scale (referred to as the second-level scale); and wind power capacity within the range of 100MW to 500MW (inclusive of both ends) corresponds to the third-level wind power generation scale (referred to as the third-level scale). The mapping relationships between wind power capacity ranges and wind power generation scales illustrated above can be found in Table 1 below. Here, the first-level scale can be understood as a small-scale wind farm, the second-level scale as a large-scale wind farm, and the third-level scale as a medium-scale wind farm. From this relationship, it can be seen that the order of the first-level scale, second-level scale, and third-level scale is: first-level scale < third-level scale < second-level scale.

[0082] Table 1

[0083] Based on the examples in the table above, it's easy to see that if we know the expected installed wind power capacity within the area where the wind farm is to be built, and combine this with the mapping relationship between the range of wind power capacity and the scale of wind power generation, we can determine the expected scale of wind power generation in the area. It should be noted that the classification of wind power generation scale and capacity range in the above mapping relationship are just one example. In practical applications, other classification methods or capacity classification methods may be used to form a mapping relationship different from that in Table 1. Therefore, no specific numerical limitations are made here regarding the specific classification method, capacity classification method, and the mapping relationship between them.

[0084] The following is an example implementation of defining reference and non-reference areas and generating a fixed point layout scheme for the wind measurement towers in the reference area.

[0085] Figures 2A and 2B graphically illustrate the scenario where the expected wind power generation scale is Level 1. Figure 2A is a flowchart illustrating an example implementation of delineating reference and non-reference areas and generating a fixed arrangement of anemometer tower locations within the reference area when the expected wind power generation scale is Level 1. Figure 2B is a schematic diagram illustrating the reference and non-reference areas formed within the wind farm development area when the expected wind power generation scale is Level 1.

[0086] Figures 3A and 3B graphically illustrate the scenario where the expected wind power generation scale is Level 2. Figure 3A is a flowchart illustrating an example implementation of delineating reference and non-reference areas and generating a fixed layout scheme for the anemometer towers within the reference area when the expected wind power generation scale is Level 2. Figure 3B is a schematic diagram illustrating the reference and non-reference areas formed within the area to be built in the wind farm when the expected wind power generation scale is Level 2.

[0087] (1) If the expected wind power generation scale is the first-level scale:

[0088] S201. The number of fixed locations for wind measurement towers is determined based on the expected scale of wind power generation.

[0089] Please refer to Figure 2B, which shows the area where a wind farm with a planned installed wind power capacity of 50MW is to be built, and its expected wind power generation scale meets the first-level scale. Therefore, the reference area and non-reference area can be delineated using the process S201 to S203 shown in Figure 2A.

[0090] In practical applications, the number of wind measurement tower locations can be set based on the expected wind power capacity to be installed within the planned wind farm area. For example, one tower can be set for every 25MW, so two towers would be needed for 50MW, three for 75MW, and four for nearly 100MW. Alternatively, the number of towers can be fixed based on the expected wind power generation scale; for example, if the expected wind power generation scale is the first-tier scale, then two wind measurement towers would be set by default.

[0091] S202. Based on the number of fixed points of the wind measurement towers and the geographical characteristics of the wind farm area to be built, set the location information of the fixed points of the wind measurement towers.

[0092] In practical applications, as a possible approach, if the geographical characteristics of the area where the wind farm is to be built indicate that the area contains special areas (such as wind gaps, areas with abrupt changes in elevation, or areas with abrupt changes in air density), then the wind turbines built in such special areas may generate greater wind power output. Therefore, fixed locations for wind measurement towers can be prioritized in these special areas.

[0093] For example, in Figure 2B, points 111 and 112 represent the fixed locations of the wind measuring towers. Since the latitude and longitude range of a special area can be measured through geographic information or other imagery methods, the location information of the fixed locations of the wind measuring towers within that area, including longitude and latitude, can be set.

[0094] In practical applications, different fixed locations for wind measurement towers can be set based on the same longitude or latitude. For example, the fixed locations of wind measurement towers may have the same longitude but different latitudes; or the fixed locations of wind measurement towers may have the same latitude but different longitudes. In addition, they can also be set according to the shape or range of a special area, such as setting two fixed locations of wind measurement towers diagonally opposite each other in the same special area.

[0095] S203. Based on the location information of the fixed points of the wind measurement tower, the area where the fixed points of the wind measurement tower are located in the area to be built of the wind farm is taken as the reference area, and the remaining areas are taken as non-reference areas.

[0096] Referring to Figure 2B, after setting the positions of the fixed points 111 and 112 of the meteorological towers, the plot area 11 where the two points are located can be used as the reference area. The remaining area 12 is used as the non-reference area. Since the positions of the fixed points of the meteorological towers have already been set in S202, the generation of the arrangement scheme of the fixed points of the meteorological towers within the reference area has been completed. Therefore, the content of the point arrangement in this scenario embodiment will not be described again here.

[0097] (2) If the expected wind power generation scale is the second level scale:

[0098] S301. Based on the expected scale of wind power generation, the area to be built for wind farms is divided into multiple zones.

[0099] Please refer to Figure 3B, which shows the area to be built for a wind farm with a planned installed wind power capacity of 1000MW, and its expected wind power generation scale meets the second-level scale. Therefore, the reference area and non-reference area can be delineated using the process S301 to S303 shown in Figure 3A, and the fixed point layout scheme of the wind measurement tower can be generated using the process S304 to S305 shown in Figure 3A.

[0100] In Figure 3B, the wind farm development area 20 is divided into 20 zones, namely S1 to S20. As an example, the number of zones can be set according to the expected wind power generation scale or the expected installed wind power capacity in the wind farm development area.

[0101] For example, if the expected installed wind power capacity in the area to be built for a wind farm is 1000MW, then the multiple of this value to 50MW is rounded down. The rounded value is used as the number of zones to be demarcated. It should be noted that the wind power capacity used as the denominator in the calculation can be selected from the range of wind power capacity corresponding to the first generating scale. For example, the denominator can be set to 50MW, 80MW, or even the upper limit of the range of wind power capacity corresponding to the first generating scale, such as 100MW.

[0102] In addition, a default number of zones can be set for each type of wind power generation scale, so that after confirming the expected wind power generation scale of the area to be built, the number of zones that should be divided can be determined directly.

[0103] In the example of Figure 3B, the ratio of 1000MW to 50MW is calculated and rounded to determine that the wind farm development area 20 should be divided into 20 zones. Subsequently, these 20 zones can be further divided based on the terrain characteristics and geographical scope of the wind farm development area, such as S1 to S20 in Figure 3B. Dividing the entire wind farm development area into zones facilitates the overall planning and management of wind resource measurements.

[0104] S302. Based on the expected wind power generation scale and the number of designated zones, determine the expected wind power generation scale for each zone.

[0105] Based on the expected wind power generation capacity of the area to be developed for the wind farm and the number of designated zones, the expected wind power generation capacity for each zone can be determined. Specifically, the expected installed wind power capacity within the area to be developed for the wind farm can be divided by the number of zones, and the calculated result can be compared with the ranges of wind power capacity mentioned above. If the calculated result falls within a certain range of wind power capacity, the expected wind power generation capacity for each zone can be determined based on the mapping relationship between the range of wind power capacity and the wind power generation capacity. For example, the calculated expected wind power generation capacity for each zone can be determined as the first-level scale. The purpose of determining the expected wind power generation capacity for each zone is to estimate the approximate wind power load level of the reference area after selecting it, thereby guiding the setting of the number of fixed points for wind measurement towers.

