Method and device for determining design parameters of wind turbines based on complex terrain conditions

Abstract

The present invention provides a method and device for determining design parameters of a wind turbine based on complex terrain conditions. The method includes: determining at least two candidate turbine locations according to the incoming flow direction of a wind farm and a preliminary turbine layout plan, where the preliminary turbine layout plan is used to characterize the layout positions of the turbine locations of the wind turbines in the wind farm area; for any candidate turbine location, determining the time series data of the wind condition parameters of different sectors corresponding to the candidate turbine location according to the meteorological parameters of the candidate turbine location and a preset number of sectors included in the candidate turbine location, and determining the terrain complexity level corresponding to the candidate turbine location, where the terrain complexity level is used to characterize the complexity of the terrain corresponding to the sector where the main wind direction of the candidate turbine location is located; designing the wind turbine design parameters of each candidate turbine location according to the time series data of the wind condition parameters of different sectors corresponding to each candidate turbine location and the terrain complexity level corresponding to each candidate turbine location. The present invention improves the accuracy of determining the wind turbine design parameters.

Description

Technical Field

[0001] The present invention relates to the technical field of wind power generation, and particularly to a method and device for determining design parameters of a wind turbine based on complex terrain conditions. Background Art

[0002] Currently, the mainstream wind resource assessment methods mainly rely on erecting wind measurement towers and other wind measurement equipment in the wind farm site area, obtaining the wind resource parameter data of each machine location point through wind measurement data analysis and Computational Fluid Dynamics (CFD) flow field simulation calculation, and finally taking the envelope value of the calculation results of the wind resource parameter data for the design calculation of the wind turbine generator set.

[0003] However, the number of wind measurement towers in the wind farm under complex terrain is small, resulting in inaccurate results of the flow field simulation software. The lack of resource data for complex terrain leads to poor accuracy in determining the design parameters of the wind turbine generator set, resulting in the inability of the designed wind turbine generator set parameters to be applicable to the power generation field with complex terrain. Summary of the Invention

[0004] The present invention provides a method and device for determining design parameters of a wind turbine based on complex terrain conditions, aiming to solve the defect that the lack of resource data for complex terrain in the prior art leads to poor accuracy in determining the design parameters of the wind turbine generator set, and improving the accuracy of determining the design parameters of the wind turbine generator set.

[0005] In a first aspect, the present invention provides a method for determining design parameters of a wind turbine based on complex terrain conditions, the method comprising the following steps:

[0006] Determine at least two candidate machine location points according to the incoming flow direction of the wind farm and the preliminary unit layout plan; the preliminary unit layout plan is used to characterize the layout position of the machine location points of the wind turbine generator set in the wind farm plant area;

[0007] For any one of the candidate machine location points, determine the time series data of the wind condition parameters of different sectors corresponding to the candidate machine location point according to the meteorological parameters of the candidate machine location point and a preset number of sectors included in the candidate machine location point;

[0008] Determine the terrain complexity level corresponding to the candidate machine location point; the terrain complexity level is used to characterize the complexity of the terrain corresponding to the sector where the main wind direction of the candidate machine location point is located, and the terrain complexity level includes any one of the following from low to high: generally complex, relatively complex, moderately complex, complex, extremely complex;

[0009] Design the wind turbine design parameters of each candidate machine location point according to the time series data of the wind condition parameters of different sectors corresponding to each candidate machine location point and the terrain complexity level corresponding to each candidate machine location point.

[0010] A method for determining design parameters of a wind turbine based on complex terrain conditions provided by the present invention, determining the time series data of wind condition parameters of different sectors corresponding to the candidate machine site according to the meteorological parameters of the candidate machine site and a preset number of sectors included in the candidate machine site, includes:

[0011] Determining the time series data of the wind condition parameters of the candidate machine site according to the meteorological parameters of the candidate machine site;

[0012] Classifying the time series data of the wind condition parameters of each candidate machine site according to the preset number of sectors to obtain the time series data of the wind condition parameters of different sectors corresponding to the candidate machine site.

[0013] A method for determining design parameters of a wind turbine based on complex terrain conditions provided by the present invention, the preset number of sectors is obtained by dividing a horizontal plane circle centered on the candidate machine site; the time series data of the wind condition parameters includes turbulence intensity, wind direction deflection rate and wind shear;

[0014] The classifying the time series data of the wind condition parameters of each candidate machine site according to the preset number of sectors to obtain the time series data of the wind condition parameters of different sectors corresponding to the candidate machine site, includes:

[0015] For any one of the candidate machine sites, determining a first metric set corresponding to each of the sectors in the candidate machine site based on the turbulence intensity corresponding to each of the sectors in the candidate machine site; the first metric set includes at least one of the following: the occurrence probability of the turbulence intensity in the time period, the average turbulence intensity and the standard deviation of the average turbulence intensity;

[0016] Counting the first metric sets in the same time period where the occurrence probability of the turbulence intensity in the time period, the average turbulence intensity and the standard deviation of the average turbulence intensity all meet their respective first preset thresholds;

[0017] Determining a second metric set corresponding to each of the sectors in different time periods based on the wind direction deflection rate corresponding to each of the sectors; the second metric set includes at least one of the following: the occurrence probability of the wind direction deflection rate in the time period, the average wind direction deflection rate and the standard deviation of the average wind direction deflection rate;

[0018] Counting the second metric sets in the same time period where the occurrence probability of the wind direction deflection rate in the time period, the average wind direction deflection rate and the standard deviation of the average wind direction deflection rate all meet their respective second preset thresholds;

[0019] Determine a third metric set corresponding to each of the sectors within different time periods based on the vertical wind shear of each of the sectors; the third metric set includes at least one of the following: the occurrence probability of the vertical wind shear in the time period, the average vertical wind shear, and the standard deviation of the average vertical wind shear;

[0020] Statistically count the third metric set in which the occurrence probability of the vertical wind shear in the time period, the average vertical wind shear, and the standard deviation of the average vertical wind shear all meet their respective third preset thresholds within the same time period;

[0021] Based on the first metric set that all meet their respective first preset thresholds, the second metric set that all meet their respective second preset thresholds, and the third metric set that all meet their respective third preset thresholds, determine the time-series data of the wind condition parameters for different sectors corresponding to the candidate turbine site.

[0022] According to a method for determining design parameters of a wind turbine based on complex terrain conditions provided by the present invention, the method further includes:

[0023] Based on the standard deviation of the wind speed corresponding to each of the sectors and the average wind speed corresponding to each of the sectors, determine the turbulence intensity corresponding to each of the sectors within different time periods;

[0024] Based on the wind direction data at a first height corresponding to each of the sectors and the wind direction data at a second height corresponding to each of the sectors, determine the wind direction deflection rate corresponding to each of the sectors within different time periods; the first height is the hub height of the wind turbine at the candidate turbine site, and the first height is higher than the second height;

[0025] Based on the wind speed at a third height corresponding to each of the sectors and the wind speed at a fourth height corresponding to each of the sectors, determine the vertical wind shear corresponding to each of the sectors within different time periods.

[0026] According to a method for determining design parameters of a wind turbine based on complex terrain conditions provided by the present invention, the determining the terrain complexity level corresponding to the candidate turbine site includes:

[0027] Based on a preset number of sectors included in the candidate turbine site, determine the sector where the main wind direction of the candidate turbine site is located;

[0028] Based on the horizontal distances between at least one reference point and the candidate turbine site and the altitude corresponding to the horizontal distances, determine the functional relationship between the radius of the horizontal plane circle with the candidate turbine site as the center and the altitude corresponding to the radius; each of the reference points is a point within the sector where the main wind direction is located;

[0029] Determine the terrain slope angle of the sector where the main wind direction is located based on the coefficients of the function relation;

[0030] Determine the terrain complexity level corresponding to the candidate turbine location based on the mapping relation between the preset terrain slope angle and the complexity of the terrain in the sector.

[0031] According to a method for determining the design parameters of a wind turbine based on complex terrain conditions provided by the present invention, the method further includes:

[0032] Determine the sector where the main wind direction of the candidate turbine location is located, the first sector and the second sector adjacent to the sector where the main wind direction of the candidate turbine location is located respectively;

[0033] Respectively determine the terrain complexity level corresponding to the terrain in the sector where the main wind direction of the candidate turbine location is located, the terrain complexity level corresponding to the first sector and the terrain complexity level corresponding to the second sector;

[0034] The design of the wind turbine design parameters for each candidate turbine location according to the time series data of the wind condition parameters of different sectors corresponding to each candidate turbine location and the terrain complexity level corresponding to each candidate turbine location includes:

[0035] Design the wind turbine design parameters for each candidate turbine location according to the terrain complexity level corresponding to the sector where the main wind direction of each candidate turbine location is located, the terrain complexity level corresponding to the first sector corresponding to each candidate turbine location, and the terrain complexity level corresponding to the second sector.

[0036] According to a method for determining the design parameters of a wind turbine based on complex terrain conditions provided by the present invention, the design of the wind turbine design parameters for each candidate turbine location according to the time series data of the wind condition parameters of different sectors corresponding to each candidate turbine location and the terrain complexity level corresponding to each candidate turbine location includes:

[0037] Refine and classify the time series data of the wind condition parameters of different sectors corresponding to each candidate turbine location according to the terrain complexity level corresponding to each candidate turbine location, the terrain complexity level corresponding to the first sector corresponding to each candidate turbine location, and the terrain complexity level corresponding to the second sector, to obtain the refined classification result of the wind condition parameters corresponding to each candidate turbine location;

[0038] Among them, the refined classification results of the wind condition parameters corresponding to each of the candidate machine positions at least include the sector where the main wind direction corresponding to each of the candidate machine positions is located, and the parameter measurement criteria of the first sector and the second sector in different time periods. The parameter measurement criteria are used to characterize: the target time period when the occurrence probability of the meteorological parameter meets the preset condition and the threshold of the meteorological parameter corresponding to the target time period;

[0039] Based on the refined classification results of the wind condition parameters corresponding to each of the candidate machine positions, the design parameters of the wind turbines at each of the candidate machine positions are adaptively designed to form a key wind resource parameter threshold table.

