Method and device for determining design parameters of wind turbine generator based on complex topographic conditions

Abstract

The invention provides a wind turbine generator design parameter determination method and device based on complex terrain conditions, and the method comprises the steps: determining at least two candidate machine sites according to the incoming flow direction of a wind power plant and a preliminary machine set arrangement scheme, and the preliminary machine set arrangement scheme is used for representing the machine site arrangement position of a wind turbine generator in a wind power plant area; for any candidate aircraft site, determining wind regime parameter time sequence data of different sectors corresponding to the candidate aircraft site according to meteorological parameters of the candidate aircraft site and a preset number of sectors included in the candidate aircraft site, and determining a terrain complexity level corresponding to the candidate aircraft site, the terrain complexity level is used for representing the complexity of the terrain corresponding to the sector where the main wind direction of the candidate camera location point is located; and according to the wind regime parameter time sequence data of different sectors corresponding to the candidate machine sites and the terrain complexity levels corresponding to the candidate machine sites, designing wind turbine generator design parameters of the candidate machine sites. The accuracy of determining the design parameters of the wind turbine generator is improved.

Description

Technical Field

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

[0002] At present, the mainstream wind resource assessment method mainly relies on the erection of wind measuring towers and other wind measuring equipment in the wind farm site area. The wind resource parameter data of each machine site is obtained through wind measurement data analysis and computational fluid dynamics (CFD) flow field simulation calculation. Finally, the calculation results of the wind resource parameter data are used as envelope values ​​for the design calculation of the wind turbine.

[0003] However, the number of wind towers in wind farms under complex terrain is small, which makes the results of flow field simulation software inaccurate. The lack of resource data for complex terrain leads to poor accuracy in determining the design parameters of wind turbines, resulting in the designed wind turbine parameters being unable to be applied to power plants in complex terrain. Summary of the invention

[0004] The present invention provides a method and device for determining design parameters of a wind turbine generator set based on complex terrain conditions, so as to solve the defect of the prior art that the lack of resource data of complex terrain leads to poor accuracy in determining design parameters of the wind turbine generator set, thereby improving the accuracy of determining 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 generator system based on complex terrain conditions, the method comprising the following steps: Determine at least two candidate generator sites according to the incoming flow direction of the wind farm and the preliminary generator arrangement plan; the preliminary generator arrangement plan is used to characterize the generator site arrangement positions of the wind turbine generators in the wind farm plant area; For any of the candidate station locations, according to the meteorological parameters of the candidate station location and a preset number of sectors included in the candidate station location, determine the time series data of wind condition parameters of different sectors corresponding to the candidate station location; Determine the terrain complexity level corresponding to the candidate station 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 station 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, and extremely complex; The design parameters of the wind turbine generator set at each candidate generator site are designed according to the time series data of wind condition parameters of different sectors corresponding to each candidate generator site and the terrain complexity level corresponding to each candidate generator site.

[0006] According to a method for determining design parameters of a wind turbine generator set based on complex terrain conditions provided by the present invention, the method determines the time series data of wind condition parameters of different sectors corresponding to the candidate generator site according to the meteorological parameters of the candidate generator site and a preset number of sectors included in the candidate generator site, including: Determine the time series data of the wind condition parameters of the candidate station location according to the meteorological parameters of the candidate station location; According to the preset number of sectors, the wind condition parameter time series data of each candidate station location is sector-classified to obtain the wind condition parameter time series data of different sectors corresponding to the candidate station location.

[0007] According to a method for determining design parameters of a wind turbine generator set based on complex terrain conditions provided by the present invention, the preset number of sectors is obtained by dividing a horizontal circle with the candidate generator site as the center; the wind condition parameter time series data includes turbulence intensity, wind direction deflection rate and wind shear; The step of performing sector classification on the wind condition parameter time series data of each candidate station location according to the preset number of sectors to obtain the wind condition parameter time series data of different sectors corresponding to the candidate station location includes: For any of the candidate machine sites, based on the turbulence intensity corresponding to each of the sectors in the candidate machine site, determine a first metric standard set corresponding to each of the sectors in different time periods; the first metric standard set includes at least one of the following: the probability of occurrence of turbulence intensity in the time period, the average turbulence intensity, and the standard deviation of the average turbulence intensity; Counting the probability of occurrence of turbulence intensity in the time period, the average turbulence intensity and the standard deviation of the average turbulence intensity in the same time period, all of which meet the first metric standard set corresponding to the first preset threshold value; Based on the wind direction deflection rate corresponding to each of the sectors, determining a second metric standard set corresponding to each of the sectors in different time periods; the second metric standard set includes at least one of the following: the probability of occurrence 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 probability of occurrence 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 in the same time period, all of which meet the second metric standard set corresponding to the second preset threshold value; Based on the vertical wind shear of each of the sectors, determine a third metric standard set corresponding to each of the sectors in different time periods; the third metric standard set includes at least one of the following: the probability of occurrence of vertical wind shear in the time period, the average vertical wind shear, and the standard deviation of the average vertical wind shear; Counting the probability of vertical wind shear occurring in the time period, the average vertical wind shear, and the average vertical wind shear standard deviation in the same time period, all of which satisfy the third metric standard set corresponding to the third preset threshold value; Based on the first set of metric standards that all meet the corresponding first preset thresholds, the second set of metric standards that all meet the corresponding second preset thresholds, and the third set of metric standards that all meet the corresponding third preset thresholds, the wind condition parameter time series data of different sectors corresponding to the candidate machine site are determined.