[0106] S303. Based on the geographical environmental characteristics of the area to be built in the wind farm, select one or more zones as reference areas, and the connected areas of the remaining zones as non-reference areas.

[0107] In selecting the reference area, the geographical characteristics of the area to be developed for the wind farm can also be taken into account. For example, if the geographical characteristics of the area indicate that it contains special areas, then the areas that overlap with these special areas should be prioritized as the reference areas. Here, overlap can refer to an overlap of 50% or more, or even 80% or more. The reference ratio for the overlap percentage can be set according to actual needs and is not limited here.

[0108] Special areas include various types such as wind gaps, areas with abrupt changes in elevation, and areas with abrupt changes in air density. Wind gaps refer to wind-increasing zones formed by the actual geographical environment, resembling funnels or other shapes. Selecting reference areas based on these special areas makes the placement of the anemometer tower more meaningful for selecting wind turbine locations. Generally, if the anemometer tower is poorly located, the final selected wind turbine locations may be unscientific and inaccurate, resulting in a significant reduction in wind resource utilization and waste of wind resources. However, in this embodiment of the invention, by analyzing whether the area to be developed for the wind farm contains special areas and then setting reference areas, it helps to improve wind resource utilization, allowing the selected wind turbine locations to achieve greater wind power output.

[0109] In the example of Figure 3B, the white-background partition S5 is the reference region, and the connected regions of the other gray-background partitions S1 to S4 and S6 to S20 are the non-reference regions.

[0110] S304. The number of fixed points for wind measurement towers is set based on the expected wind power generation scale corresponding to the reference area.

[0111] Multiple fixed locations for wind measurement towers can be set within the reference area to complete subsequent fixed wind resource measurements using the towers established at these locations. The number of fixed locations for wind measurement towers within the reference area can still be determined by referring to the expected wind power generation capacity corresponding to the reference area.

[0112] For example, if the expected wind power generation capacity corresponding to the reference area is at the first-level, then 20 fixed locations for wind measurement towers will be set. It should be noted that the number of fixed locations for wind measurement towers set within the reference area also needs to be considered in conjunction with factors such as geographical characteristics and cost, and the number of fixed locations for wind measurement towers is not strictly limited.

[0113] S305. Generate a layout scheme for fixed points of wind measurement towers based on the geographical environmental characteristics of the reference area.

[0114] After determining the number of fixed meteorological tower locations through S304, the layout design of these locations can be further generated by considering the geographical characteristics of the reference area. For example, if a small area within the reference area is a special region, more fixed meteorological tower locations can be set up for that special region. Furthermore, the resulting layout can be along the outline of the reference area or at equal intervals within the reference area. No restrictions are placed on the resulting layout of the fixed meteorological tower locations.

[0115] Figure 3C exemplifies the effect of a wind measurement tower fixed point layout scheme formed within a reference area. In Figure 3C, the green-background area represents the reference area within the wind farm construction area, and its edges are defined by the five vertices K1, K2, K3, K4, and K5 in Figure 3C. It can be seen that the outline of the reference area can also be an irregular graphic outline. Nineteen wind measurement fixed points A1 to A19 are marked within the reference area. It is easy to see from Figure 3C that in this example, the wind measurement fixed points are almost evenly distributed throughout the reference area. Of course, Figure 3C is only one layout example; in other possible implementations, the wind measurement tower fixed points can also be arranged only within a local area of ​​the reference area.

[0116] The above content, with reference to Figures 2A and 2B, illustrates the delineation of the reference area and the generation of the fixed-point layout scheme for the expected wind power generation scale of Level 1. Figures 3A to 3C illustrate the delineation of the reference area and the generation of the fixed-point layout scheme for the expected wind power generation scale of Level 2. For other possible scales, such as Level 3, the approach can be similar to that of Level 1 or Level 2; no limitation is made here. Furthermore, the classification of wind power generation scale is not limited to that shown in Table 1; it can also be divided into only two types: Level 1 and Level 2. In this case, the upper limit of the wind power capacity corresponding to Level 1 can be adjacent to the lower limit of the wind power capacity corresponding to Level 2.

[0117] Based on the foregoing, wind measurement towers can be constructed according to a fixed-point layout scheme. Furthermore, wind resource data can be measured and collected using the wind measurement equipment on the towers.

[0118] In one possible implementation, a wind measuring instrument is used as the wind measuring device, based on the wind measurement needs of the wind farm and taking into account the current internationally accepted wind farm resource assessment calculation requirements.

[0119] The main performance indicators of the anemometer are as follows: wind speed range: 0~70m / s, wind speed error: <0.1m / s; wind direction range: 0~360°, wind direction error: <0.1°. While measuring wind speed, the anemometer can also record other types of data, such as temperature and pressure. These data can be used to indirectly calculate air density. Air density refers to the mass of air per unit volume, and it is closely related to factors such as air temperature, pressure, and humidity. For example, by measuring air temperature and pressure, air density can be estimated using the ideal gas law (PV=nRT). Furthermore, the anemometer can be combined with data from other meteorological observation equipment, such as hygrometers and barometers, to more accurately assess air density.

[0120] In one possible implementation, wind vanes and anemometers are installed at several different heights on the wind measuring tower. For example, one set of wind vanes is installed at heights ranging from 10m to 160m above the ground (the 10m height can be adjusted to 15m or 30m depending on the local vegetation and micro-topography); one set of anemometers is installed at heights of 10m, 50m, 80m, 100m, 120m, and 140m above the ground, and two sets of anemometers are installed at the 160m height (the 10m height can be adjusted to 15m or 30m depending on the local vegetation and micro-topography). Furthermore, a set of air temperature measuring instruments and a set of barometric pressure measuring instruments can be installed at a height of 10m above the ground. This allows for the collection of a wider variety of fixed wind resource measurement data.

[0121] The following is an example of obtaining fixed measurement data of wind resources using instruments installed on a wind measurement tower:

[0122] The wind speed sampling interval shall not exceed 3 seconds (the proposed NRG anemometer has a sampling interval of 2 seconds), and the system shall automatically calculate and record the average wind speed every 10 minutes, the standard deviation of wind speed every 10 minutes, the maximum wind speed within every 10 minutes, and the corresponding time and direction. Wind speed shall be measured in m / s. The wind direction sampling interval shall not exceed 3 seconds (the proposed NRG anemometer has a sampling interval of 72 seconds), and the system shall automatically calculate and record the average wind direction value every 10 minutes. Wind direction shall be measured in degrees. Fixed wind resource measurement data can be collected automatically via remote reception of data via Internet email or through on-site acquisition. After data collection, it is necessary to process and analyze the data to check its rationality. If any problems are found, staff must promptly go to the site to check the instrument and troubleshoot the fault.

[0123] S102. Based on fixed measurement data of wind resources at multiple fixed locations, determine the fixed measurement reference value of the target wind resource index within the reference area.

[0124] Fixed wind resource measurement data can include various types of data such as latitude and longitude coordinates, wind speed, air density, and elevation. Furthermore, based on this data, data such as annual power generation and equivalent operating hours can be calculated.