[0040] According to a method for determining the design parameters of a wind turbine based on complex terrain conditions provided by the present invention, the method further includes:

[0041] Using the sample meteorological parameters of each of the candidate machine positions, the terrain complexity level of each of the candidate machine positions, and the label data of each of the candidate machine positions, the initial deep learning network is trained to obtain a refined wind turbine design parameter determination model;

[0042] Using the refined wind turbine design parameter determination model, the design parameter values of the wind turbines at the target machine position are determined.

[0043] In a second aspect, the present invention further provides a device for determining the design parameters of a wind turbine based on complex terrain conditions, including the following modules:

[0044] A unit division module, configured to determine at least two candidate machine positions according to the incoming flow direction of the wind farm and the preliminary unit layout plan; the preliminary unit layout plan is used to characterize the layout positions of the machine positions of the wind turbines in the wind farm plant area;

[0045] A design parameter determination model, for any one of the candidate machine positions, according to the meteorological parameters of the candidate machine position and a preset number of sectors included in the candidate machine position, determines the time series data of the wind condition parameters of different sectors corresponding to the candidate machine position;

[0046] Determine the terrain complexity level corresponding to the candidate machine position; the terrain complexity level is used to characterize the complexity of the terrain corresponding to the sector where the main wind direction of the candidate machine position is located, and the terrain complexity level includes any one of the following from low to high: generally complex, relatively complex, moderately complex, complex, extremely complex;

[0047] According to the time series data of the wind condition parameters of different sectors corresponding to each of the candidate machine positions and the terrain complexity level corresponding to each of the candidate machine positions, the design parameters of the wind turbines at each of the candidate machine positions are designed.

[0048] In a third aspect, the present invention further provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the method for determining the design parameters of a wind turbine based on complex terrain conditions as described in any one of the above is implemented.

[0049] In a fourth aspect, the present invention further provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the method for determining the design parameters of a wind turbine based on complex terrain conditions as described in any one of the above is implemented.

[0050] In a fifth aspect, the present invention further provides a computer program product, including a computer program. When the computer program is executed by a processor, the method for determining the design parameters of a wind turbine based on complex terrain conditions as described in any one of the above is implemented.

[0051] For the method and device for determining the design parameters of a wind turbine based on complex terrain conditions provided by the present invention, first, according to the incoming flow direction of the wind farm and the preliminary turbine layout plan, at least two candidate turbine locations are determined, where the preliminary turbine layout plan is used to characterize the layout positions of the turbine locations of the wind turbines in the wind farm area; then, for any candidate turbine location, according to the meteorological parameters of the candidate turbine location and a preset number of sectors included in the candidate turbine location, the time series data of the wind condition parameters of different sectors corresponding to the candidate turbine location are determined, and the terrain complexity level corresponding to the candidate turbine location is determined, where the terrain complexity level is used to characterize the complexity of the terrain corresponding to the sector where the main wind direction of the candidate turbine location is located, and the terrain complexity level includes any one of the following from low to high: generally complex, relatively complex, moderately complex, complex, extremely complex; furthermore, the design parameters of the wind turbines at each candidate turbine location can be designed according to the time series data of the wind condition parameters of different sectors corresponding to each candidate turbine location and the terrain complexity level corresponding to each candidate turbine location.

[0052] In the present invention, the measured data (meteorological parameters) and the terrain data (terrain complexity under complex terrain conditions) are creatively combined, considering the comprehensive influence of complex terrain on the components of the wind condition parameters. Furthermore, according to the time series data of the wind condition parameters of different sectors corresponding to each candidate turbine location and the terrain complexity level corresponding to each candidate turbine location, the design parameters of the wind turbines at each candidate turbine location are designed, improving the accuracy of determining the design parameters of the wind turbines. Description of the Drawings

[0053] To more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the accompanying drawings required for the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can also be obtained based on these drawings.

[0054] Figure 1 It is one of the flow schematic diagrams of the method for determining the design parameters of a wind turbine based on complex terrain conditions provided by the present invention.

[0055] Figure 2 It is a schematic diagram of dividing sectors of a horizontal plane circle with a target machine location point as the center provided by the present invention.

[0056] Figure 3 It is a schematic diagram of dividing sectors of a horizontal plane circle with a target machine location point as the center provided by the present invention.

[0057] Figure 4 It is a schematic diagram of the corresponding relationship between the radius where the reference point is located and the altitude provided by an embodiment of the present invention.

[0058] Figure 5 It is the second flow schematic diagram of the method for determining the design parameters of a wind turbine based on complex terrain conditions provided by the present invention.

[0059] Figure 6 It is a schematic diagram of the structure of a device for determining the design parameters of a wind turbine based on complex terrain conditions provided by the present invention.

[0060] Figure 7 It is a schematic diagram of the structure of an electronic device provided by the present invention. Detailed implementation manners

[0061] To make the objectives, technical solutions, and advantages of the present invention clearer, the following will clearly and completely describe the technical solutions in the present invention in conjunction with the accompanying drawings in the present invention. Obviously, the described embodiments are some embodiments of the present invention, rather than all embodiments. Based on the embodiments in the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0062] Wind turbines are often in complex and variable natural environments. Especially under complex terrain conditions, the simplification of wind resource assessment and the variability of the atmospheric environment significantly affect their safety and economic benefits during operation. In wind energy resource analysis, atmospheric stability affects the vertical distribution and turbulence of the wind, and thus fluctuates the output power of wind turbines. In an unstable atmosphere, the vertical wind shear intensifies, increasing the dynamic load of the unit and raising the risk of fatigue damage. High shear wind speeds, especially in terrains such as valleys and hills, test the response and control capabilities of the unit and may also trigger protective shutdowns, reducing power generation efficiency. The complexity of the terrain further complicates wind speed prediction, making it necessary to conduct a refined study of the wind resource situation of the wind farm for wind farm layout and unit selection.

[0063] Currently, the design input parameters of wind turbines are derived from the results of wind resource calculations. Moreover, the mainstream wind resource assessment methods mainly rely on wind measurement equipment such as erecting wind measurement towers in the wind farm site area. Through wind measurement data analysis and CFD flow field simulation calculations, wind resource parameter data for each machine location are obtained. Finally, the envelope value of the calculation results of the wind resource parameter data is taken for the design calculation of wind turbines. The results obtained by this wind resource assessment method have the following deficiencies: 1) Often, the number of wind measurement towers in wind farms under complex terrain is small, making the results of the flow field simulation software inaccurate. As a result, there are significant differences in the resource conditions themselves under complex terrain. The lack of resource data for complex terrain leads to the inapplicability of the designed wind turbine parameters to power generation fields with complex terrain; 2) When designing the unit, taking the envelope value of the calculation results of wind resource parameter data for the design calculation of wind turbines often makes the calculation results too conservative, increasing the unit cost; 3) When the unit operates under complex terrain, in the face of high turbulence and high shear, a sector management strategy is often adopted, that is, the unit is shut down and other non-power generation situations occur within the sector, resulting in additional losses in the unit's power generation and affecting economic benefits.

[0064] Based on the above problems, the present invention proposes a method for determining the design parameters of wind turbines based on complex terrain conditions. First, an environmental assessment model is used to screen at least one candidate machine location, quickly filtering out machine locations with a higher environmental assessment level, reducing the amount of data calculation. Then, the remaining machine locations with a smaller environmental level are refined and divided, increasing the diversity, comprehensiveness, and accuracy of terrain resource data, improving the later power generation efficiency, being conducive to improving the accuracy and applicability of the design parameters of wind turbines in complex terrain wind farms, and also being conducive to guiding wind farm development, site selection optimization, and safe operation.

[0065] The following combines Figures 1-5Describes the method for determining the design parameters of a wind turbine provided by the present invention based on complex terrain conditions. The method for determining the design parameters of a wind turbine provided by the present invention is applicable to the site selection of any wind farm and the design of input parameters of wind turbines. The execution entity of this method can be an electronic device or a device for determining the design parameters of a wind turbine based on complex terrain conditions set in the electronic device. The device for determining the design parameters of a wind turbine based on complex terrain conditions can be implemented by software, hardware, or a combination of both.

[0066] Figure 1 Is one of the flow schematic diagrams of the method for determining the design parameters of a wind turbine provided by the present invention based on complex terrain conditions. As Figure 1 shown, the method includes the following:

[0067] Step 101: Determine at least two candidate machine locations according to the incoming flow direction of the wind farm and the preliminary machine layout plan; the preliminary machine layout plan is used to characterize the layout positions of the machine locations of the wind turbines in the wind farm area.

[0068] Specifically, it should be noted that the execution entity of this embodiment is an electronic device, which is used to implement the determination of the design parameters of a wind turbine based on complex terrain conditions.

[0069] It should be noted that the candidate machine locations can be understood as representative machine locations. In the early stage of wind farm development, technicians will design a preliminary machine layout plan. According to the wind direction of the wind farm and the preliminary machine layout plan, the entire factory area is divided into different regions, and a representative machine location is determined in each region. For example, the entire factory area is divided into 3 to 5 regions, and a representative machine location is selected in each region.

[0070] Exemplarily, the method for determining the representative machine location can be to determine the altitude of each machine location according to the elevation map information and the position coordinates of the machine location. Taking each machine location as the center and the radius as the preset distance, determine and count the altitudes at the points due east, due west, due south, and due north of each machine location; subtract the altitudes at the 4 points due east, due west, due south, and due north from the altitude at the machine location respectively, and use the elevation difference as the screening variable. The machine locations with an elevation difference of less than or equal to 10m within each region and located in the incoming flow direction are used as representative machine locations (i.e., candidate machine locations).

[0071] Step 102: For any candidate machine location, determine the time series data of the wind condition parameters for different sectors corresponding to the candidate machine location according to the meteorological parameters of the candidate machine location and the preset number of sectors included in the candidate machine location.