[0008] According to a method for determining design parameters of a wind turbine generator system based on complex terrain conditions provided by the present invention, the method further includes: Determining the turbulence intensity corresponding to each of the sectors in different time periods based on the wind speed standard deviation corresponding to each of the sectors and the average wind speed corresponding to each of the sectors; Based on the wind direction data at the first height corresponding to each of the sectors and the wind direction data at the second height corresponding to each of the sectors, the wind direction deflection rate of each of the sectors in different time periods is determined; the first height is the height of the hub of the wind turbine at the candidate machine site, and the first height is higher than the second height; Based on the wind speed at the third height corresponding to each of the sectors and the wind speed at the fourth height corresponding to each of the sectors, the vertical wind shear of each of the sectors in different time periods is determined.

[0009] According to a method for determining design parameters of a wind turbine generator set based on complex terrain conditions provided by the present invention, the step of determining the terrain complexity level corresponding to the candidate generator site includes: Based on a preset number of sectors included in the candidate station site, determining a sector where the main wind direction of the candidate station site is located; 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 a functional relationship between the radius of a horizontal plane circle with the candidate machine 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, determining the terrain slope angle of the sector where the main wind direction is located; Based on the mapping relationship between the preset terrain slope angle and the complexity of the terrain corresponding to the sector, the terrain complexity level corresponding to the candidate machine site is determined.

[0010] According to a method for determining design parameters of a wind turbine generator system based on complex terrain conditions provided by the present invention, the method further includes: Determine a sector where the main wind direction of the candidate station site is located, and a first sector and a second sector respectively adjacent to the sector where the main wind direction of the candidate station site is located; respectively determining a terrain complexity level corresponding to a sector where the main wind direction of the candidate machine site is located, a terrain complexity level corresponding to the first sector, and a terrain complexity level corresponding to the second sector; The design parameters of the wind turbine generator set at each candidate generator site are designed according to the time series data of wind condition parameters of different sectors corresponding to each candidate generator site and the terrain complexity level corresponding to each candidate generator site, including: The design parameters of the wind turbines at each of the candidate machine sites are designed according to the complexity level of the terrain corresponding to the sector where the main wind direction corresponding to each of the candidate machine sites is located, the complexity level of the terrain corresponding to the first sector corresponding to each of the candidate machine sites, and the complexity level of the terrain corresponding to the second sector.

[0011] According to a method for determining design parameters of a wind turbine generator set based on complex terrain conditions provided by the present invention, the wind turbine generator set design parameters of each candidate generator set site are designed according to the time series data of wind condition parameters of different sectors corresponding to each candidate generator set site and the terrain complexity level corresponding to each candidate generator set site, including: According to the terrain complexity level corresponding to each candidate station site, the terrain complexity level corresponding to the first sector corresponding to each candidate station site, and the terrain complexity level corresponding to the second sector, the wind condition parameter time series data of different sectors corresponding to each candidate station site are finely classified to obtain a fine classification result of the wind condition parameters corresponding to each candidate station site; The refined classification results of the wind condition parameters corresponding to each of the candidate machine locations at least include parameter metrics of the sectors where the main wind direction corresponding to each of the candidate machine locations is located, the first sectors, and the second sectors in different time periods, and the parameter metrics are used to characterize: the target time period in which the probability of occurrence of meteorological parameters meets the preset conditions and the threshold value of the meteorological parameters corresponding to the target time period; Based on the refined classification results of the wind condition parameters corresponding to each of the candidate machine sites, the design parameters of the wind turbines at each of the candidate machine sites are adaptively designed to form a key wind resource parameter threshold table.

[0012] According to a method for determining design parameters of a wind turbine generator system based on complex terrain conditions provided by the present invention, the method further includes: Using the sample meteorological parameters of each candidate machine site, the terrain complexity level of each candidate machine site, and the label data of each candidate machine site, the initial deep learning network is trained to obtain a refined wind turbine design parameter determination model; The refined wind turbine design parameter determination model is used to determine the wind turbine design parameter values ​​at the target machine site.

[0013] In a second aspect, the present invention further provides a device for determining design parameters of a wind turbine generator system based on complex terrain conditions, comprising the following modules: A unit division module is used to determine at least two candidate unit locations according to the incoming flow direction of the wind farm and a preliminary unit arrangement plan; the preliminary unit arrangement plan is used to characterize the unit location arrangement positions of the wind turbine units in the wind farm plant area; Design a parameter determination model, for any of the candidate station locations, determine the time series data of wind condition parameters of different sectors corresponding to the candidate station location according to the meteorological parameters of the candidate station location and a preset number of sectors included in the candidate station location; Determine the terrain complexity level corresponding to the candidate station 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 station 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, and extremely complex; The design parameters of the wind turbine generator set at each candidate generator site are designed according to the time series data of wind condition parameters of different sectors corresponding to each candidate generator site and the terrain complexity level corresponding to each candidate generator site.

[0014] In a third aspect, the present invention further provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein 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.

[0015] In a fourth aspect, the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the above-described methods for determining design parameters of a wind turbine generator system based on complex terrain conditions.

[0016] In a fifth aspect, the present invention further provides a computer program product, comprising a computer program, which, when executed by a processor, implements any of the above-described methods for determining design parameters of a wind turbine generator system based on complex terrain conditions.