[0125] Table 2 below illustrates a wind measurement parameter table. Annual power generation is calculated based on wind speed and air density, while the equivalent hours are calculated by dividing the annual power generation by the wind turbine's rated power output per hour. Numbers A1 to A19 correspond to the 19 fixed locations of the wind measurement towers in the example arrangement shown in Figure 3C.

[0126] Table 2

[0127] The target wind resource index is one of several types of wind resource indices within fixed wind resource measurement data. In one possible implementation, the target wind resource index is specifically wind speed. Alternatively, annual power generation and equivalent operating hours can also be used as target wind resource indices. The specific type of wind resource index is not limited here.

[0128] If the target wind resource indicator is wind speed, based on fixed measurement data of wind resources at multiple fixed locations, a fixed measurement reference value for the target wind resource indicator within the reference area can be determined, which may include:

[0129] Wind speed measurements were extracted from multiple fixed-point wind resource data, as shown in the wind speed column of Table 2. The median or average of these measurements was then used as the fixed reference value for wind speed in the reference area.

[0130] Taking Table 2 as an example, the last row shows the average value of 8.19 m / s among multiple fixed-point measurements of wind speed. In other possible embodiments, the median of multiple fixed-point measurements can also be used as the fixed measurement reference value for the corresponding indicator. The fixed measurement reference value represents the average situation (or mid-range situation) of the fixed measurement data. Because this value does not involve extreme values, it is generally representative of fixed measurements in the reference area, and therefore can be used as a benchmark for comparison with dynamic measurement data.

[0131] Table 2 shows the wind speed, air density, and calculated annual power generation and equivalent hours at specific elevations for fixed locations of wind measurement towers at different latitudes and longitudes. The calculation of average wind power density should be based on the average hourly wind power density over a given time period. Therefore, to improve measurement speed and accuracy over the measurement period while saving costs, lightweight aluminum tubes or rectangular arrays with eight measuring points at different elevations (between 10m and 160m) can be installed on the aircraft structure, significantly improving measurement time, speed, and accuracy. It should be noted that in practical applications, the annual power generation of a single fixed location can be calculated cumulatively over multiple time intervals. Table 3 below shows the wind resource indicators for a fixed location A1 over multiple consecutive time intervals.

[0132] Table 3

[0133] As shown in Table 3, to calculate the power generation at a fixed location, wind resource indicators such as wind speed and air density at that location can be continuously measured for 24 hours, and corresponding data for each hour can be obtained, including power generation and equivalent hours. The wind speed can be averaged, with 8.18 m / s representing the actual wind speed at that fixed location, and this value is recorded in Table 2. The calculation of power generation for a given hour relies on the following formula:

[0134] In this formula, V represents wind speed, E represents power generation, P(V) is the power curve, and P(V) is a function of wind speed. `cutin` and `cutout` represent the cut-in and cut-out wind speeds of the wind turbine, respectively. `f(V)` is the probability density function of wind speed, expressed by the formula below:

[0135] In this formula, The value represents the average wind speed. The parameters c and k are two parameters in the Weibull distribution. The Weibull distribution is a probabilistic model commonly used to describe the frequency distribution of wind speed. c is the scale parameter, which determines the central location and scale of the wind speed data, reflecting the overall level of the wind speed distribution. In the Weibull distribution, a higher scale parameter value means the distribution tends towards larger wind speed values. k is the shape parameter, which greatly influences the shape of the Weibull distribution curve. It determines the frequency of extreme values ​​in the dataset and the sharpness of the distribution curve. When the value of k is large, the distribution curve becomes sharp, meaning that the variability of wind speed is greater, and the probability of extreme values ​​(such as high-speed or low-speed winds) increases. This usually indicates that the average wind speed varies less, but the range of wind speed fluctuations is larger. When the value of k is small, the distribution curve becomes flatter, indicating that the wind speed varies more evenly, with fewer extreme values. This usually means that the average wind speed is larger, but the range of wind speed fluctuations is relatively smaller.

[0136] Based on a year of 365 days, there are a total of 8760 hours. After calculating the power generation per hour using the above formula, multiplying this by the total number of hours in a year (8760) gives the annual power generation of 24,663,900 kWh. This value is recorded in Table 2 regarding the annual power generation of fixed location A1. The above example uses fixed location A1; in practical applications, the annual power generation of each fixed location can be calculated using the same formula.

[0137] S103. By controlling the mobile patrol device to conduct multiple patrols in the reference area along various patrol paths, the mobile patrol device can collect data during the patrol and obtain multiple sets of dynamic wind resource measurement data of the reference area.

[0138] This invention proposes a method to dynamically measure wind resource indicators within a reference area by controlling a mobile patrol device to cruise within that area. The mobile patrol device can be a small aircraft, drone, or similar device. It is equipped with one or more sensors for collecting wind resource indicator data. These sensors collect dynamic measurement data of wind resources, which is then used to analyze suitable patrol paths.

[0139] The aircraft can rotate 360 ​​degrees, which makes the subsequent model simulation of the wind turbine rotation more accurate, and can also determine the appropriate wind turbine orientation, thus realizing digital twin.

[0140] In this embodiment of the invention, the cruise device collects data by conducting multiple cruises along several different cruise paths, combined with multiple fixed points. For example, three cruise paths are pre-set: a first cruise path, a second cruise path, and a third cruise path. Three cruises are conducted within a reference area along these three cruise paths, generating a first set of dynamic wind resource measurement data, a second set of dynamic wind resource measurement data, and a third set of dynamic wind resource measurement data. Each set of dynamic wind resource measurement data corresponds to the cruise path used in one cruise within the reference area.

[0141] Upon reaching each measurement point on the cruise path, the cruise equipment can be controlled to move in the altitude direction to obtain dynamic wind resource measurement data at different elevations for the same measurement point. Each cruise path includes multiple locations with the same longitude and latitude but different elevations, allowing the mobile cruise equipment to collect data at multiple different elevations for these locations during the cruise. Fixed wind resource measurement data for each fixed point includes fixed wind resource measurement data at different elevations for the longitude and latitude indicated by that fixed point. It should be noted that for measurement points and fixed points of the meteorological tower that are close in location, the elevations used for dynamic and fixed measurements can be the same or similar, thus ensuring data comparability under the same or similar elevation conditions.

[0142] The following is an example illustrating dynamic measurement.

[0143] First, given the established reference area and pre-set measurement points, the cruise path is determined, and the coordinates of each measurement point along the cruise path are input into the aircraft's controller. Furthermore, the dwell time and flight time at each measurement point are determined based on weather forecasts and also input into the aircraft's controller.

[0144] The aircraft consists of three functional parts: first, traction to generate horizontal force to move the measuring rod; second, vertical ascent and descent to control the height of the measuring point, where the measuring point is vertically tractioned to determine the height, and after reaching the height, a command is issued and the spring locks the height of the measuring point; and third, dynamic measurement, where the aircraft carries its own measuring point, takes off at regular intervals to a specific altitude, and cruises.