[0072] After selecting the candidate turbine locations, for each candidate turbine location, the basic wind resource parameters of the candidate turbine location can be calculated, that is, the time series data of the wind condition parameters of the candidate turbine location.

[0073] Exemplarily, Step1: Process the meteorological data collected at the site using conventional resource analysis methods and input it into commercial flow field simulation software to calculate the time series data of the wind condition parameters of the representative turbine locations. The wind condition parameters need to include: turbulence intensity, wind direction at two altitude levels, and wind shear.

[0074] Step2: Process and analyze the time series data of the wind condition parameters at the representative turbine locations. In particular, classify them by sector. For example, according to the meteorological parameters of the candidate turbine location and the preset number of sectors included in the candidate turbine location, determine the time series data of the wind condition parameters of different sectors corresponding to the candidate turbine location. The sector division method is as follows:

[0075] Taking the representative turbine location as the center and due north as 0°, divide the azimuth of the turbine location into 12 sectors, each sector with an angle of 30 degrees, respectively at 50m, 100m, 150m, 200m, 250m... 2000m.

[0076] Step 103: Determine the terrain complexity level corresponding to the candidate turbine location; the terrain complexity level is used to characterize the complexity of the terrain corresponding to the sector where the main wind direction of the candidate turbine location is located. The terrain complexity level includes any of the following from low to high: generally complex, relatively complex, moderately complex, complex, extremely complex.

[0077] Specifically, in the present invention, the time series data of the wind condition parameters of each candidate turbine location can be further divided in combination with the terrain conditions of each candidate turbine location.

[0078] Among them, first, it is necessary to determine the terrain conditions of each candidate turbine location. Among them, the terrain conditions can be terrain complexity, and the terrain complexity can include: terrain slope angle and the corresponding level of the terrain slope angle. In particular, it can be the complexity of the terrain corresponding to the sector where the main wind direction of the candidate turbine location is located.

[0079] Step 104: Design the wind turbine design parameters of each candidate turbine location according to the time series data of the wind condition parameters of different sectors corresponding to each candidate turbine location and the terrain complexity level corresponding to each candidate turbine location.

[0080] After determining the terrain complexity level corresponding to each candidate turbine location, the time series data of the wind condition parameters of different sectors corresponding to each candidate turbine location can be further refined and divided in combination with the terrain complexity level corresponding to the candidate turbine location to obtain a refined classification result. Thus, during the design stage of the unit and the safety check and adaptability analysis of the site, refined design can be carried out according to the refined classification result.

[0081] Specifically, based on the refined classification results of the wind condition parameters corresponding to the candidate turbine locations and combined with the terrain slope, a refined resource assessment is carried out. The main considerations for the classification levels are as follows:

[0082] Step1: Based on the classification results of the terrain complexity levels, the results of the main wind direction sectors and the adjacent ±30° sectors of the candidate turbine locations are comprehensively summarized as shown in Table 1 below:

[0083] Table 1:

[0084]

[0085] Step2: Based on the comprehensive summary results of the representative turbine locations in step1, during the design stage of the wind turbine and the safety check and adaptability analysis of the site, focus on calculating the envelope data of the main wind direction and adjacent sectors, and form a key wind resource parameter threshold table. And adopt targeted strategies in specific sectors. The key wind resource parameter threshold table is shown in Table 2 below:

[0086] Table 2:

[0087]

[0088] The method provided in this embodiment first determines at least two candidate turbine locations according to the incoming flow direction of the wind farm and the preliminary turbine layout plan, where the preliminary turbine layout plan is used to represent the layout positions of the turbine locations of the wind turbines in the wind farm area; then, for any candidate turbine location, according to the meteorological parameters of the candidate turbine location and the preset number of sectors included in the candidate turbine location, determine the time series data of the wind condition parameters of different sectors corresponding to the candidate turbine location, and determine the terrain complexity level corresponding to the candidate turbine location, where the terrain complexity level is used to represent the complexity of the terrain corresponding to the sector where the main wind direction of the candidate turbine location is located, and the terrain complexity levels from low to high include any one of the following: generally complex, relatively complex, moderately complex, complex, extremely complex; furthermore, the design parameters of the wind turbines at each candidate turbine location can be designed according to the time series data of the wind condition parameters of different sectors corresponding to each candidate turbine location and the terrain complexity level corresponding to each candidate turbine location.

[0089] In the present invention, the measured data (meteorological parameters) and terrain data (terrain complexity under complex terrain conditions) are creatively combined, considering the comprehensive influence of complex terrain on the components of wind condition parameters. Furthermore, the design parameters of the wind turbines at each candidate turbine location are designed according to the time series data of the wind condition parameters of different sectors corresponding to each candidate turbine location and the terrain complexity level corresponding to each candidate turbine location, improving the accuracy of determining the design parameters of the wind turbines.

[0090] A method for determining design parameters of a wind turbine based on complex terrain conditions provided by the present invention determines the time series data of wind condition parameters for different sectors corresponding to a candidate machine site according to the meteorological parameters of the candidate machine site and a preset number of sectors included in the candidate machine site, including:

[0091] Determine the time series data of wind condition parameters for the candidate machine site according to the meteorological parameters of the candidate machine site;

[0092] Classify the time series data of wind condition parameters for each candidate machine site into sectors according to a preset number of sectors to obtain the time series data of wind condition parameters for different sectors corresponding to the candidate machine site.

[0093] Specifically, in some embodiments, step 102 can be implemented through the following steps, including:

[0094] First, determine the time series data of wind condition parameters for the candidate machine site according to the meteorological parameters of the candidate machine site. Among them, the meteorological parameters are obtained by actually monitoring the meteorological conditions at the site of the plant using conventional resource analysis methods. The meteorological parameters can be wind condition parameters, and the wind condition parameters include: turbulence intensity, wind direction at two altitude levels, and wind shear. It should be noted that the meteorological parameters may change according to time, etc. Therefore, the meteorological parameters of the candidate machine site can be input into a commercial flow field simulation software according to the corresponding time points to obtain the time series data of wind condition parameters for the candidate machine site.

[0095] Furthermore, after obtaining the time series data of wind condition parameters for the candidate machine site, the time series data of wind condition parameters for each candidate machine site can be further classified into sectors according to a preset number of sectors included in the candidate machine site to obtain the time series data of wind condition parameters for different sectors corresponding to the candidate machine site.

[0096] The method provided in this embodiment determines the time series data of wind condition parameters for the candidate machine site according to the meteorological parameters of the candidate machine site, and then classifies the time series data of wind condition parameters for each candidate machine site into sectors according to a preset number of sectors to obtain the time series data of wind condition parameters for different sectors corresponding to the candidate machine site, and the obtained time series data of wind condition parameters has a relatively high degree of refinement.

[0097] A method for determining design parameters of a wind turbine based on complex terrain conditions provided by the present invention, the preset number of sectors is obtained by dividing the horizontal plane circle with the candidate machine site as the center; the time series data of wind condition parameters includes turbulence intensity, wind direction deflection rate, and wind shear;

[0098] Classify the time series data of wind condition parameters for each candidate machine site into sectors according to a preset number of sectors to obtain the time series data of wind condition parameters for different sectors corresponding to the candidate machine site, including:

[0099] For any candidate wind turbine site, based on the turbulence intensity corresponding to each sector in the candidate wind turbine site, determine the first metric set corresponding to each sector in different time periods; the first metric set includes at least one of the following: the occurrence probability of the time period turbulence intensity, the average turbulence intensity, and the standard deviation of the average turbulence intensity;

[0100] Count the first metric set in which the occurrence probability of the time period turbulence intensity, the average turbulence intensity, and the standard deviation of the average turbulence intensity all meet their respective first preset thresholds in the same time period;

[0101] Based on the wind direction deflection rate corresponding to each sector, determine the second metric set corresponding to each sector in different time periods; the second metric set includes at least one of the following: the occurrence probability of the time period wind direction deflection rate, the average wind direction deflection rate, and the standard deviation of the average wind direction deflection rate;

[0102] Count the second metric set in which the occurrence probability of the time period wind direction deflection rate, the average wind direction deflection rate, and the standard deviation of the average wind direction deflection rate all meet their respective second preset thresholds in the same time period;

[0103] Based on the vertical wind shear of each sector, determine the third metric set corresponding to each sector in different time periods; the third metric set includes at least one of the following: the occurrence probability of the time period vertical wind shear, the average vertical wind shear, and the standard deviation of the average vertical wind shear;

[0104] Count the third metric set in which the occurrence probability of the time period vertical wind shear, the average vertical wind shear, and the standard deviation of the average vertical wind shear all meet their respective third preset thresholds in the same time period;

[0105] Based on the first metric set that all meet their respective first preset thresholds, the second metric set that all meet their respective second preset thresholds, and the third metric set that all meet their respective third preset thresholds, determine the time series data of the wind condition parameters of different sectors corresponding to the candidate wind turbine site.

[0106] Specifically, in some embodiments, a preset number of sectors in the candidate wind turbine site are obtained by dividing a horizontal plane circle centered on the candidate wind turbine site. Here, the number of sectors can be any suitable number, such as 12 sectors or 8 sectors.

[0107] The time-series data of wind condition parameters in this embodiment include turbulence intensity, wind direction deflection rate, and wind shear. Here, the turbulence intensity describes the degree of variation of wind speed over time and space. It reflects the relative intensity of the pulsating wind speed and is the most important characteristic quantity for describing the characteristics of atmospheric turbulent motion. Here, the wind direction deflection rate refers to the degree or rate of deflection of the wind direction during the flow process due to factors such as the Coriolis force. Here, the vertical wind shear characterizes the change of the wind speed vector in the vertical direction.