[0017] The method and device for determining design parameters of a wind turbine generator set based on complex terrain conditions provided by the present invention first determine at least two candidate generator sites according to the incoming flow direction of the wind farm and the preliminary generator set arrangement plan, wherein the preliminary generator set arrangement plan is used to characterize the generator site arrangement positions of the wind turbine generator sets in the wind farm plant area; then, for any candidate generator site, according to the meteorological parameters of the candidate generator site and a preset number of sectors included in the candidate generator site, determine the time series data of wind condition parameters of different sectors corresponding to the candidate generator site, and determine the terrain complexity level corresponding to the candidate generator site, wherein 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 generator 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, and extremely complex; further, the design parameters of the wind turbine generator set of each candidate generator site can be designed according to the time series data of wind condition parameters of different sectors corresponding to each candidate generator site and the terrain complexity level corresponding to each candidate generator site.

[0018] In the present invention, measured data (meteorological parameters) and terrain data (terrain complexity under complex terrain conditions) are creatively combined, and the comprehensive influence of complex terrain on wind condition parameter components is taken into account. Furthermore, the design parameters of the wind turbine set at each candidate machine site are designed 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, thereby improving the accuracy of determining the design parameters of the wind turbine set. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0020] Figure 1 This is one of the flow charts of the method for determining design parameters of a wind turbine generator set based on complex terrain conditions provided by the present invention.

[0021] Figure 2 It is a schematic diagram of dividing a horizontal plane circle with a target machine position point as the center into sectors provided by the present invention.

[0022] Figure 3 It is a schematic diagram of dividing a horizontal plane circle with a target machine position point as the center into sectors provided by the present invention.

[0023] Figure 4 It is a schematic diagram of the corresponding relationship between the radius of the reference point and the altitude provided by an embodiment of the present invention.

[0024] Figure 5This is the second flow chart of the method for determining design parameters of a wind turbine generator set based on complex terrain conditions provided by the present invention.

[0025] Figure 6 It is a structural schematic diagram of a device for determining design parameters of a wind turbine generator set based on complex terrain conditions provided by the present invention.

[0026] Figure 7 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0027] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0028] Wind turbines are often located in complex and changeable 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 wind, which in turn fluctuates the output power of wind turbines. In an unstable atmosphere, vertical wind shear intensifies, increasing the dynamic load on the unit and increasing the risk of fatigue damage. High shear wind speeds, especially in valleys, hills and other terrains, test the response and control capabilities of the unit, and may also trigger protective shutdowns and reduce power generation efficiency. The complexity of the terrain further complicates wind speed prediction, requiring detailed research on the wind resource conditions of the wind farm for wind farm layout and unit selection.

[0029] At present, the design input parameters of wind turbines are derived from the results of wind resource calculations, and the mainstream wind resource assessment method mainly relies on the erection of wind measurement towers and other wind measurement equipment in the wind farm site area. The wind resource parameter data of each machine site is obtained through wind measurement data analysis and CFD flow field simulation calculations. Finally, the calculation results of the wind resource parameter data are taken as envelope values ​​for the design calculation of wind turbines. The results obtained by this wind resource assessment method have the following shortcomings: 1) The number of wind towers in wind farms under complex terrain is often small, which makes the results of flow field simulation software inaccurate, resulting in large differences in resource conditions under complex terrain. The lack of resource data for complex terrain makes the designed wind turbine parameters unable to apply to power plants in complex terrain; 2) When designing the unit, the envelope value of the calculation results of wind resource parameter data is used to design the wind turbine, which often makes the calculation results conservative and increases the cost of the unit; 3) When the unit is operating in complex terrain, facing high turbulence and high shear, the sector management strategy is often adopted, that is, the unit is shut down in the sector and other non-power generation situations are not generated, resulting in additional losses in the unit's power generation, affecting economic benefits.

[0030] Based on the above problems, the present invention proposes a method for determining design parameters of wind turbines based on complex terrain conditions. First, an environmental evaluation model is used to screen at least one candidate machine site, and machine sites with higher environmental evaluation levels are quickly filtered out, reducing the amount of data calculation. Then, the remaining machine sites with lower environmental levels are refined and divided, which increases the diversity, comprehensiveness and accuracy of terrain resource data, improves the subsequent power generation efficiency, and is beneficial to improving the accuracy and applicability of wind turbine design parameters in complex terrain wind farms. In addition, it is also beneficial to guide wind farm development, site optimization and safe operation.

[0031] Combine the following Figure 1-Figure 5 The present invention describes a method for determining design parameters of a wind turbine based on complex terrain conditions. The method for determining design parameters of a wind turbine based on complex terrain conditions provided by the present invention is applicable to the site selection of any wind farm and the input parameter design of a wind turbine. The execution subject of the method can be an electronic device, or a device for determining design parameters of a wind turbine based on complex terrain conditions arranged in the electronic device. The device for determining design parameters of a wind turbine based on complex terrain conditions can be implemented by software, hardware, or a combination of both.

[0032] Figure 1 This is one of the flow charts of the method for determining the design parameters of a wind turbine generator system based on complex terrain conditions provided by the present invention. Figure 1 As shown, the method includes the following: Step 101: Determine at least two candidate generator sites according to the wind farm's incoming flow direction and a preliminary generator arrangement plan; the preliminary generator arrangement plan is used to characterize the generator site arrangement positions of the wind turbine generators in the wind farm plant area; Specifically, it should be noted that the execution subject of this embodiment is an electronic device, which is used to determine the design parameters of the wind turbine generator system based on complex terrain conditions.