[0145] As mentioned earlier, multiple cruises are conducted using multiple cruise paths. These cruise paths can be planned using pre-defined measurement points, or they can be newly planned based on the comparison between dynamic measurement data generated after each cruise and the aforementioned fixed measurement data. The comparison method will be specifically explained in step S105, as detailed below. For example, deep learning can be used to replan new cruise paths to measure wind resource data. For elevation, eight elevation points consistent with those used in fixed measurements are set within the 10m to 160m range as measurement points to measure wind speed and air density, facilitating the comparison between dynamic and fixed measurement data. The purpose of deep learning is to plan dynamic measurement cruise paths that more closely approximate the data results from fixed measurements.

[0146] S104. For each set of dynamic wind resource measurement data in the multiple sets of dynamic wind resource measurement data, calculate the dynamic measurement reference value of the target wind resource index.

[0147] To enable the comparison between dynamic and fixed measurement data, and subsequently the selection of the target cruise path, this embodiment of the invention proposes calculating a dynamic measurement reference value for the target wind resource index for each set of dynamic wind resource measurement data. For example, based on the first set of dynamic wind resource measurement data, a first dynamic measurement reference value for the target wind resource index is calculated; based on the second set of dynamic wind resource measurement data, a second dynamic measurement reference value for the target wind resource index is calculated; and based on the third set of dynamic wind resource measurement data, a third dynamic measurement reference value for the target wind resource index is calculated.

[0148] Taking wind speed as the target wind resource indicator as an example, this step involves extracting dynamic wind speed measurement datasets from each set of dynamic wind resource measurement data. For each dynamic measurement dataset, the mean wind speed is calculated and used as the dynamic measurement reference value for that set of dynamic wind resource measurement data. Since the mean wind speed reflects the overall average condition of this set of dynamic wind resource measurement data, it can be used as a dynamic measurement reference value for comparison with a fixed measurement reference value. In practical applications, by combining the dynamic and static measurement data to be compared, data with similar elevations can be selected for comparison. For example, dynamic and fixed wind speed measurement reference values ​​with elevations approximately 50m above the ground can be selected for matching and determination.

[0149] S105. Based on the matching between the calculated dynamic measurement reference values ​​of the target wind resource index and the fixed measurement reference values ​​of the target wind resource index, a target cruise path is determined from multiple cruise paths.

[0150] In one possible implementation of this step, the absolute values ​​of the differences between multiple dynamic measurement reference values ​​and fixed measurement reference values ​​of the target wind resource index are calculated. These multiple dynamic measurement reference values ​​originate from multiple different cruise paths. It is understood that the smaller the absolute value of the difference, the smaller the discrepancy between the two values ​​being compared. Based on the correspondence between the dynamic wind resource measurement data and the cruise paths, the cruise path corresponding to the dynamic measurement reference value with the smallest absolute value of the difference from the fixed measurement reference value is determined as the target cruise path.

[0151] S106. Construct a cruise path in the non-reference area within the wind farm construction area based on the target cruise path, and control the mobile cruise device to cruise in the non-reference area based on the constructed cruise path, so that the mobile cruise device can collect data during the cruise and obtain dynamic measurement data of wind resources in the non-reference area.

[0152] Because the dynamic measurement data obtained from the target cruise path has the highest matching degree with the data from the fixed measurements of the wind towers, the specific shape of this path can also be reused in the dynamic measurement of data in non-reference areas. For example, if the target cruise path is an "S" shaped path, then an "S" shaped path cruise is also used in non-reference areas; if the target cruise path is a "T" shaped path, then a "T" shaped path cruise is also used in non-reference areas. This operation can reduce the setting of wind towers, and accurate measurements can be achieved by using low-cost aircraft or drones to replace the construction costs of large-scale wind towers. In addition, various cruise paths can be calculated and planned based on deep learning, driven by data, realizing the efficient utilization of fixed and dynamic measurement data within the reference area. The resulting data assets assist in data matching comparison, path planning, and target cruise path selection, providing strong data support for the selection of wind turbine locations, reducing manual calculation costs and path planning difficulty, and simultaneously improving the accuracy and effectiveness of wind turbine location selection.

[0153] S107. Based on the dynamic measurement data of wind resources in the reference area and the dynamic measurement data of wind resources in the non-reference area, by analyzing wind power output, wind power cost and grid electricity cost, multiple wind turbine locations to be built in the wind farm construction area are determined.

[0154] In this embodiment of the invention, dynamic wind resource measurement data from a reference area and dynamic wind resource measurement data from non-reference areas can be considered comprehensively. Since the fixed wind resource measurement data from the reference area matches the dynamic wind resource measurement data collected along the target cruise path, the dynamic wind resource measurement data from the reference area specifically refers to the dynamic wind resource measurement data collected along the target cruise path. Alternatively, this step can also be understood as determining multiple potential wind turbine locations within the wind farm development area by analyzing wind power output, wind power cost, and grid electricity cost based on the fixed wind resource measurement data from the reference area and the dynamic wind resource measurement data from non-reference areas.

[0155] In one possible implementation, in conjunction with Table 2, both fixed wind resource measurement data and dynamic wind resource measurement data can include the following types of wind resource indicators: latitude and longitude coordinates, wind speed, air density, and elevation.

[0156] The implementation process of this step may specifically include:

[0157] Based on dynamic wind resource measurement data from both the reference and non-reference areas, multiple wind turbine site construction plans are generated. Each plan includes the latitude and longitude coordinates, elevation, and annual power generation of the wind turbines to be constructed. The annual power generation is calculated based on wind speed and air density. In one possible example, some wind turbine sites may be shared between each plan. In another possible example, the elevations of the wind turbines may differ between plans; for example, in the first plan, all turbines are at 150m, in the second plan, all are at 50m, and in the third plan, the elevations are inconsistent. The elevation referred to here is relative to the ground level. However, the elevations in Table 2 are altitudes (i.e., absolute elevations), thus showing values ​​exceeding 500m.

[0158] Based on annual power generation, wind power costs, and grid electricity costs, the feasibility of multiple wind turbine site construction plans is analyzed. Finally, the construction plan with the highest feasibility is used to determine multiple wind turbine sites to be built. For example, if the feasibility analysis determines that the second wind turbine site construction plan is the most feasible, the latitude and longitude coordinates, elevation, and other information of the multiple wind turbines to be built included in the second wind turbine site construction plan are extracted as information for the wind turbine sites to be built, for reference and use in subsequent wind turbine construction.

[0159] In conjunction with S101 to S107, the technical solution of this invention obtains fixed wind resource measurement data at multiple fixed points within a reference area using a wind measurement tower, and based on this, a fixed measurement reference value for the target wind resource index within the reference area can be obtained. Furthermore, multiple sets of dynamic wind resource measurement data are collected through multiple cruises within the reference area using a cruise device with various cruise paths, and the dynamic measurement reference value for the target wind resource index is calculated. Based on the matching between the dynamic measurement reference value and the fixed measurement reference value, a target cruise path is determined from the multiple cruise paths. Then, a cruise path is constructed in a non-reference area based on the target cruise path, and the cruise device is guided along this path to collect data, obtaining dynamic wind resource measurement data for the non-reference area. Finally, based on the dynamic wind resource measurement data of the reference and non-reference areas, multiple wind turbine locations to be built are determined within the wind farm development area by analyzing wind power output, wind power cost, and grid electricity costs.