[0108] Correspondingly, in this embodiment, according to a preset number of sectors, the process of sector classification of the time-series data of wind condition parameters for each candidate turbine location to obtain the time-series data of wind condition parameters for different sectors corresponding to the candidate turbine location includes the following steps:

[0109] Step 1: For any candidate turbine location, based on the turbulence intensity corresponding to each sector in the candidate turbine location, determine the first metric set corresponding to each sector in different time periods; the first metric set includes at least one of the following: the occurrence probability of the time-period turbulence intensity, the average turbulence intensity, and the standard deviation of the average turbulence intensity; count the first metric set in which the occurrence probability of the time-period turbulence intensity, the average turbulence intensity, and the standard deviation of the average turbulence intensity all meet their respective first preset thresholds in the same time period. Specifically, based on the turbulence intensity corresponding to each sector, determine the first metric set corresponding to each sector in different time periods; the first metric set includes at least one of the following: the occurrence probability of the time-period turbulence intensity, the average turbulence intensity, and the standard deviation of the average turbulence intensity.

[0110] Exemplarily, divide 24 hours of a day into 12 time periods, for example, 0:00 - 2:00, 2:00 - 4:00... 22:00 - 24:00, and divide the horizontal plane circle centered on the target turbine location into 12 sectors on average, 0° - 30°, 30° - 60°... 330° - 360°. Specifically, each time period corresponds to 12 sectors, so each time period corresponds to a first metric set for 12 sectors.

[0111] The standard deviation of the average turbulence intensity is used to describe the relative strength of the wind speed fluctuation and its dispersion degree. The standard deviation of the average turbulence intensity is calculated based on the average turbulence intensity.

[0112] Count the first metric set in which the occurrence probability of the time-period turbulence intensity, the average turbulence intensity, and the standard deviation of the average turbulence intensity all meet their respective first preset thresholds in the same time period.

[0113] Here, the first preset threshold can be any appropriate value. Among them, the first preset thresholds corresponding to the occurrence probability of the time-period turbulence intensity, the average turbulence intensity, and the standard deviation of the average turbulence intensity can be the same or different.

[0114] Step 2: Based on the wind direction deflection rate corresponding to each sector, determine the second metric set corresponding to each sector within different time periods; the second metric set includes at least one of the following: the occurrence probability of the time period wind direction deflection rate, the average wind direction deflection rate, and the standard deviation of the average wind direction deflection rate; count the second metric set in which the occurrence probability of the time period wind direction deflection rate, the average wind direction deflection rate, and the standard deviation of the average wind direction deflection rate all meet their respective second preset thresholds within the same time period.

[0115] Specifically, here, the occurrence probability of the time period wind direction deflection rate refers to the probability that the wind direction undergoes a significant deflection within a specific time period. For example, it is the proportion of the number of significant deflections within this time period in a year to the total number of significant deflections in a year.

[0116] The standard deviation of the average wind direction deflection rate is used to measure the degree of dispersion of the wind direction deflection rate data, and the standard deviation of the average wind direction deflection rate is calculated based on the average wind direction deflection rate.

[0117] It should be noted that the wind direction deflection rate is the difference between the wind direction data at two different heights. Since the wind direction data at the low altitude layer is greatly affected by the terrain and landform, when analyzing the wind direction deflection rate by sector, the sector division is based on the wind direction data at the height layer where it is located.

[0118] Count the second metric set in which the occurrence probability of the time period wind direction deflection rate, the average wind direction deflection rate, and the standard deviation of the average wind direction deflection rate all meet their respective second preset thresholds within the same time period;

[0119] Here, the second preset threshold can be any appropriate value. Among them, the second preset thresholds corresponding to the occurrence probability of the time period wind direction deflection rate, the average wind direction deflection rate, and the standard deviation of the average wind direction deflection rate can be the same or different.

[0120] Step 3: Based on the vertical wind shear of each sector, determine the third metric set corresponding to each sector within different time periods; the third metric set includes at least one of the following: the occurrence probability of the time period vertical wind shear, the average vertical wind shear, and the standard deviation of the average vertical wind shear; count the third metric set in which the occurrence probability of the time period vertical wind shear, the average vertical wind shear, and the standard deviation of the average vertical wind shear all meet their respective third preset thresholds within the same time period.

[0121] Specifically, here, the occurrence probability of the time period vertical wind shear refers to the possibility or frequency of the occurrence of vertical wind shear (i.e., the change in wind direction and / or wind speed in the vertical distance) within a specific time period. For example, it is the proportion of the number of occurrences of vertical wind shear within this time period in a year to the total number of occurrences of vertical wind shear in a year.

[0122] The standard deviation of the average vertical wind shear is used to measure the dispersion degree of the vertical wind shear data, and the standard deviation of the average vertical wind shear can be calculated based on the average vertical wind shear.

[0123] Statistically, a third set of measurement criteria in the same time period is obtained when the occurrence probability of the time period vertical wind shear, the average vertical wind shear, and the standard deviation of the average vertical wind shear all meet their respective third preset thresholds.

[0124] Here, the third preset threshold can be any suitable value. Among them, the third preset thresholds corresponding to the occurrence probability of the time period vertical wind shear, the average vertical wind shear, and the standard deviation of the average vertical wind shear can be the same or different.

[0125] Step 4: Based on the first set of measurement criteria that all meet their respective first preset thresholds, the second set of measurement criteria that all meet their respective second preset thresholds, and the third set of measurement criteria that all meet their respective third preset thresholds, determine the time series data of the wind condition parameters for different sectors corresponding to the candidate turbine site.

[0126] In the method provided by the embodiments of the present invention, three meteorological parameters and various measurement criteria of vertical wind shear are used to finely divide the meteorological data, improving the accuracy, diversity, and reliability of the data. Moreover, through refined calculation and verification for each sector by referring to actual values and directly applying them to the design stage of the wind turbine generator, the performance optimization and structural safety of the unit under complex terrain conditions are ensured, significantly enhancing the pertinence and adaptability of the unit design. In addition, targeted strategies can be adopted in specific sectors to ensure the normal operation of the fan resistance and avoid economic losses caused by shutdowns.

[0127] According to a method for determining the design parameters of a wind turbine unit based on complex terrain conditions provided by the present invention, the method further includes:

[0128] Based on the standard deviation of the wind speed corresponding to each sector and the average wind speed corresponding to each sector, determine the turbulence intensity corresponding to each sector in different time periods.

[0129] Based on the wind direction data at the first height corresponding to each sector and the wind direction data at the second height corresponding to each sector, determine the wind direction deflection rate corresponding to each sector in different time periods; the first height is the hub height of the wind turbine unit at the candidate turbine site, and the first height is higher than the second height.

[0130] Based on the wind speed at the third height corresponding to each sector and the wind speed at the fourth height corresponding to each sector, determine the vertical wind shear corresponding to each sector in different time periods.

[0131] Specifically, in some embodiments, the method further includes:

[0132] Determine the turbulence intensity corresponding to each sector within different time periods based on the wind speed standard deviation corresponding to each sector and the average wind speed corresponding to each sector. Here, the turbulence intensity can be a first ratio, where the first ratio can be the ratio of the wind speed standard deviation to the average wind speed, or the ratio of the weighted wind speed standard deviation to the weighted average wind speed.

[0133] Exemplarily, the calculation of the turbulence intensity is as shown in formula (1) below:

[0134] (1)

[0135] Where, is the turbulence intensity of the th sector, is the wind speed standard deviation within the th sector, is the average wind speed.

[0136] Determine the wind direction deflection rate corresponding to each sector within different time periods based on the wind direction data at the first height corresponding to each sector and the wind direction data at the second height corresponding to each sector; the first height is the hub height of the wind turbine at the target machine location, and the first height is higher than the second height. The difference between the first height and the second height can be any suitable value, for example, 10 meters (m), 9 meters, etc.

[0137] Here, the wind direction deflection rate can be a second ratio, where the second ratio can be the ratio of the first difference to the wind direction data at the second height, or the ratio of the weighted first difference to the weighted wind direction data at the second height. The first difference can be the difference between the wind direction data at the first height and the wind direction data at the second height, or the difference between the weighted wind direction data at the first height and the weighted wind direction data at the second height.

[0138] Exemplarily, the calculation of the wind direction deflection rate is as shown in formula (2) below:

[0139] (2)

[0140] Where, is the wind direction data corresponding to the hub height of the wind turbine in the meteorological data, is the wind direction data corresponding to the lower altitude layer in the meteorological data.

[0141] Determine the vertical wind shear corresponding to each sector within different time periods based on the wind speed at the third height corresponding to each sector and the wind speed at the fourth height corresponding to each sector.

[0142] Here, the vertical wind shear can be a third ratio, and the third ratio can be the ratio of a first logarithm to a second logarithm, or the ratio of a number obtained by weighting the first logarithm to a number obtained by weighting the second logarithm. The first logarithm can be the logarithm of the ratio of the wind speed corresponding to a third height to the wind speed corresponding to a fourth height, or the logarithm of the ratio of a number obtained by weighting the wind speed corresponding to the third height to a number obtained by weighting the wind speed corresponding to the fourth height. The second logarithm can be the logarithm of the ratio of the third height to the fourth height, or the logarithm of the ratio of a number obtained by weighting the third height to a number obtained by weighting the fourth height.

[0143] Exemplarily, the calculation of the wind direction deflection rate is as shown in the following formula (3):

[0144] (3)

[0145] Where: is the wind shear index, is the third height, is the fourth height, is the wind speed corresponding to the corresponding height of, the wind speed corresponding to the corresponding height of, is the logarithm symbol.

[0146] The method provided in this embodiment uses various wind measurement data, such as wind speed, wind direction, height, etc. to calculate meteorological parameters such as turbulence intensity, wind direction deflection rate, and vertical wind shear, improving the accuracy, diversity, and reliability of wind resource data.