[0033] It should be noted that the candidate machine site can be understood as a representative machine site. In the early stage of wind farm development, technicians will design a preliminary unit layout plan. According to the wind direction of the wind farm and the preliminary unit layout plan, the entire plant area will be divided into different areas, and a representative machine site will be determined in each area. For example, the entire plant area can be divided into 3 to 5 areas, and a representative machine site can be selected in each area.

[0034] Exemplarily, the method for determining the representative machine point may be to determine the altitude of each machine point according to the elevation map information and the position coordinates of the machine point, and determine the altitude of each machine point at the east, west, south and north of each machine point with each machine point as the center and a preset radius and perform statistics; subtract the altitudes of the four points due east, west, south and north from the altitude of the machine point, respectively, to obtain the elevation difference as a screening variable, and take the machine point in each area with an elevation difference of less than or equal to 10m and located in the incoming flow direction as the representative machine point (i.e., the candidate machine point).

[0035] Step 102: for any candidate station site, according to the meteorological parameters of the candidate station site and a preset number of sectors included in the candidate station site, determine the time series data of wind condition parameters of different sectors corresponding to the candidate station site; After the candidate machine sites are selected, the basic wind resource parameters of the candidate machine sites, that is, the time series data of the wind condition parameters of the candidate machine sites, can be calculated for each candidate machine site.

[0036] For example, Step 1, apply conventional resource analysis methods to process the meteorological data collected at the site, and bring it into commercial flow field simulation software to calculate the time series data of wind condition parameters at representative machine sites. The wind condition parameters need to include: turbulence intensity, wind direction at two altitude layers, and wind shear; Step 2: Process and analyze the time series data of wind parameters at the representative station. In particular, classify by sectors. For example, according to the meteorological parameters of the candidate station and the preset number of sectors included in the candidate station, determine the time series data of wind parameters of different sectors corresponding to the candidate station. The division of sectors is as follows: With the representative station location as the center of the circle and due north as 0°, the station location is divided into 12 sectors. The angle of each sector is 30 degrees, and they are 50m, 100m, 150m, 200m, 250m...2000m respectively.

[0037] Step 103, determining the terrain complexity level corresponding to the candidate station 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 station site is located, and the terrain complexity level includes any of the following from low to high: generally complex, relatively complex, medium complex, complex, and extremely complex; Specifically, in the present invention, the time series data of wind condition parameters of each candidate station site can be further divided in combination with the terrain conditions of each candidate station site.

[0038] First, the terrain conditions of each candidate station site need to be determined, wherein the terrain conditions may be terrain complexity, and the terrain complexity may include: terrain slope angle and the level corresponding to the terrain slope angle. In particular, it may be the complexity of the terrain corresponding to the sector where the main wind direction of the candidate station site is located.

[0039] Step 104: design the wind turbine design parameters of each candidate generator site according to the time series data of wind condition parameters of different sectors corresponding to each candidate generator site and the terrain complexity level corresponding to each candidate generator site.

[0040] After determining the terrain complexity level corresponding to each candidate machine site, the time series numbers of wind condition parameters in different sectors corresponding to each candidate machine site can be further refined based on the terrain complexity level corresponding to the candidate machine site to obtain refined classification results. Therefore, during the design stage of the unit and the safety verification and adaptability analysis of the site, refined design can be carried out according to the refined classification results.

[0041] Specifically, the refined resource assessment is carried out based on the results of the fine classification of wind parameters corresponding to the candidate machine sites and the terrain slope. The classification level mainly considers the following steps: Step 1: Based on the classification results of terrain complexity level, the results of the main wind direction sector and the adjacent ±30° sectors of the candidate station site are summarized as shown in Table 1 below: Table 1:

[0042] Step 2: Based on the comprehensive summary results of representative machine sites in step 1, during the design stage of the unit and the safety verification 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 take targeted strategies in specific sectors. The key wind resource parameter threshold table is shown in Table 2 below: Table 2:

[0043] The method provided in this embodiment first determines at least two candidate machine sites according to the incoming flow direction of the wind farm and the preliminary machine unit arrangement plan, wherein the preliminary machine unit arrangement plan is used to characterize the machine site arrangement position of the wind turbine units in the wind farm plant area; then, for any 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, the time series data of wind condition parameters of different sectors corresponding to the candidate machine site is determined, and the terrain complexity level corresponding to the candidate machine site is determined, wherein 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, and the terrain complexity level includes any one of the following from low to high: generally complex, relatively complex, moderately complex, complex, and extremely complex; further, the design parameters of the wind turbine units at each candidate machine site can be designed according to the time series data of wind condition parameters of different sectors corresponding to each candidate machine site and the terrain complexity level corresponding to each candidate machine site.

[0044] In the present invention, measured data (meteorological parameters) and terrain data (terrain complexity under complex terrain conditions) are creatively combined, and the comprehensive influence of complex terrain on wind condition parameter components is taken into account. Furthermore, the design parameters of the wind turbine set at each candidate machine site are designed 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, thereby improving the accuracy of determining the design parameters of the wind turbine set.

[0045] According to a method for determining design parameters of a wind turbine generator set based on complex terrain conditions provided by the present invention, according to the meteorological parameters of the candidate generator site and a preset number of sectors included in the candidate generator site, the time series data of wind condition parameters of different sectors corresponding to the candidate generator site are determined, including: Determine the time series data of wind condition parameters at the candidate aircraft site according to the meteorological parameters at the candidate aircraft site; According to a preset number of sectors, the wind condition parameter time series data of each candidate station site is sector-classified to obtain the wind condition parameter time series data of different sectors corresponding to the candidate station site.