[0160] This scheme uses a fixed measurement reference value of the target wind resource index determined in the reference area as a reference, and compares it with the data collected by actual dynamic cruise to achieve the screening of the cruise path. Furthermore, based on the screened target cruise path, cruise and data collection are carried out in non-reference areas. This method does not require setting up wind measurement towers throughout the wind farm construction area; it only requires setting up towers in a limited reference area. The dynamic measurement method in the reference area is used as an example and extended to non-reference areas, achieving effective reuse of the cruise path and enabling the selection of wind turbine locations within the entire wind farm construction area. Therefore, this invention reduces the number of wind measurement towers, lowers measurement costs, and improves the utility of measurement data. By using a limited number of fixed-point measurements from a few wind measurement towers and dynamic data measurement from mobile cruise equipment, wind turbine location selection can be easily achieved. Since the target cruise path is determined after analyzing the matching between dynamic and fixed measurement reference values, the accuracy of the final selected wind turbine locations can be guaranteed, which is beneficial to the power production work in wind power scenarios.

[0161] Figure 4 is a flowchart of another wind turbine location selection method for a wind farm provided by an embodiment of the present invention. In Figure 4, starting from the area to be built in the wind farm, basic information such as basic elevation, wind speed, air density, and special areas is determined. Understanding the above information about the area to be built in the wind farm provides a data foundation, facilitating the subsequent selection of fixed and dynamic measuring points, as well as the selection of wind turbine types and locations. For the wind farm to be built, its expected power generation scale also needs to be determined, such as whether it is large-scale or small-scale. For small-scale wind farms, a small number of meteorological towers can be deployed for fixed measurements at a small number of measuring points. For large-scale wind farms, a reference area can be drawn after dividing the area into zones, and multiple meteorological towers can be set up within the reference area for fixed measurements. Furthermore, the aircraft flies based on a cruise path and achieves dynamic data acquisition from multiple measuring points. Based on digital data models and deep learning, the cruise path is adjusted to match the measured data with the data measured at fixed measuring points using a wind tower, so that the target cruise path has matching (referring to the mutual matching between dynamic and fixed measurements) and representativeness relative to the fixed measurement method.

[0162] Subsequently, by utilizing the target cruise path, dynamic wind resource measurement data can be obtained for both reference and non-reference areas within the entire wind farm construction area. Based on this, multiple wind turbine location deployment plans can be developed. By combining data such as the annual power generation of each wind turbine location, and even the annual power generation of the entire wind farm, cost estimation can be achieved. Through digital data models and digital analysis based on the above data, as well as digital analysis of the equipment, several measurement points with the highest feasibility can be identified as the selected wind turbine locations. After selection, recalculation can be performed, combining wind turbine type, measurement strategy, and wind turbine elevation to finally determine the wind turbine locations. Furthermore, correspondingly, feasibility analysis results of the plan can be provided.

[0163] This invention employs a data model and utilizes cruise measurements at different altitudes and dynamic measurements of wind resources to improve the certainty of the measured wind resource data and further enhance the certainty of wind turbine location selection. This, in turn, influences the selection of wind turbine locations within the entire wind farm development area. The data model digitizes the correlations between data such as wind turbine height, cost, annual power generation, annual cash flow, and the internal rate of return (IRR) of the wind farm project, facilitating turbine selection. It reduces the material and installation costs of the meteorological tower, and uses large-scale digital calculations of wind speed, air density, and altitude at various elevation measurement points to obtain annual power generation and annual utilization hours for each point. A beneficial cruise scheme (target cruise path) ensures that the temporal discontinuity of the aircraft measurements does not affect the measurement certainty, and spatially, it employs multi-point elevation measurements using corresponding fixed meteorological towers.

[0164] Corresponding to the different wind speeds at different altitudes, a data model calculation method is used to selectively determine the height of each wind measuring tower at the reference area's wind measurement points, in order to select the height with the best wind speed distribution and maximum wind speed. For manufacturers, instead of full-scale mass production, a digital "one-unit-one-policy" small-batch production is implemented. Then, based on the obtained wind speed distribution and the next year's power generation and altitude characteristics, the corresponding wind turbine measurement points are set. For wind farms, it is no longer about neatly installed wind turbines, but about maximizing power generation and optimizing economic costs based on digital measurements. This fully reflects the selection of wind turbines at different heights after digital correlation, so that the wind resources of wind vents and special geographical environments can be captured digitally, increasing the certainty of maximizing wind energy at the wind turbine measurement points.

[0165] Conventional methods focus solely on annual power generation, failing to reflect the inherent numerical logic of wind turbine height selection and cost, annual power generation, annual cash flow, and project return on investment (IRR). This invention's technical solution uses a dynamic data model to reflect the relationships between these cost-related quantities, creating a digital model connecting site selection, equipment selection, cost, and revenue. Site selection determines the basic wind speed, cost, and annual power generation in the measurement area, thus impacting power generation revenue. Furthermore, the final cash flow and IRR are not solely related to any single factor. For example, IRR is not only related to annual power generation but also to the selected wind measurement elevation, which in turn relates to the wind turbine type and height. Additionally, equipment depreciation is also related to equipment selection and cost (higher equipment costs but longer depreciation periods; by comprehensively incorporating relevant factors such as the elevation and wind speed at each measurement point, the final IRR is obtained for assessment).

[0166] Based on the feasibility analysis and comparison of multiple wind turbine site construction schemes, the following formula is proposed for analysis and comparison:

[0167] Formula 1: Annual cash flow = Annual revenue - Annual expenditure = Annual electricity consumption value * (Annual electricity price - LCOE per kilowatt-hour) = Annual electricity consumption value * Annual electricity price - Annual operating and equipment costs - Annual capital - Annual interest - Annual taxes;

[0168] Formula 2: LCOE (Levelized Cost of Electricity) = NPV (Net Cost) / NPV (Net Energy Output);

[0169] Formula 3: Annual operating and equipment costs = Operating costs * Depreciation rate;

[0170] Formula 4: Annual electricity cost = LCOE (Low Cost of Electricity) * Annual power generation;

[0171] Formula 5: Annual electricity revenue = Annual electricity price contract fee * Annual power generation

[0172] Here, revenue electricity charges can be understood as grid electricity charges. Revenue electricity charges are from the perspective of the power plant's profits, while cost electricity charges are from the perspective of the power plant's expenses.

[0173] Figure 5 is a schematic diagram of wind turbine site selection for wind farms based on deep learning and reinforcement learning. This invention innovatively utilizes historical meteorological data of surrounding wind resources to establish data features, employs large-sample deep learning, and small-sample statistical methods (such as normalization and / or median calculation) to input into the model operator. It replaces continuous-time measurement with discrete-time measurement and uses deep learning for approximation, making measurement more flexible and cost-effective, applicable even to large-scale measurement points and areas where wind towers are difficult to install (e.g., 100 meters high). Measurements from 10 to 100 meters measure wind speed and air density at different continuous elevations, determining the height of the wind turbine center. Although not continuous in time, it is spatially continuous due to the change in altitude, making it suitable for measurements in specific environments. For example, air density can be used to select whether to build the wind turbine on a mountain or at its foot, and wind speed differences and cost can be considered to determine whether to build the wind turbine at 100 meters or 120 meters. This method has significant characteristics and advantages for large areas with complex environments.