[0147] According to a method for determining design parameters of a wind turbine based on complex terrain conditions provided by the present invention, determining the terrain complexity level corresponding to a candidate machine site location includes:

[0148] Based on a preset number of sectors included in the candidate machine site location, determining the sector where the main wind direction of the candidate machine site location is located;

[0149] Based on the horizontal distance between at least one reference point and the candidate machine site location and the altitude corresponding to the horizontal distance, determining a functional relationship between the radius of the horizontal plane circle with the candidate machine site location as the center and the altitude corresponding to the radius; each reference point is a point within the sector where the main wind direction is located;

[0150] Based on the coefficients of the functional relationship, determining the terrain slope angle of the sector where the main wind direction is located;

[0151] Based on the mapping relationship between the preset terrain slope angle and the complexity of the terrain corresponding to the sector, determining the terrain complexity level corresponding to the candidate machine site location.

[0152] Specifically, in some embodiments, the implementation process of determining the terrain complexity level corresponding to the candidate machine site in step 103 may include the following steps:

[0153] First, based on a preset number of sectors included in the candidate machine site, determine the sector where the main wind direction of the candidate machine site is located. Here, the number of sectors can be any appropriate number, such as 12, 8, etc. The main wind direction, also known as the prevailing wind direction, refers to the range of the wind direction angle with the largest wind frequency. By collecting and analyzing historical meteorological parameters, the main wind direction of the target machine site can be determined.

[0154] Further, based on the horizontal distance between at least one reference point and the candidate machine site and the altitude corresponding to the horizontal distance, determine the functional relationship between the radius of the horizontal plane circle with the candidate machine site as the center and the altitude corresponding to the radius; each reference point is a point within the sector where the main wind direction is located.

[0155] Here, the reference points are randomly selected points within the sector where the main wind direction is located. By fitting the mapping relationship between the horizontal distance from multiple reference points to the target machine site and the altitude corresponding to the horizontal distance, the functional relationship between the horizontal distance and the altitude is obtained.

[0156] Exemplarily, Figure 2 is a schematic diagram of dividing sectors of the horizontal plane circle with the target machine site as the center provided by the present invention. As Figure 2 shown, each 30 degrees divides a sector, and there are a total of 12 sectors. Then, concentric circles are drawn with radii of 50m, 100m, 150m, 200m, 250m... 2000m respectively, where the radius represents the horizontal distance of the reference point.

[0157] Figure 3 is a schematic diagram of dividing sectors of the horizontal plane circle with the target machine site as the center provided by the present invention. As Figure 3 shown, θ is the terrain slope angle corresponding to the sector where it is located, and the altitudes of concentric circles with different radii are different.

[0158] Figure 4 is a schematic diagram of the corresponding relationship between the radius where the reference point is located and the altitude provided by the present invention. As Figure 4 shown, the horizontal axis represents the radius, and the vertical axis represents the altitude. The curve fitted by multiple reference points is close to a linear equation. Among them, the linear equation is as follows formula (4):

[0159] (4)

[0160] Among them, represents the altitude, represents the radius, represents the radius, represents the constant term or intercept. Among them,Figure 4 In the linear equation fitted from the reference points in is -0.2291, is 645.96.

[0161] Furthermore, based on the coefficients of the functional relationship, the terrain slope angle of the sector where the main wind direction is located can be determined.

[0162] Here, the terrain slope angle can be the fourth ratio, and the fourth ratio can be the ratio of 1 to the trigonometric function or the ratio of 1 to the weight of the trigonometric function. The trigonometric function can be .

[0163] Exemplarily, the calculation of the terrain slope angle is as formula (5) below:

[0164] (5)

[0165] Where, the terrain slope angle, represents the reciprocal of the trigonometric function, represents the altitude corresponding to a radius of 2000. It can be understood that, combining with (4), formula (6) can be obtained:

[0166] (6)

[0167] Furthermore, based on the preset mapping relationship between the terrain slope angle and the terrain complexity of the sector, the terrain complexity level corresponding to the candidate machine site is determined.

[0168] Here, the terrain complexity is used to characterize the level of the terrain slope angle. The mapping relationship can be that a preset terrain slope angle interval corresponds to a complexity and a level. For example, the terrain slope angle interval is 0 - 10 degrees, the corresponding level is level 1, and the corresponding complexity is generally complex; the terrain slope angle interval is 10 - 20 degrees, the corresponding level is level 2, and the corresponding complexity is relatively complex; the terrain slope angle interval is 20 - 30 degrees, the corresponding level is level 3, and the corresponding complexity is moderately complex; the terrain slope angle interval is 30 - 40 degrees, the corresponding level is level 4, and the corresponding complexity is complex; the terrain slope angle interval is 40 - 50 degrees, the corresponding level is level 5, and the corresponding complexity is extremely complex.

[0169] The method provided in this embodiment, by determining the sector where the main wind direction is located and the level, terrain complexity, etc. of the sector where the main wind direction is located, and then making a refined division of the wind resource parameters based on the terrain complexity, can improve the accuracy of determining the parameters of the wind turbine.

[0170] According to a method for determining the design parameters of a wind turbine based on complex terrain conditions provided by the present invention, the method further includes:

[0171] Determine the sector where the main wind direction of the candidate turbine site is located, the first sector and the second sector adjacent to the sector where the main wind direction of the candidate turbine site is located respectively;

[0172] Determine the terrain complexity level corresponding to the sector where the main wind direction of the candidate turbine site is located, the terrain complexity level corresponding to the first sector, and the terrain complexity level corresponding to the second sector respectively;

[0173] Design the wind turbine design parameters of each candidate turbine site according to the time series data of the wind condition parameters of different sectors corresponding to each candidate turbine site and the terrain complexity level corresponding to each candidate turbine site, including:

[0174] Design the wind turbine design parameters of each candidate turbine site according to the terrain complexity level corresponding to the sector where the main wind direction of each candidate turbine site is located, the terrain complexity level corresponding to the first sector corresponding to each candidate turbine site, and the terrain complexity level corresponding to the second sector.

[0175] Specifically, in some embodiments, the method further includes:

[0176] First, determine the sector where the main wind direction of the candidate turbine site is located, the first sector and the second sector adjacent to the sector where the main wind direction of the candidate turbine site is located respectively. Here, the first sector and the second sector are the right sector and the left sector adjacent to the sector where the main wind direction is located respectively. For example, if the sector where the main wind direction is located is 60 - 90 degrees, then the first sector is 30 - 60 degrees, and the second sector is 90 - 120 degrees.

[0177] Further, determine the terrain complexity level corresponding to the sector where the main wind direction of the candidate turbine site is located, the terrain complexity level corresponding to the first sector, and the terrain complexity level corresponding to the second sector respectively. For example, determine the second level corresponding to the first sector and the third level corresponding to the second sector respectively; the second level is used to characterize the terrain complexity of the first sector, and the third level is used to characterize the terrain complexity of the second sector.

[0178] Here, the method for determining the second level and the third level can refer to the description of determining the terrain complexity level of the sector where the main wind direction is located, which will not be elaborated here.

[0179] Correspondingly, the process of designing the wind turbine design parameters of each candidate turbine site according to the time series data of the wind condition parameters of different sectors corresponding to each candidate turbine site and the terrain complexity level corresponding to each candidate turbine site can be implemented through the following steps, including:

[0180] Design the wind turbine design parameters of each candidate machine site according to the terrain complexity level corresponding to each candidate machine site, the terrain complexity level corresponding to the first sector corresponding to each candidate machine site, and the terrain complexity level corresponding to the second sector.

[0181] The method provided in this embodiment determines the first sector and the second sector adjacent to the sector where the main wind direction is located, the level and complexity corresponding to the first sector, and the level and complexity corresponding to the second sector, expanding the range of sectors where the main wind direction may be located, and avoiding the problem of inaccurate data caused by deviation of the main wind direction. Moreover, through refined load calculation and verification by sector with reference to actual values, it is directly applied to the design stage of wind turbines, ensuring the performance optimization and structural safety of the turbines under complex terrain conditions, and significantly improving the pertinence and adaptability of the turbine design. In addition, targeted strategies can be adopted in specific sectors to ensure the normal operation of the fan resistance and avoid economic losses caused by shutdown.

[0182] According to a method for determining wind turbine design parameters based on complex terrain conditions provided by the present invention, design the wind turbine design parameters of each candidate machine site according to the time series data of wind condition parameters in different sectors corresponding to each candidate machine site and the terrain complexity level corresponding to each candidate machine site, including:

[0183] Refined classification of the time series data of wind condition parameters in different sectors corresponding to each candidate machine site is performed according to the terrain complexity level corresponding to each candidate machine site, the terrain complexity level corresponding to the first sector corresponding to each candidate machine site, and the terrain complexity level corresponding to the second sector, to obtain the refined classification result of wind condition parameters corresponding to each candidate machine site;

[0184] Among them, the refined classification result of wind condition parameters corresponding to each candidate machine site at least includes the parameter measurement criteria of the sector where the main wind direction is located, the first sector, and the second sector corresponding to each candidate machine site in different time periods. The parameter measurement criteria are used to characterize: the target time period when the occurrence probability of meteorological parameters meets the preset conditions and the threshold of the meteorological parameters corresponding to the target time period;

[0185] Based on the refined classification result of wind condition parameters corresponding to each candidate machine site, an adaptive design of the wind turbine design parameters of each candidate machine site is performed to form a key wind resource parameter threshold table.