[0046] Specifically, in some embodiments, step 102 may be implemented by the following steps, including: First, according to the meteorological parameters of the candidate machine site, the time series data of the wind condition parameters of the candidate machine site is determined. Among them, the meteorological parameters are obtained by actually monitoring the meteorological conditions at the plant site 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 layers, and wind shear. It should be noted that the meteorological parameters may change with time, so the meteorological parameters of the candidate machine site can be input into the commercial flow field simulation software according to the corresponding time point, and the time series data of the wind condition parameters of the candidate machine site can be obtained.

[0047] Furthermore, after obtaining the wind condition parameter time series data of the candidate machine site, the wind condition parameter time series data of each candidate machine site can be further classified by sector according to a preset number of sectors contained in the candidate machine site to obtain the wind condition parameter time series data of different sectors corresponding to the candidate machine site.

[0048] The method provided in this embodiment determines the time series data of wind condition parameters of the candidate machine site based on the meteorological parameters of the candidate machine site, and then classifies the time series data of wind condition parameters of each candidate machine site according to a preset number of sectors to obtain the time series data of wind condition parameters of different sectors corresponding to the candidate machine site. The obtained time series data of wind condition parameters has a high degree of refinement.

[0049] According to a method for determining design parameters of a wind turbine generator set based on complex terrain conditions provided by the present invention, the preset number of sectors is obtained by dividing a horizontal circle with the candidate generator site as the center; the wind condition parameter time series data includes turbulence intensity, wind direction deflection rate and wind shear; According to a preset number of sectors, the wind condition parameter time series data of each candidate station site is sector-classified to obtain the wind condition parameter time series data of different sectors corresponding to the candidate station site, including: For any candidate machine point, based on the turbulence intensity corresponding to each sector in the candidate machine point, determine a first metric standard set corresponding to each sector in different time periods; the first metric standard set includes at least one of the following: the probability of occurrence of turbulence intensity in the time period, the average turbulence intensity, and the standard deviation of the average turbulence intensity; Counting the probability of occurrence of turbulence intensity in a time period, the average turbulence intensity and the average turbulence intensity standard deviation in the same time period, all of which meet the first preset threshold values ​​corresponding to each other; Based on the wind direction deflection rate corresponding to each sector, determine a second metric standard set corresponding to each sector in different time periods; the second metric standard set includes at least one of the following: the probability of occurrence of 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 probability of occurrence of wind direction deflection rate in the same time period, the average wind direction deflection rate and the standard deviation of the average wind direction deflection rate, all of which meet the second metric standard set corresponding to the second preset threshold value; Based on the vertical wind shear of each sector, determine a third metric standard set corresponding to each sector in different time periods; the third metric standard set includes at least one of the following: the probability of vertical wind shear occurrence in the time period, the average vertical wind shear, and the standard deviation of the average vertical wind shear; Counting the probability of vertical wind shear occurrence, average vertical wind shear, and average vertical wind shear standard deviation in the same time period, all of which satisfy the third metric standard set corresponding to the third preset threshold; Based on a first set of metric standards that all satisfy their respective first preset thresholds, a second set of metric standards that all satisfy their respective second preset thresholds, and a third set of metric standards that all satisfy their respective third preset thresholds, the wind condition parameter time series data of different sectors corresponding to the candidate machine site are determined.

[0050] Specifically, in some embodiments, the preset number of sectors in the candidate station site is obtained by dividing a horizontal circle with the candidate station site as the center. Here, the number of sectors can be any appropriate number, such as 12 sectors or 8 sectors.

[0051] The wind condition parameter time series data in this embodiment includes turbulence intensity, wind direction deflection rate and wind shear. Here, turbulence intensity describes the degree to which wind speed changes over time and space. It reflects the relative intensity of pulsating wind speed and is the most important characteristic quantity to describe the motion characteristics of atmospheric turbulence. Here, wind direction deflection rate refers to the degree or rate at which the direction of wind deflects during its flow due to the influence of factors such as the Coriolis force. Here, vertical wind shear characterizes the change of the wind speed vector in the vertical direction.

[0052] Correspondingly, in this embodiment, according to a preset number of sectors, the wind condition parameter time series data of each candidate station site is sector-classified to obtain the wind condition parameter time series data of different sectors corresponding to the candidate station site, and the implementation process includes the following steps: Step 1: For any candidate machine site, based on the turbulence intensity corresponding to each sector in the candidate machine site, determine the first metric standard set corresponding to each sector in different time periods; the first metric standard set includes at least one of the following: the probability of occurrence of turbulence intensity in the time period, the average turbulence intensity, and the standard deviation of the average turbulence intensity; the first metric standard set in which the probability of occurrence of turbulence intensity in the time period, the average turbulence intensity, and the standard deviation of the average turbulence intensity in the same time period all meet the first preset threshold value corresponding to each other. Specifically, based on the turbulence intensity corresponding to each sector, determine the first metric standard set corresponding to each sector in different time periods; the first metric standard set includes at least one of the following: the probability of occurrence of turbulence intensity in the time period, the average turbulence intensity, and the standard deviation of the average turbulence intensity.