[0174] This invention innovatively utilizes historical meteorological data on surrounding wind resources; data acquisition and calibration, reinforcement learning for data calibration; model operator construction and scheme determination, and deep learning to achieve hierarchical representation of data. By calculating the loss function and updating the parameters and values ​​in the model operators under different schemes, better measurement schemes are obtained, making the schemes non-fixed, and obtaining the optimal scheme from deep learning.

[0175] The process and significance of deep learning in two stages:

[0176] For projects with lower cost requirements, deep learning is directly employed, establishing two wind measurement points. Other wind measurement points are then measured using the same cruise method. This ensures that data from the project location is compared with the data from these two wind measurement points for deep learning, while also ensuring that wind measurement data from points like wind gaps can be compared horizontally with data from other points, facilitating the identification of wind data at these locations and calculating wind energy through data correlation. For large-scale projects, assuming 20 zones are selected, one of which is chosen as a reference area using the method described in this case. Dynamic wind resource measurement data is collected via aircraft cruise, compared with fixed measurement data to determine compatibility, and then the target cruise path is selected. Through deep learning, the measured data from 10m to 160m can be correlated with fixed wind measurement devices, obtaining path, elevation, and wind speed data. This data is then used to train the system with fixed wind measurement point data, mapping its multivariate function to an electricity cost function, and selecting wind turbines at the most advantageous power generation height. Due to wind gap and geographical location factors, deep learning analysis continuously refines the measurement function to obtain the optimal wind turbine location.

[0177] The significance of multiple variables is illustrated in Figure 5, as air density, wind speed, and elevation are all multiple variables. The final electricity revenue obtained by substituting these variables into the electricity bill function is shown in Figure 5.

[0178] By creating reference data samples and setting up fixed-area wind measurement towers, the uncertainty of wind energy is reduced. Data feature extraction employs different methods for small and large sample data. Data is calibrated using data benchmarking, and weighted data is shared for transmission. Then, through reinforcement learning and other methods, the measured data, after calculation by operators, is compared with control production factor samples to achieve data cleaning. Model operators are established, such as wind energy density E operator, wind energy P operator, and F operator (electricity cost function), allowing the operator output of electricity costs to be used by other intelligent agents. Deep learning is used to calculate loss functions, update parameters, and feed back to model operators, causing changes in cruise, path, and elevation schemes, ultimately affecting the measured data and making the measured data approximate or find the optimal solution from the fixed measurement point data. Finally, because the environment in the same area, such as air density, elevation, and wind speed, is generally similar, and considering the different environmental parameters in a few areas, the optimal wind speed points are targeted to find. This method not only avoids the uncertainty of wind speed measurement but also enhances its ability to find the optimal wind turbine construction points. By transmitting various parameters in digital electricity, the final electricity bill can dynamically reflect the data correlation of digital electricity.

[0179] The formula for wind power output is as follows:

[0180] E (wind energy density) = (1 / 2) * ρ * V^3 (unit: W / m2)

[0181] It can be seen that wind energy density is directly proportional to the cube of the average wind speed V.

[0182] P (wind energy) = E * A * Cp

[0183] Where E represents wind energy density; A represents the rotor area, A = PI * R^2; R is the rotor radius; and Cp represents the rotor efficiency, with a maximum theoretical value of 0.593 according to Bets theory. Combining the formula for E, E is directly proportional to the cube of the wind speed and directly proportional to the air density. The height of the wind turbine determines the (variable) air density, while the swept area and the selection of the wind turbine determine the investment cost and the obtained turbine output. The above formula can be used to roughly calculate wind power output. In a specific area, different wind measurement points determine different outputs in digital power systems, highlighting the crucial role of data assets in both technology and economics.

[0184] As shown in Table 3 above, for data studies on fixed coordinates and elevations over a time period, further research is needed to understand the wind resource characteristics of various points in the region, such as wind resource characteristics in wind gaps or areas with special terrain. This allows for the optimization and arrangement of the orientation and location array of wind turbines, such as a "T"-shaped array corresponding to wind gaps. Based on the study of two parameters (shape parameter k and scale parameter c) in the Weibull distribution of wind resources, deep learning and reinforcement learning (as shown in Figure 5) can more specifically compare and calculate various parameters, which is beneficial for using more abstract hierarchical data to discover more abstract wind resource characteristics.

[0185] Further improvements require a more concrete approach: refining the model to include curves showing the wind turbine's output power at various wind speeds, both within the cut-in and cut-out wind speed ranges. These curves define the wind turbine's power characteristics and operational features, serving as a crucial factor in calculating power generation. The main influencing factors are multifaceted. Classified by formation conditions, power curves can be categorized into wind measurement power curves and actual operating power curves. Due to varying wind resource conditions across different wind farms, the theoretical power curve is used for power generation calculation. The static power curve, calculated under steady-state conditions, does not consider factors such as wind turbulence, inflow angle, wind speed shear, instantaneous wind speed fluctuations, wind deviation, wake, and turbine turbulence control, reflecting the turbine's steady-state performance. The dynamic power curve, on the other hand, represents the relationship between wind turbine power and wind speed. Unlike the static power curve, its input conditions include changes in wind speed over time and space, better reflecting the dynamic process and power characteristics of the wind turbine during actual wind farm operation. Therefore, the advantages of this case in dynamic space can be used to design a measuring device that better reflects the actual operation of the wind turbine, and can more specifically consider more physical quantities that affect the power generation of the wind turbine, thereby creating a more accurate measuring device in digital twin form, and making the cost lower and more controllable.

[0186] Based on the wind turbine location selection method for wind farms described in the foregoing embodiments, this invention also provides a wind turbine location selection device for wind farms. Figure 6 is a schematic diagram of the structure of the wind turbine location selection device for wind farms. As shown in Figure 6, the device includes: a fixed data acquisition module 601, a fixed measurement reference value determination module 602, a cruise control module 603, a dynamic measurement reference value calculation module 604, a path determination module 605, and a wind turbine location determination module 606.

[0187] The fixed data acquisition module 601 is used to obtain fixed measurement data of wind resources at multiple fixed points through multiple wind measurement towers set in the reference area of ​​the wind farm to be built.

[0188] The fixed measurement reference value determination module 602 is used to determine the fixed measurement reference value of the target wind resource index within the reference area based on fixed wind resource measurement data from multiple fixed points; the target wind resource index is one of the various types of wind resource indicators in the fixed wind resource measurement data;

[0189] The cruise control module 603 is used to control the mobile cruise device to cruise multiple times in a reference area using various cruise paths, so that the mobile cruise device can collect data during the cruise and obtain multiple sets of dynamic wind resource measurement data of the reference area; the mobile cruise device is equipped with one or more sensors for collecting wind resource index data; a set of dynamic wind resource measurement data corresponds to the cruise path used in one cruise in the reference area.

[0190] The dynamic measurement reference value calculation module 604 is used to calculate the dynamic measurement reference value of the target wind resource index for each set of dynamic measurement data in multiple sets of dynamic measurement data of wind resources.

[0191] The path determination module 605 is used to determine a target cruise path from multiple cruise paths based on the matching between multiple dynamic measurement reference values ​​of the target wind resource index and the fixed measurement reference value of the target wind resource index.

[0192] The cruise control module 603 is also used to construct a cruise path in the non-reference area within the wind farm to be built area based on the target cruise path, and control the mobile cruise device to cruise in the non-reference area based on the constructed cruise path, so that the mobile cruise device can collect data during the cruise and obtain dynamic measurement data of wind resources in the non-reference area.