[0186] Specifically, in some embodiments, the implementation process of designing the wind turbine design parameters of each candidate machine site according to the time series data of wind condition parameters in different sectors corresponding to each candidate machine site and the terrain complexity level corresponding to each candidate machine site in step 104 can be implemented through the following steps, including:

[0187] First, according to the terrain complexity levels corresponding to each candidate turbine site, the terrain complexity levels corresponding to the first sector and the second sector corresponding to each candidate turbine site, the time series data of the wind condition parameters for different sectors corresponding to each candidate turbine site are classified in detail to obtain the refined classification results of the wind condition parameters corresponding to each candidate turbine site. Among them, the refined classification results of the wind condition parameters corresponding to each candidate turbine site at least include the parameter measurement criteria for the sector where the main wind direction is located, the first sector, and the second sector corresponding to each candidate turbine site in different time periods. The parameter measurement criteria are used to characterize: the target time period when the occurrence probability of the meteorological parameter meets the preset condition and the threshold of the meteorological parameter corresponding to the target time period. For example, Table 1 below:

[0188] Table 1:

[0189]

[0190] Furthermore, based on the refined classification results of the wind condition parameters corresponding to each candidate turbine site, the wind turbine design parameters corresponding to each candidate turbine site can be adaptively designed to form a critical wind resource parameter threshold table. The critical wind resource parameter threshold table is shown in Table 2 below:

[0191] Table 2:

[0192]

[0193] The method provided in this embodiment first classifies the time series data of the wind condition parameters for different sectors corresponding to each candidate turbine site in detail according to the terrain complexity levels corresponding to each candidate turbine site, the terrain complexity levels corresponding to the first sector and the second sector corresponding to each candidate turbine site, to obtain the refined classification results of the wind condition parameters corresponding to each candidate turbine site. Among them, the refined classification results of the wind condition parameters corresponding to each candidate turbine site at least include the parameter measurement criteria for the sector where the main wind direction is located, the first sector, and the second sector corresponding to each candidate turbine site in different time periods. The parameter measurement criteria are used to characterize: the target time period when the occurrence probability of the meteorological parameter meets the preset condition and the threshold of the meteorological parameter corresponding to the target time period; then, based on the refined classification results of the wind condition parameters corresponding to each candidate turbine site, the wind turbine design parameters corresponding to each candidate turbine site are adaptively designed to form a critical wind resource parameter threshold table.

[0194] The present invention creatively combines the measured data (meteorological parameters) and terrain data (terrain complexity under complex terrain conditions), considers the comprehensive influence of complex terrain on the components of wind condition parameters, and further designs the wind turbine design parameters corresponding to each candidate turbine site according to the time series data of the wind condition parameters for different sectors corresponding to each candidate turbine site and the terrain complexity level corresponding to each candidate turbine site, improving the accuracy of determining the wind turbine design parameters.

[0195] A method for determining design parameters of a wind turbine based on complex terrain conditions provided by the present invention further includes:

[0196] Using the sample meteorological parameters of each candidate turbine site, the terrain complexity level of each candidate turbine site, and the label data of each candidate turbine site to train an initial deep learning network, and obtaining a refined model for determining wind turbine design parameters;

[0197] Using the refined model for determining wind turbine design parameters to determine the values of the wind turbine design parameters for the target turbine site.

[0198] Specifically, in some embodiments, the method further includes:

[0199] Using the sample meteorological parameters of each candidate turbine site, the terrain complexity level of each candidate turbine site, and the label data of each candidate turbine site to train an initial deep learning network, and obtaining a refined model for determining wind turbine design parameters. Among them, deep learning networks are a type of artificial neural network composed of multiple layers, and they can learn multi-level representations and abstractions of data. An example of the process of training to obtain a refined model for determining wind turbine design parameters is as follows:

[0200] First, take the sample meteorological parameters of each candidate turbine site and the terrain complexity level of each candidate turbine site as sample data, and take the label data of each candidate turbine site as the label corresponding to the sample data, and input them into the initial deep learning network together;

[0201] After meeting the preset number of iterations, determine the model parameters at the end of the iteration as the model parameters of the refined model for determining wind turbine design parameters, and thus complete the model training of deep learning.

[0202] Furthermore, the refined model for determining wind turbine design parameters can be used to determine the values of the wind turbine design parameters for the target turbine site. Using the trained refined model for determining wind turbine design parameters to determine the values of the wind turbine design parameters for the target turbine site, the determination accuracy is relatively high.

[0203] In this embodiment, first use the sample meteorological parameters of each candidate turbine site, the terrain complexity level of each candidate turbine site, and the label data of each candidate turbine site to train an initial deep learning network, and obtain a refined model for determining wind turbine design parameters. Furthermore, use the refined model for determining wind turbine design parameters to determine the values of the wind turbine design parameters for the target turbine site, and the accuracy of parameter determination is improved.

[0204] Figure 5It is the second flow schematic diagram of the method for determining the design parameters of a wind turbine based on complex terrain conditions provided by the present invention. As Figure 5 shown, it specifically includes the following steps:

[0205] Step 501: Select the target machine location points in the wind farm.

[0206] Among them, the target machine location points are representative machine location points. The method for selecting the target machine location points can refer to the above method for determining the target machine location points, which will not be elaborated here.

[0207] Step 502: Calculate the turbulence intensity of the target machine location points and classify them by sector.

[0208] Step 503: Calculate the wind direction deflection rate of the target machine location points and classify them by sector.

[0209] Step 504: Calculate the vertical wind shear of the target machine location points and classify them by sector.

[0210] Step 505: Calculate the terrain slope angles corresponding to the sectors where the main wind direction is located, the terrain slope angle corresponding to the first sector, and the terrain slope angle corresponding to the second sector respectively.

[0211] Step 506: Statistically analyze the terrain complexity levels corresponding to each sector.

[0212] Step 507: Refine the resource data statistics.

[0213] Step 508: Conduct a site adaptability safety analysis of the target machine location points.

[0214] The method for determining the design parameters of a wind turbine based on complex terrain conditions provided by the embodiments of the present invention has the following advantages: combined analysis of meteorological parameters and terrain parameters: through the wind measurement data and terrain data (terrain slope) in actual projects, the complex correlation between the two is systematically explored. This analysis not only improves the accuracy of wind resource assessment, but also takes into account the comprehensive impact of complex terrain on meteorological parameters in the assessment method for the first time; refined design of sector load calculation: based on different grades of complex terrain, various wind resource parameters in each sector, and the time period when each parameter variable appears, load calculation is carried out. Through referring to actual values, refined load calculation and verification are carried out for each sector. This method is directly applied to the design stage of wind turbines, ensuring the performance optimization and structural safety of the turbines under complex terrain conditions, and significantly improving the pertinence and adaptability of the turbine design; targeted design parameter regulation for high-turbulence and high-shear sectors: aiming at the problem that traditional wind turbines often adopt direct shutdown methods in high-turbulence sectors, resulting in power generation loss, it is proposed to obtain the corresponding occurrence time of high-turbulence and high-shear through time series data, and bring the design method of looking up the parameters of high-turbulence and high-sector according to the threshold time matrix table into the unit control strategy, so as to realize the stable operation and efficient power generation of the unit in a high-turbulence environment, and improve the economic benefits of the whole field.

[0215] The device for determining the design parameters of a wind turbine based on complex terrain conditions provided by the present invention will be described below. The device for determining the design parameters of a wind turbine based on complex terrain conditions described below can be correspondingly referred to the method for determining the design parameters of a wind turbine based on complex terrain conditions described above.

[0216] Figure 6 is a schematic structural diagram of the device for determining the design parameters of a wind turbine based on complex terrain conditions provided by the present invention. Refer to Figure 6 As shown, the device 600 for determining the design parameters of a wind turbine based on complex terrain conditions includes: a unit division module 610 and a design parameter determination model 602; wherein:

[0217] The unit division module 610 is used to determine at least two candidate machine positions according to the incoming flow direction of the wind farm and the preliminary unit layout plan; the preliminary unit layout plan is used to represent the layout positions of the machine positions of the wind turbines in the wind farm area;

[0218] The design parameter determination module 620, for any one of the candidate machine positions, determines the time series data of the wind condition parameters of different sectors corresponding to the candidate machine position according to the meteorological parameters of the candidate machine position and a preset number of sectors included in the candidate machine position;

[0219] Determine the terrain complexity level corresponding to the candidate turbine site; the terrain complexity level is used to characterize the complexity of the terrain corresponding to the sector where the main wind direction of the candidate turbine site is located, and the terrain complexity level includes any one of the following from low to high: generally complex, relatively complex, moderately complex, complex, extremely complex;

[0220] Design the wind turbine design parameters for each candidate turbine site according to the time series data of the wind condition parameters of different sectors corresponding to each candidate turbine site and the terrain complexity level corresponding to each candidate turbine site.

[0221] The device for determining the wind turbine design parameters based on complex terrain conditions provided by the present invention includes: a unit division module 610 and a design parameter determination module 620. First, the unit division module 610 determines at least two candidate turbine sites according to the incoming flow direction of the wind farm and the preliminary unit layout plan, where the preliminary unit layout plan is used to characterize the layout positions of the turbine sites of the wind turbines in the wind farm area; then, for any candidate turbine site, the design parameter determination module 620 determines the time series data of the wind condition parameters of different sectors corresponding to the candidate turbine site according to the meteorological parameters of the candidate turbine site and the preset number of sectors included in the candidate turbine site, and determines the terrain complexity level corresponding to the candidate turbine site, where the terrain complexity level is used to characterize the complexity of the terrain corresponding to the sector where the main wind direction of the candidate turbine site is located, and the terrain complexity level includes any one of the following from low to high: generally complex, relatively complex, moderately complex, complex, extremely complex; furthermore, the wind turbine design parameters for each candidate turbine site can be designed according to the time series data of the wind condition parameters of different sectors corresponding to each candidate turbine site and the terrain complexity level corresponding to each candidate turbine site.

[0222] In the present invention, the measured data (meteorological parameters) and terrain data (terrain complexity under complex terrain conditions) are creatively combined, considering the comprehensive influence of complex terrain on the components of wind condition parameters. Furthermore, the wind turbine design parameters for each candidate turbine site are designed according to the time series data of the wind condition parameters of different sectors corresponding to each candidate turbine site and the terrain complexity level corresponding to each candidate turbine site, improving the accuracy of determining the wind turbine design parameters.

[0223] According to the device 600 for determining the wind turbine design parameters based on complex terrain conditions provided by the present invention, the design parameter determination module 620 is specifically used for:

[0224] Determine the time series data of the wind condition parameters of the candidate turbine site according to the meteorological parameters of the candidate turbine site;

[0225] According to the preset number of sectors, sector classification is performed on the time series data of the wind condition parameters of each of the candidate turbine locations, and the time series data of the wind condition parameters of different sectors corresponding to the candidate turbine locations are obtained.