[0053] For example, 24 hours a day is divided into 12 time periods, such as 0:00-2:00, 2:00-4:00...22:00 to 24:00, and the horizontal circle with the target machine position as the center is evenly divided into 12 sectors, 0 degrees-30 degrees, 30 degrees-60 degrees...330 degrees-360 degrees. Specifically, each time period corresponds to 12 sectors, so each time period corresponds to the first metric standard set of 12 sectors.

[0054] The mean turbulence intensity standard deviation is used to describe the relative strength of wind speed fluctuations and their dispersion. The mean turbulence intensity standard deviation is calculated based on the mean turbulence intensity.

[0055] The first metric standard set is calculated to determine whether the probability of occurrence of time period turbulence intensity, the average turbulence intensity and the average turbulence intensity standard deviation in the same time period all meet the first preset threshold values ​​corresponding to each other.

[0056] Here, the first preset threshold value may be any appropriate value, wherein the first preset threshold values ​​corresponding to the probability of occurrence of turbulence intensity in a time period, the average turbulence intensity and the standard deviation of the average turbulence intensity may be the same or different.

[0057] Step 2. Based on the wind direction deflection rate corresponding to each sector, determine the second metric standard set corresponding to each sector in different time periods; the second metric standard set includes at least one of the following: the probability of occurrence of wind direction deflection rate in a time period, the average wind direction deflection rate, and the standard deviation of the average wind direction deflection rate; and the second metric standard set in which the probability of occurrence of wind direction deflection rate in a time period, the average wind direction deflection rate, and the standard deviation of the average wind direction deflection rate in the same time period all meet their respective corresponding second preset thresholds.

[0058] Specifically, here, the probability of wind direction deflection rate in a time period refers to the probability of a significant deflection of wind direction in a specific time period, for example, the ratio of the number of significant deflections occurring in this time period in a year to the total number of significant deflections occurring in a year.

[0059] The mean wind direction deflection rate standard deviation is used to measure the dispersion of wind direction deflection rate data. The mean wind direction deflection rate standard deviation is calculated based on the mean wind direction deflection rate.

[0060] It should be noted that the wind direction deflection rate is the difference between wind direction data at two different altitudes. Since the wind direction data at low altitudes is greatly affected by topography and landforms, when analyzing the wind direction deflection rate by sector, the sector division is based on the wind direction data at the altitude.

[0061] Counting the probability of occurrence of wind direction deflection rate in the same time period, the average wind direction deflection rate and the standard deviation of the average wind direction deflection rate, all of which meet the second metric standard set corresponding to the second preset threshold value; Here, the second preset threshold may be any appropriate value, wherein the second preset thresholds corresponding to the probability of occurrence of wind direction deflection rate in a time period, the average wind direction deflection rate and the standard deviation of the average wind direction deflection rate may be the same or different.

[0062] Step 3. Based on the vertical wind shear of each sector, determine the third metric standard set corresponding to each sector in different time periods; the third metric standard set includes at least one of the following: the probability of vertical wind shear in the time period, the average vertical wind shear, and the standard deviation of the average vertical wind shear; and the third metric standard set in which the probability of vertical wind shear in the time period, the average vertical wind shear, and the standard deviation of the average vertical wind shear in the same time period all meet their respective corresponding third preset thresholds.

[0063] Specifically, here, the probability of vertical wind shear occurrence in a time period refers to the possibility or frequency of vertical wind shear (i.e., the change in wind direction and / or wind speed over a vertical distance) occurring in a specific time period. For example, the proportion of the number of vertical wind shear occurrences in this time period in a year to the total number of vertical wind shear occurrences in a year.

[0064] The mean vertical wind shear standard deviation is used to measure the dispersion of vertical wind shear data. The mean vertical wind shear standard deviation can be calculated based on the mean vertical wind shear.

[0065] Counting the probability of vertical wind shear occurrence, average vertical wind shear, and average vertical wind shear standard deviation in the same time period, all of which satisfy the third metric standard set corresponding to the third preset threshold; Here, the third preset threshold may be any appropriate value, wherein the third preset thresholds corresponding to the probability of vertical wind shear occurrence in a time period, the average vertical wind shear, and the average vertical wind shear standard deviation may be the same or different.

[0066] Step 4: Determine the time series data of wind condition parameters of different sectors corresponding to the candidate machine site based on a first set of metric standards that all meet their respective first preset thresholds, a second set of metric standards that all meet their respective second preset thresholds, and a third set of metric standards that all meet their respective third preset thresholds.

[0067] In the method provided by the embodiment of the present invention, three meteorological parameters and multiple metrics of vertical wind shear are used to finely divide meteorological data, thereby improving the accuracy, diversity and reliability of the data; and, by referring to actual values, the refined calculation and verification of the sectors are directly applied to the design stage of the wind turbine generator set, ensuring the performance optimization and structural safety of the unit under complex terrain conditions, and significantly improving the pertinence and adaptability of the unit design. In addition, targeted strategies can be adopted in specific sectors to ensure the normal operation of wind turbine resistors and avoid economic losses caused by downtime.

[0068] According to a method for determining design parameters of a wind turbine generator set based on complex terrain conditions provided by the present invention, the method further includes: Based on the wind speed standard deviation corresponding to each sector and the average wind speed corresponding to each sector, the turbulence intensity corresponding to each sector in different time periods is determined; 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 wind direction deflection rate of each sector in different time periods is determined; the first height is the height of the hub of the wind turbine at the candidate machine site, and the first height is higher than the second height; 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, the vertical wind shear of each sector in different time periods is determined.