[0193] The wind turbine location determination module 606 is used to determine multiple wind turbine locations within the wind farm construction area based on dynamic wind resource measurement data of the reference area and dynamic wind resource measurement data of the non-reference area, by analyzing wind power output, wind power cost and grid electricity cost.

[0194] In the optional implementation, the wind turbine location selection device for the wind farm also includes:

[0195] The power generation scale determination module is used to determine the expected wind power generation scale of the area where the wind farm is to be built;

[0196] The geographic environment feature determination module is used to determine the geographic environment features of the area where the wind farm is to be built;

[0197] The regional division and layout scheme generation module is used to delineate reference areas and non-reference areas within the wind farm construction area based on the expected wind power generation scale and geographical characteristics, and to generate a layout scheme for the fixed points of the wind measurement towers in the reference areas.

[0198] In the optional implementation, the region division and layout scheme generation module is specifically used for:

[0199] If the expected wind power generation scale is the first level, then the number of fixed points of the wind measurement towers is set based on the expected wind power generation scale. Based on the number and the geographical characteristics of the wind farm to be built area, the location information of the fixed points of the wind measurement towers is set. Based on the location information, the area where the fixed points of the wind measurement towers are located in the wind farm to be built area is used as the reference area, and the remaining areas are used as non-reference areas.

[0200] If the expected wind power generation scale is the second-level scale, then the area to be built for the wind farm is divided into multiple zones based on the expected wind power generation scale; the expected wind power generation scale corresponding to each zone is determined based on the expected wind power generation scale and the number of zones; based on the geographical characteristics of the area to be built for the wind farm, one or more zones are selected as reference areas, and the connected areas of the remaining zones are designated as non-reference areas; the number of fixed points for wind measurement towers is set based on the expected wind power generation scale corresponding to the reference areas; a wind measurement tower fixed point layout scheme is generated based on the geographical characteristics of the reference areas; the second-level scale is larger than the first-level scale.

[0201] In the optional implementation, the region division and layout scheme generation module is specifically used for:

[0202] If the geographical features of the area where the wind farm is to be built indicate that the area contains special areas, then the fixed locations of the wind measurement towers should be set in the special areas first.

[0203] Based on the geographical characteristics of the area where the wind farm is to be built, one or more zones are selected as reference areas, including: if the geographical characteristics of the area where the wind farm is to be built indicate that there are special areas within the area, then the zones that overlap with the special areas are selected as reference areas first.

[0204] In the optional implementation, the special region is at least one of the following types:

[0205] A wind gap is a region where the elevation changes abruptly, and where the air density changes abruptly.

[0206] In the optional implementation, the power generation scale determination module is specifically used for:

[0207] Obtain the expected installed wind power capacity within the area where the wind farm is to be built;

[0208] Based on the mapping relationship between the range of wind power capacity and the scale of wind power generation, the expected scale of wind power generation in the area where wind farms are to be built is determined.

[0209] In the optional implementation, the path determination module 605 is specifically used for:

[0210] Calculate the absolute value of the difference between multiple dynamic measurement reference values ​​and fixed measurement reference values ​​of the target wind resource index;

[0211] Based on the correspondence between dynamic wind resource measurement data and cruise paths, the cruise path corresponding to the dynamic measurement reference value with the smallest absolute value of the difference from the fixed measurement reference value is determined as the target cruise path.

[0212] In the optional implementation, each cruise path includes multiple location points with the same longitude and latitude but different elevations, so that the mobile cruise device can collect data at multiple different elevations for location points with the same longitude and latitude during the cruise.

[0213] The fixed wind resource measurement data for each fixed location includes wind resource measurement data at different elevations at the longitude and latitude indicated by that fixed location.

[0214] In the optional implementation methods, the target wind resource indicator is wind speed;

[0215] The fixed measurement reference value determination module is specifically used to: extract wind speed measurements from multiple fixed wind resource measurement data at multiple fixed points; and calculate the median or average of the multiple fixed wind speed measurement values ​​as the fixed measurement reference value for the wind speed in the reference area.

[0216] In the optional implementation, the dynamic measurement reference value calculation module 604 is specifically used to: extract the dynamic measurement value dataset of wind speed from each set of dynamic wind resource measurement data; calculate the average wind speed for each dynamic measurement value dataset, and use it as the dynamic measurement reference value of wind speed corresponding to that set of dynamic wind resource measurement data.

[0217] In the optional implementation methods, both fixed wind resource measurement data and dynamic wind resource measurement data include the following types of wind resource indicators:

[0218] Latitude and longitude coordinates, wind speed, air density, and elevation;

[0219] The module for determining the location of wind turbines to be built is specifically used for:

[0220] Based on dynamic wind resource measurement data of the reference area and dynamic wind resource measurement data of the non-reference area, multiple wind turbine site construction plans are generated. The wind turbine site construction plan includes: the latitude and longitude coordinates, elevation and annual power generation of multiple wind turbines to be constructed; among them, the annual power generation is calculated based on wind speed and air density.

[0221] Based on annual power generation, wind power cost and grid electricity cost, the feasibility of multiple wind turbine site construction plans is analyzed; multiple wind turbine sites to be built are determined based on the wind turbine site construction plan with the highest feasibility.

[0222] It should be noted that the various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, for the device embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the description of the method embodiments. The device embodiments described above are merely illustrative, and the units described as separate components may or may not be physically separate. The components indicated as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment solution according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0223] The above description is merely one specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for selecting wind turbine locations in a wind farm, characterized in that, The method includes: By setting up multiple wind measurement towers in the reference area within the wind farm construction area, fixed measurement data of wind resources at multiple fixed points are obtained. Based on fixed wind resource measurement data from multiple fixed locations, a fixed measurement reference value for a target wind resource indicator within the reference area is determined; the target wind resource indicator is one of several types of wind resource indicators in the fixed wind resource measurement data. By controlling a mobile patrol device to conduct multiple patrols within the reference area using various patrol paths, the mobile patrol device collects data during the patrol, obtaining multiple sets of dynamic wind resource measurement data for the reference area; the mobile patrol device is equipped with one or more sensors for collecting wind resource index data; each set of dynamic wind resource measurement data corresponds to a patrol path used in a single patrol within the reference area. For each set of dynamic wind resource measurement data in the multiple sets of dynamic wind resource measurement data, a dynamic measurement reference value for the target wind resource index is calculated. Based on the matching between the calculated dynamic measurement reference values ​​of the target wind resource index and the fixed measurement reference values ​​of the target wind resource index, a target cruise path is determined from the multiple cruise paths. Based on the target cruise path, a cruise path for a non-reference area is constructed within the wind farm construction area, and the mobile cruise device is controlled to cruise within the non-reference area based on the constructed cruise path, so that the mobile cruise device can collect data during the cruise and obtain dynamic measurement data of wind resources in the non-reference area. Based on the dynamic measurement data of wind resources in the reference area and the dynamic measurement data of wind resources in the non-reference area, multiple wind turbine locations to be built are determined in the area where the wind farm is to be built by analyzing wind power output, wind power cost and grid electricity cost.