[0226] According to the wind turbine design parameter determination device 600 based on complex terrain conditions provided by the present invention, the preset number of sectors is obtained by dividing the horizontal plane circle centered on the candidate turbine location; the time series data of the wind condition parameters include turbulence intensity, wind direction deflection rate, and wind shear.

[0227] The design parameter determination module 620 is further configured to:

[0228] For any one of the candidate turbine locations, based on the turbulence intensity corresponding to each of the sectors in the candidate turbine location, a first metric set corresponding to each of the sectors in different time periods is determined; the first metric set includes at least one of the following: the occurrence probability of the turbulence intensity in the time period, the average turbulence intensity, and the standard deviation of the average turbulence intensity.

[0229] Count the first metric sets in the same time period where the occurrence probability of the turbulence intensity in the time period, the average turbulence intensity, and the standard deviation of the average turbulence intensity all meet their respective first preset thresholds.

[0230] Based on the wind direction deflection rate corresponding to each of the sectors, a second metric set corresponding to each of the sectors in different time periods is determined; the second metric set includes at least one of the following: the occurrence probability of the wind direction deflection rate in the time period, the average wind direction deflection rate, and the standard deviation of the average wind direction deflection rate.

[0231] Count the second metric sets in the same time period where the occurrence probability of the wind direction deflection rate in the time period, the average wind direction deflection rate, and the standard deviation of the average wind direction deflection rate all meet their respective second preset thresholds.

[0232] Based on the vertical wind shear corresponding to each of the sectors, a third metric set corresponding to each of the sectors in different time periods is determined; the third metric set includes at least one of the following: the occurrence probability of the vertical wind shear in the time period, the average vertical wind shear, and the standard deviation of the average vertical wind shear.

[0233] Count the third metric sets in the same time period where the occurrence probability of the vertical wind shear in the time period, the average vertical wind shear, and the standard deviation of the average vertical wind shear all meet their respective third preset thresholds.

[0234] Based on the first set of measurement criteria all meeting their respective first preset thresholds, the second set of measurement criteria all meeting their respective second preset thresholds, and the third set of measurement criteria all meeting their respective third preset thresholds, determine the time series data of the wind condition parameters for different sectors corresponding to the candidate turbine site.

[0235] For the wind turbine design parameter determination device 600 based on complex terrain conditions provided by the present invention, the design parameter determination module 620 is further configured to:

[0236] Based on the standard deviation of the wind speed corresponding to each sector and the average wind speed corresponding to each sector, determine the turbulence intensity corresponding to each sector in different time periods;

[0237] Based on the wind direction data at the first height corresponding to each sector and the wind direction data at the second height corresponding to each sector, determine the wind direction deflection rate corresponding to each sector in different time periods; the first height is the hub height of the wind turbine at the candidate turbine site, and the first height is higher than the second height;

[0238] Based on the wind speed at the third height corresponding to each sector and the wind speed at the fourth height corresponding to each sector, determine the vertical wind shear corresponding to each sector in different time periods.

[0239] For the wind turbine design parameter determination device 600 based on complex terrain conditions provided by the present invention, determining the terrain complexity level corresponding to the candidate turbine site includes:

[0240] Based on a preset number of sectors included in the candidate turbine site, determine the sector where the main wind direction of the candidate turbine site is located;

[0241] Based on the horizontal distance between at least one reference point and the candidate turbine site and the altitude corresponding to the horizontal distance, determine the functional relationship between the radius of the horizontal plane circle with the candidate turbine site as the center and the altitude corresponding to the radius; each reference point is a point in the sector where the main wind direction is located;

[0242] Based on the coefficients of the functional relationship, determine the terrain slope angle of the sector where the main wind direction is located;

[0243] Based on the mapping relationship between the preset terrain slope angle and the complexity of the sector - corresponding terrain, determine the terrain complexity level corresponding to the candidate turbine site.

[0244] For the wind turbine design parameter determination device 600 based on complex terrain conditions provided by the present invention, the method further includes:

[0245] Determine the sector where the main wind direction of the candidate wind turbine site is located, the first sector and the second sector adjacent to the sector where the main wind direction of the candidate wind turbine site is located, respectively;

[0246] Determine the terrain complexity level corresponding to the sector where the main wind direction of the candidate wind turbine site is located, the terrain complexity level corresponding to the first sector, and the terrain complexity level corresponding to the second sector, respectively;

[0247] Design the wind turbine design parameters of each candidate wind turbine site according to the wind condition parameter time series data of different sectors corresponding to each candidate wind turbine site and the terrain complexity level corresponding to each candidate wind turbine site, including:

[0248] Design the wind turbine design parameters of each candidate wind turbine site according to the terrain complexity level corresponding to the sector where the main wind direction of each candidate wind turbine site is located, the terrain complexity level corresponding to the first sector corresponding to each candidate wind turbine site, and the terrain complexity level corresponding to the second sector.

[0249] According to the wind turbine design parameter determination device 600 based on complex terrain conditions provided by the present invention, the design parameter determination module 620 is further configured to:

[0250] Refine and classify the wind condition parameter time series data of different sectors corresponding to each candidate wind turbine site according to the terrain complexity level corresponding to each candidate wind turbine site, the terrain complexity level corresponding to the first sector corresponding to each candidate wind turbine site, and the terrain complexity level corresponding to the second sector, to obtain the refined classification result of the wind condition parameters corresponding to each candidate wind turbine site;

[0251] Among them, the refined classification result of the wind condition parameters corresponding to each candidate wind turbine site at least includes the parameter measurement criteria of the sector where the main wind direction of each candidate wind turbine site is located, the first sector, and the second sector in different time periods, and the parameter measurement criteria are used to characterize: the target time period when the occurrence probability of meteorological parameters meets the preset conditions and the threshold of the meteorological parameters corresponding to the target time period;

[0252] Based on the refined classification result of the wind condition parameters corresponding to each candidate wind turbine site, adaptively design the wind turbine design parameters of each candidate wind turbine site to form a key wind resource parameter threshold table.

[0253] The wind turbine design parameter determination device 600 based on complex terrain conditions provided by the present invention further includes a deep learning model training module;

[0254] The deep learning model training module is used for:

[0255] Using the sample meteorological parameters of each of the candidate machine sites, the terrain complexity level of each of the candidate machine sites, and the label data of each of the candidate machine sites, train an initial deep learning network to obtain a refined wind turbine design parameter determination model;

[0256] Using the refined wind turbine design parameter determination model, determine the values of the wind turbine design parameters for the target machine site.

[0257] Figure 7 is a schematic structural diagram of an electronic device provided by the present invention, as Figure 7 shown. The electronic device may include: a processor 710, a communication interface 720, a memory 730, and a communication bus 740. Among them, the processor 710, the communication interface 720, and the memory 730 complete mutual communication through the communication bus 740. The processor 710 may call the logical instructions in the memory 730 to execute a method for determining wind turbine design parameters based on complex terrain conditions. The method includes:

[0258] According to the incoming flow direction of the wind farm and the preliminary unit layout plan, determine at least two candidate machine sites; the preliminary unit layout plan is used to characterize the layout positions of the machine sites of the wind turbines in the wind farm area;

[0259] For any one of the candidate machine sites, according to the meteorological parameters of the candidate machine site and a preset number of sectors included in the candidate machine site, determine the time series data of the wind condition parameters of different sectors corresponding to the candidate machine site;

[0260] Determine the terrain complexity level corresponding to the candidate machine site; the terrain complexity level is used to characterize the complexity of the terrain corresponding to the sector where the main wind direction of the candidate machine site is located. The terrain complexity level includes any one of the following from low to high: generally complex, relatively complex, moderately complex, complex, extremely complex;

[0261] According to the time series data of the wind condition parameters of different sectors corresponding to each of the candidate machine sites and the terrain complexity level corresponding to each of the candidate machine sites, design the wind turbine design parameters of each of the candidate machine sites.

[0262] In addition, when the logical instructions in the above-mentioned memory 730 are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs that can store program codes.

[0263] On the other hand, the present invention also provides a computer program product. The computer program product includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the method for determining the design parameters of a wind turbine based on complex terrain conditions provided by the above-mentioned various methods. The method includes:

[0264] According to the incoming flow direction of the wind farm and the preliminary unit layout plan, determine at least two candidate machine positions; the preliminary unit layout plan is used to characterize the layout positions of the machine positions of the wind turbines in the wind farm area;

[0265] For any one of the candidate machine positions, according to the meteorological parameters of the candidate machine position and a preset number of sectors included in the candidate machine position, determine the time series data of the wind condition parameters of different sectors corresponding to the candidate machine position;

[0266] Determine the terrain complexity level corresponding to the candidate machine position; the terrain complexity level is used to characterize the complexity of the terrain corresponding to the sector where the main wind direction of the candidate machine position is located. The terrain complexity level includes any one of the following from low to high: generally complex, relatively complex, moderately complex, complex, and extremely complex;

[0267] According to the time series data of the wind condition parameters of different sectors corresponding to each candidate machine position and the terrain complexity level corresponding to each candidate machine position, design the design parameters of the wind turbines at each candidate machine position.

[0268] On another aspect, the present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it is implemented to execute the method for determining the design parameters of a wind turbine based on complex terrain conditions provided by the above-mentioned various methods. The method includes:

[0269] According to the incoming flow direction of the wind farm and the preliminary unit layout plan, determine at least two candidate unit locations; the preliminary unit layout plan is used to characterize the layout positions of the unit locations of the wind turbines in the wind farm area;

[0270] For any one of the candidate unit locations, according to the meteorological parameters of the candidate unit location and a preset number of sectors included in the candidate unit location, determine the time series data of the wind condition parameters of different sectors corresponding to the candidate unit location;

[0271] Determine the terrain complexity level corresponding to the candidate unit location; the terrain complexity level is used to characterize the complexity of the terrain corresponding to the sector where the main wind direction of the candidate unit location is located, and the terrain complexity level includes any one of the following from low to high: generally complex, relatively complex, moderately complex, complex, extremely complex;

[0272] Design the wind turbine design parameters of each candidate unit location according to the time series data of the wind condition parameters of different sectors corresponding to each candidate unit location and the terrain complexity level corresponding to each candidate unit location.