[0069] Specifically, in some embodiments, the method further includes: Based on the wind speed standard deviation corresponding to each sector and the average wind speed corresponding to each sector, the turbulence intensity corresponding to each sector in different time periods is determined. Here, the turbulence intensity can be a first ratio, wherein the first ratio can be a ratio of the wind speed standard deviation to the average wind speed, or a weighted ratio of the wind speed standard deviation to the average wind speed.

[0070] For example, the turbulence intensity is calculated as follows: (1)

[0071] in, For the The turbulence intensity of the sector is For the The standard deviation of wind speed in a sector is is the average wind speed.

[0072] 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 wind direction deflection rate of each sector in different time periods is determined; the first height is the hub height of the wind turbine at the target machine site, and the first height is higher than the second height. The difference between the first height and the second height can be any appropriate value, such as 10 meters (m), 9 meters, etc.

[0073] Here, the wind direction deflection rate can be a second ratio, wherein the second ratio can be a ratio of the first difference to the wind direction data at the second height, or a weighted ratio of the first difference to the wind direction data at the second height, and 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 a weighted difference between the wind direction data at the first height and the wind direction data at the second height.

[0074] For example, the wind direction deflection rate is calculated as follows: (2)

[0075] in, is the wind direction data at the hub height of the wind turbine in the meteorological data. It is the wind direction data corresponding to the lower altitude layer in the meteorological data.

[0076] 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, the vertical wind shear of each sector in different time periods is determined.

[0077] Here, the vertical wind shear can be the third ratio, the third ratio can be the ratio of the first logarithm to the second logarithm, or the ratio of the weighted number of the first logarithm to the weighted number of the second logarithm. The first logarithm can be the logarithm of the ratio of the wind speed corresponding to the third height to the wind speed corresponding to the fourth height, or the logarithm of the ratio of the weighted number of the wind speed corresponding to the third height to the weighted number of 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 the weighted number of the third height to the weighted number of the fourth height.

[0078] For example, the wind direction deflection rate is calculated as follows: (3)

[0079] in: is the wind shear index, is the third height, The fourth height, For the corresponding height The wind speed, Corresponding height The wind speed, is the logarithmic sign.

[0080] The method provided in this embodiment uses a variety of wind measurement data, such as wind speed, wind direction, altitude, etc. to calculate meteorological parameters such as turbulence intensity, wind direction deflection rate and vertical wind shear, thereby improving the accuracy, diversity and reliability of wind resource data.

[0081] According to a method for determining design parameters of a wind turbine generator set based on complex terrain conditions provided by the present invention, determining the terrain complexity level corresponding to a candidate generator site includes: Based on a preset number of sectors included in the candidate station site, determine the sector where the main wind direction of the candidate station site is located; Based on the horizontal distance between at least one reference point and the candidate station location and the altitude corresponding to the horizontal distance, determine the functional relationship between the radius of a horizontal plane circle with the candidate station 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; 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 mapping relationship between the preset terrain slope angle and the complexity of the terrain corresponding to the sector, the terrain complexity level corresponding to the candidate machine site is determined.

[0082] Specifically, in some embodiments, the process of determining the terrain complexity level corresponding to the candidate machine site in step 103 may include the following steps: First, based on the preset number of sectors included in the candidate station site, the sector where the main wind direction of the candidate station site is located is determined. Here, the number of sectors can be any appropriate number, such as 12, 8, etc. The main wind direction is also called the dominant wind direction, which refers to the range of wind direction angles with the largest wind frequency. By collecting and analyzing historical meteorological parameters, the main wind direction of the target station site can be determined.

[0083] Furthermore, based on the horizontal distance between at least one reference point and the candidate machine site and the altitude corresponding to the horizontal distance, a functional relationship between the radius of a horizontal plane circle with the candidate machine site as the center and the altitude corresponding to the radius is determined; each reference point is a point within the sector where the main wind direction is located.

[0084] Here, the reference point is a point randomly selected in the sector where the main wind direction is located. By fitting the mapping relationship between the horizontal distances from multiple reference points to the target aircraft site and the altitude corresponding to the horizontal distance, the functional relationship between the horizontal distance and the altitude is obtained.

[0085] For example, Figure 2 Schematic diagram of the present invention providing a horizontal circle with the target machine position as the center dividing the sectors, such as Figure 2As shown, each 30 degrees is divided into a sector, with 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.

[0086] Figure 3 Schematic diagram of the present invention providing a horizontal circle with the target machine position as the center dividing the sectors, such as Figure 3 As shown, θ is the terrain slope angle corresponding to the sector, and concentric circles of different radii are located at different altitudes.

[0087] Figure 4 It is a schematic diagram of the corresponding relationship between the radius of the reference point and the altitude provided by the present invention, such as Figure 4 As 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 (4): (4)

[0088] in, Indicates 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 point in is -0.2291, It is 645.96.

[0089] Furthermore, the terrain slope angle of the sector where the main wind direction is located can be determined based on the coefficients of the functional relationship.

[0090] Here, the terrain slope angle may be a fourth ratio, the fourth ratio may be a ratio of 1 to a trigonometric function, or a ratio of 1 to a weight of a trigonometric function, the trigonometric function may be .