2. The method according to claim 1, characterized in that, The method further includes: Determine the expected wind power generation scale and geographical environmental characteristics of the area where the wind farm is to be built; Based on the expected wind power generation scale and the geographical environment characteristics, a reference area and a non-reference area are delineated within the area to be built in the wind farm, and a layout scheme for the fixed points of the wind measurement towers in the reference area is generated.

3. The method according to claim 2, characterized in that, The step of delineating reference and non-reference areas within the proposed wind farm construction area based on the expected wind power generation scale and the geographical environmental characteristics, and generating a fixed location layout scheme for the wind measurement towers in the reference area, includes: If the expected wind power generation scale is the first level scale, then the number of fixed points of the wind measurement tower is set based on the expected wind power generation scale. Based on the number and the geographical environmental characteristics of the wind farm to be built area, the location information of the fixed points of the wind measurement tower is set. Based on the location information, the land area where the fixed points of the wind measurement tower are located in the wind farm to be built area is used as the reference area, and the remaining areas are used as non-reference areas. If the expected wind power generation scale is the second-level scale, then the area to be built for the wind farm is divided into multiple zones based on the expected wind power generation scale; the expected wind power generation scale corresponding to each zone is determined based on the expected wind power generation scale and the number of zones; based on the geographical environmental characteristics of the area to be built for the wind farm, one or more zones are selected as reference areas, and the connected areas of the remaining zones are designated as non-reference areas; the number of fixed points for wind measurement towers is set based on the expected wind power generation scale corresponding to the reference areas; a wind measurement tower fixed point layout scheme is generated according to the geographical environmental characteristics of the reference areas; the second-level scale is larger than the first-level scale.

4. The method according to claim 3, characterized in that, The step of setting the location information of the fixed points of the wind measurement tower based on the quantity and the geographical environmental characteristics of the wind farm construction area includes: If the geographical environment characteristics of the wind farm construction area indicate that the wind farm construction area includes special areas, then the fixed points of the wind measurement towers shall be set in the special areas first. The step of selecting one or more zones as reference areas based on the geographical environmental characteristics of the wind farm construction area includes: if the geographical environmental characteristics of the wind farm construction area indicate that the wind farm construction area contains special areas, then the zones that overlap with the special areas are preferentially selected as reference areas.

5. The method according to claim 4, characterized in that, The special area is at least one of the following types of areas: A wind gap is a region where the elevation changes abruptly, and where the air density changes abruptly.

6. The method according to claim 2, characterized in that, Determining the expected wind power generation capacity of the area where the wind farm is to be built includes: Obtain the expected installed wind power capacity within the area to be built of the wind farm; Based on the mapping relationship between the range of wind power capacity and the scale of wind power generation, the expected scale of wind power generation in the area where the wind farm is to be built is determined.

7. The method according to claim 1, characterized in that, The determination of a target cruise path from multiple cruise paths based on the matching between the calculated dynamic measurement reference values ​​of the target wind resource index and the fixed measurement reference values ​​of the target wind resource index includes: Calculate the absolute value of the difference between multiple dynamic measurement reference values ​​of the target wind resource index and the fixed measurement reference value respectively; Based on the correspondence between dynamic wind resource measurement data and cruise paths, the cruise path corresponding to the dynamic measurement reference value with the smallest absolute value of the difference from the fixed measurement reference value is determined as the target cruise path.

8. The method according to claim 1, characterized in that, Each cruise route includes multiple locations with the same longitude and latitude but different elevations, so that the mobile cruise device can collect data at multiple different elevations for locations with the same longitude and latitude during the cruise. The fixed wind resource measurement data for each fixed location includes wind resource measurement data at different elevations at the longitude and latitude indicated by that fixed location.

9. The method according to claim 8, characterized in that, The target wind resource indicator is wind speed; The determination of fixed measurement reference values ​​for target wind resource indicators within the reference area based on fixed wind resource measurement data from multiple fixed locations includes: Wind speed measurements at multiple fixed points are extracted from the fixed wind resource measurement data at these multiple fixed points. The median or average of the wind speed measurements at multiple fixed points is taken as the fixed reference value for wind speed in the reference area.

10. The method according to claim 9, characterized in that, For each set of dynamic wind resource measurement data in the plurality of sets of dynamic wind resource measurement data, a dynamic measurement reference value for the target wind resource index is calculated, including: From each set of dynamic wind resource measurement data, extract the dynamic measurement data dataset of wind speed; For each dynamic measurement dataset, the average wind speed is calculated and used as the dynamic measurement reference value for the wind speed corresponding to that set of dynamic wind resource measurement data.

11. The method according to claim 1, characterized in that, Both the fixed wind resource measurement data and the dynamic wind resource measurement data include the following types of wind resource indicators: Latitude and longitude coordinates, wind speed, air density, and elevation; The dynamic wind resource measurement data based on the reference area and the non-reference area, through analysis of wind power output, wind power cost, and grid electricity cost, determines multiple potential wind turbine locations within the wind farm development area, specifically including: Based on the dynamic wind resource measurement data of the reference area and the dynamic wind resource measurement data of the non-reference area, multiple wind turbine site construction plans are generated; the wind turbine site construction plan includes: the latitude and longitude coordinates, elevation and annual power generation of multiple wind turbines to be constructed; wherein, the annual power generation is calculated based on wind speed and air density; Based on annual power generation, wind power cost and grid electricity cost, the feasibility of the multiple wind turbine site construction plans is analyzed; multiple wind turbine sites to be built are determined according to the wind turbine site construction plan with the highest feasibility.

12. A wind turbine location selection device for a wind farm, characterized in that, The device includes: The fixed data acquisition module is used to obtain fixed measurement data of wind resources at multiple fixed points by setting up multiple meteorological towers in the reference area of ​​the wind farm to be built. The fixed measurement reference value determination module is used to determine the fixed measurement reference value of the target wind resource index within the reference area based on fixed wind resource measurement data from multiple fixed points; the target wind resource index is one of several types of wind resource indices in the fixed wind resource measurement data. The cruise control module is used to control a mobile cruise device to cruise multiple times within the reference area along various cruise paths, so that the mobile cruise device can collect data during the cruise and obtain multiple sets of dynamic wind resource measurement data of the reference area; the mobile cruise device is equipped with one or more sensors for collecting wind resource index data; a set of dynamic wind resource measurement data corresponds to the cruise path used in one cruise within the reference area. The dynamic measurement reference value calculation module is used to calculate the dynamic measurement reference value of the target wind resource index for each set of dynamic measurement data of wind resources in the multiple sets of dynamic measurement data. The path determination module is used to determine a target cruise path from the multiple cruise paths based on the matching between multiple dynamic measurement reference values ​​of the target wind resource index and the fixed measurement reference value of the target wind resource index. The cruise control module is also used to construct a cruise path for a non-reference area within the wind farm construction area based on the target cruise path, and control the mobile cruise device to cruise within the non-reference area based on the constructed cruise path, so that the mobile cruise device can collect data during the cruise and obtain dynamic measurement data of wind resources in the non-reference area. The module for determining the location of wind turbines to be built is used to determine multiple locations of wind turbines to be built within the area to be built of the wind farm by analyzing the dynamic measurement data of wind resources in the reference area and the dynamic measurement data of wind resources in the non-reference area, as well as the wind power output, wind power cost and electricity charges and the grid electricity charges.

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