[0273] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative work.

[0274] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence, or the part that contributes to the prior art can be embodied in the form of a software product, and this computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., including several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0275] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for determining the design parameters of a wind turbine based on complex terrain conditions, characterized in that Including: Determine at least two candidate turbine locations according to the incoming flow direction of the wind farm and the preliminary turbine layout plan; The preliminary turbine layout plan is used to characterize the layout positions of the turbine locations of the wind turbines in the wind farm area; For any one of the candidate turbine locations, determine the time series data of the wind condition parameters of different sectors corresponding to the candidate turbine location according to the meteorological parameters of the candidate turbine location and the preset number of sectors included in the candidate turbine location; Determine the terrain complexity level corresponding to the candidate turbine location; the terrain complexity level is used to characterize the complexity of the terrain corresponding to the sector where the main wind direction of the candidate turbine location is located, and the terrain complexity level includes any one of the following from low to high: generally complex, relatively complex, moderately complex, complex, extremely complex; Design the wind turbine design parameters of each candidate turbine location according to the time series data of the wind condition parameters of different sectors corresponding to each candidate turbine location and the terrain complexity level corresponding to each candidate turbine location; The designing the wind turbine design parameters of each candidate turbine location according to the time series data of the wind condition parameters of different sectors corresponding to each candidate turbine location and the terrain complexity level corresponding to each candidate turbine location includes: Determine the sector where the main wind direction of the candidate turbine location is located, the first sector and the second sector adjacent to the sector where the main wind direction of the candidate turbine location is located respectively; Determine the terrain complexity level corresponding to the terrain of the sector where the main wind direction of the candidate turbine location is located, the terrain complexity level corresponding to the first sector, and the terrain complexity level corresponding to the second sector respectively; Design the wind turbine design parameters of each candidate turbine location according to the terrain complexity level corresponding to the sector where the main wind direction of each candidate turbine location is located, the terrain complexity level corresponding to the first sector corresponding to each candidate turbine location, and the terrain complexity level corresponding to the second sector; Refine the classification of the time series data of the wind condition parameters of different sectors corresponding to each candidate turbine location according to the terrain complexity level corresponding to each candidate turbine location, the terrain complexity level corresponding to the first sector corresponding to each candidate turbine location, and the terrain complexity level corresponding to the second sector, to obtain the refined classification result of the wind condition parameters corresponding to each candidate turbine location.

2. The method for determining the design parameters of a wind turbine based on complex terrain conditions according to claim 1, wherein The determining the time series data of the wind condition parameters of different sectors corresponding to the candidate turbine location according to the meteorological parameters of the candidate turbine location and the preset number of sectors included in the candidate turbine location includes: Determine the time series data of the wind condition parameters of the candidate turbine location according to the meteorological parameters of the candidate turbine location; Classify the time series data of the wind condition parameters of each candidate turbine location into sectors according to the preset number of sectors to obtain the time series data of the wind condition parameters of different sectors corresponding to the candidate turbine location.

3. The method for determining the design parameters of a wind turbine based on complex terrain conditions according to claim 2, wherein The preset number of sectors is obtained by dividing the horizontal plane circle with the candidate turbine location as the center; the time series data of the wind condition parameters includes turbulence intensity, wind direction deflection rate, and wind shear; Classifying the time series data of the wind condition parameters of each of the candidate turbine locations according to the preset number of sectors to obtain the time series data of the wind condition parameters of different sectors corresponding to the candidate turbine locations, including: For any one of the candidate turbine locations, determining a first metric set corresponding to each of the sectors within different time periods based on the turbulence intensity corresponding to each of the sectors in the candidate turbine location; the first metric set includes at least one of the following: the occurrence probability of the turbulence intensity in the time period, the average turbulence intensity, and the standard deviation of the average turbulence intensity; Counting the first metric set in which the occurrence probability of the turbulence intensity in the time period, the average turbulence intensity, and the standard deviation of the average turbulence intensity all satisfy their respective first preset thresholds within the same time period; Determining a second metric set corresponding to each of the sectors within different time periods based on the wind direction deflection rate corresponding to each of the sectors; the second metric set includes at least one of the following: the occurrence probability of the wind direction deflection rate in the time period, the average wind direction deflection rate, and the standard deviation of the average wind direction deflection rate; Counting the second metric set in which the occurrence probability of the wind direction deflection rate in the time period, the average wind direction deflection rate, and the standard deviation of the average wind direction deflection rate all satisfy their respective second preset thresholds within the same time period; Determining a third metric set corresponding to each of the sectors within different time periods based on the vertical wind shear corresponding to each of the sectors; the third metric set includes at least one of the following: the occurrence probability of the vertical wind shear in the time period, the average vertical wind shear, and the standard deviation of the average vertical wind shear; Counting the third metric set in which the occurrence probability of the vertical wind shear in the time period, the average vertical wind shear, and the standard deviation of the average vertical wind shear all satisfy their respective third preset thresholds within the same time period; Determining the time series data of the wind condition parameters of different sectors corresponding to the candidate turbine location based on the first metric set that all satisfy their respective first preset thresholds, the second metric set that all satisfy their respective second preset thresholds, and the third metric set that all satisfy their respective third preset thresholds.

4. The method for determining the design parameters of a wind turbine based on complex terrain conditions according to claim 3, wherein The method further includes: Determining the turbulence intensity corresponding to each of the sectors within different time periods based on the standard deviation of the wind speed corresponding to each of the sectors and the average wind speed corresponding to each of the sectors; Determining the wind direction deflection rate corresponding to each of the sectors within different time periods based on the wind direction data at a first height corresponding to each of the sectors and the wind direction data at a second height corresponding to each of the sectors; the first height is the hub height of the wind turbine at the candidate turbine location, and the first height is higher than the second height; Determining the vertical wind shear corresponding to each of the sectors within different time periods based on the wind speed at a third height corresponding to each of the sectors and the wind speed at a fourth height corresponding to each of the sectors.

5. The method for determining the design parameters of a wind turbine based on complex terrain conditions according to claim 1, wherein Determining the terrain complexity level corresponding to the candidate turbine location includes: Determining the sector where the main wind direction of the candidate turbine location is located based on the preset number of sectors included in the candidate turbine location; Based on the horizontal distance between at least one reference point and the candidate turbine site and the altitude corresponding to the horizontal distance, determine the functional relationship between the radius of the horizontal plane circle with the candidate turbine site as the center and the altitude corresponding to the radius; each of the reference points is a point within the sector where the main wind direction is located; Based on the coefficients of the functional relationship, determine the terrain slope angle of the sector where the main wind direction is located; Based on the preset mapping relationship between the terrain slope angle and the terrain complexity of the sector, determine the terrain complexity level corresponding to the candidate turbine site.

6. The method for determining the design parameters of a wind turbine based on complex terrain conditions according to claim 5, wherein The design of the wind turbine design parameters for each candidate turbine site according to the time series data of the wind condition parameters of different sectors corresponding to each candidate turbine site and the terrain complexity level corresponding to each candidate turbine site includes: Based on the refined classification results of the wind condition parameters corresponding to each candidate turbine site, conduct an adaptive design of the wind turbine design parameters for each candidate turbine site to form a key wind resource parameter threshold table; Among them, the refined classification results of the wind condition parameters corresponding to each candidate turbine site at least include the parameter measurement criteria in different time periods for the sector where the main wind direction of each candidate turbine site is located, the first sector, and the second sector, and the parameter measurement criteria are used to characterize: the target time period when the occurrence probability of the meteorological parameter meets the preset condition and the threshold of the meteorological parameter corresponding to the target time period.

7. A device for determining the design parameters of a wind turbine based on complex terrain conditions, characterized in that, It includes: A unit division module, configured to determine at least two candidate turbine sites according to the incoming flow direction of the wind farm and the preliminary unit layout plan; The preliminary unit layout plan is used to represent the layout positions of the turbine sites of the wind turbines in the wind farm plant area; A design parameter determination module, for any one of the candidate turbine sites, determine the time series data of the wind condition parameters of different sectors corresponding to the candidate turbine site according to the meteorological parameters of the candidate turbine site and the preset number of sectors included in the candidate turbine site; Determine the terrain complexity level corresponding to the candidate turbine site; the terrain complexity level is used to characterize the complexity of the terrain corresponding to the sector where the main wind direction of the candidate turbine site is located, and the terrain complexity level includes any one of the following from low to high: generally complex, relatively complex, moderately complex, complex, extremely complex; Design the wind turbine design parameters for each candidate turbine site according to the time series data of the wind condition parameters of different sectors corresponding to each candidate turbine site and the terrain complexity level corresponding to each candidate turbine site; The design parameter determination module is specifically configured to determine the sector where the main wind direction of the candidate turbine site is located, the first sector and the second sector adjacent to the sector where the main wind direction of the candidate turbine site is located respectively; determine the terrain complexity level corresponding to the sector where the main wind direction of the candidate turbine site is located, the terrain complexity level corresponding to the first sector, and the terrain complexity level corresponding to the second sector respectively; design the wind turbine design parameters of each candidate turbine site according to the terrain complexity level corresponding to the sector where the main wind direction of each candidate turbine site is located, the terrain complexity level corresponding to the first sector corresponding to each candidate turbine site, and the terrain complexity level corresponding to the second sector; and refine the classification of the time series data of the wind condition parameters of different sectors corresponding to each candidate turbine site according to the terrain complexity level corresponding to each candidate turbine site, the terrain complexity level corresponding to the first sector corresponding to each candidate turbine site, and the terrain complexity level corresponding to the second sector, so as to obtain the refined classification result of the wind condition parameters corresponding to each candidate turbine site.

8. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method for determining the design parameters of a wind turbine based on complex terrain conditions according to any one of claims 1 to 6.

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