[0091] For example, the terrain slope angle is calculated as follows: (5)

[0092] in, Terrain slope angle, represents the reciprocal of trigonometric functions, It indicates the altitude corresponding to a radius of 2000. It can be understood that, combined with (4), formula (6) can be obtained: (6)

[0093] Furthermore, based on a mapping relationship between a preset terrain slope angle and the complexity of the terrain corresponding to the sector, a terrain complexity level corresponding to the candidate machine site is determined.

[0094] Here, the complexity of the terrain is used to characterize the level of the terrain slope angle, and 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 medium 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.

[0095] The method provided in this embodiment can improve the accuracy of determining wind turbine parameters by determining the sector where the main wind direction is located and the level of the sector where the main wind direction is located, the terrain complexity, etc., and then finely dividing the wind resource parameters based on the terrain complexity.

[0096] According to a method for determining design parameters of a wind turbine generator set based on complex terrain conditions provided by the present invention, the method further includes: Determine a sector where the main wind direction of the candidate station site is located, and a first sector and a second sector respectively adjacent to the sector where the main wind direction of the candidate station site is located; Determine respectively the terrain complexity level corresponding to the sector where the main wind direction of the candidate machine site is located, the terrain complexity level corresponding to the first sector, and the terrain complexity level corresponding to the second sector; According to the wind condition parameter time series data of different sectors corresponding to each candidate machine site and the terrain complexity level corresponding to each candidate machine site, the design parameters of the wind turbine at each candidate machine site are designed, including: The design parameters of the wind turbines at each candidate machine site are designed according to the complexity level of the terrain corresponding to the sector where the main wind direction corresponding to each candidate machine site is located, the complexity level of the terrain corresponding to the first sector corresponding to each candidate machine site, and the complexity level of the terrain corresponding to the second sector.

[0097] Specifically, in some embodiments, the method further includes: First, determine the sector where the main wind direction of the candidate station site is located, and the first sector and the second sector adjacent to the sector where the main wind direction of the candidate station site is located. Here, the first sector and the second sector are respectively the right sector and the left sector adjacent to the sector where the main wind direction is located. For example, if the sector where the main wind direction is located is 60-90 degrees, the first sector is 30-60 degrees, and the second sector is 90-120 degrees.

[0098] Furthermore, the complexity level of the terrain corresponding to the sector where the main wind direction of the candidate machine site is located, the complexity level of the terrain corresponding to the first sector, and the complexity level of the terrain corresponding to the second sector are determined respectively. For example, the second level corresponding to the first sector and the third level corresponding to the second sector are determined respectively; the second level is used to characterize the complexity of the terrain corresponding to the first sector, and the third level is used to characterize the complexity of the terrain corresponding to the second sector.

[0099] 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 repeated here.

[0100] Correspondingly, the process of designing the design parameters of the wind turbines at each candidate station location according to the time series data of wind condition parameters of different sectors corresponding to each candidate station location and the terrain complexity level corresponding to each candidate station location can be implemented by the following steps, including: 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, the design parameters of the wind turbine at each candidate machine site are designed.

[0101] The method provided in this embodiment expands the scope of the sectors where the main wind direction may be located by determining 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, thereby avoiding the problem of inaccurate data when the main wind direction deviates. In addition, by referring to the actual values ​​for the refined load calculation and verification of the sectors, it is directly applied to the design stage of the wind turbine generator set, ensuring the performance optimization and structural safety of the unit under complex terrain conditions, and significantly improving the pertinence and adaptability of the unit design. In addition, targeted strategies can be adopted in specific sectors to ensure the normal operation of wind turbine resistors and avoid economic losses caused by downtime.

[0102] According to a method for determining design parameters of a wind turbine generator set based on complex terrain conditions provided by the present invention, design parameters of a wind turbine generator set at each candidate generator site are designed according to time series data of wind condition parameters of different sectors corresponding to each candidate generator site and the terrain complexity level corresponding to each candidate generator site, including: According to the terrain complexity level corresponding to each candidate station site, the terrain complexity level corresponding to the first sector corresponding to each candidate station site, and the terrain complexity level corresponding to the second sector, the wind condition parameter time series data of different sectors corresponding to each candidate station site are finely classified to obtain the wind condition parameter fine classification results corresponding to each candidate station site; The refined classification results of wind condition parameters corresponding to each candidate station location at least include parameter metrics of the sectors where the main wind direction is located, the first sector and the second sector corresponding to each candidate station location in different time periods. The parameter metrics are used to characterize: the target time period in which the probability of occurrence of meteorological parameters meets the preset conditions and the threshold value of the meteorological parameters corresponding to the target time period; Based on the refined classification results of wind condition parameters corresponding to each candidate machine site, the design parameters of wind turbines at each candidate machine site are adaptively designed to form a threshold table of key wind resource parameters.

[0103] Specifically, in some embodiments, the implementation process of designing the design parameters of the wind turbines at each candidate station site according to the time series data of the wind condition parameters of different sectors corresponding to each candidate station site and the terrain complexity level corresponding to each candidate station site in step 104 can be implemented by the following steps, including: First, 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, the time series data of wind condition parameters of different sectors corresponding to each candidate machine site are finely classified to obtain the refined classification results of wind condition parameters corresponding to each candidate machine site. Among them, the refined classification results of wind condition parameters corresponding to each candidate machine site include at least the parameter metrics of the sectors where the main wind direction of each candidate machine site is located, the first sector, and the second sector in different time periods. The parameter metrics are used to characterize: the target time period in which the probability of occurrence of meteorological parameters meets the preset conditions and the threshold value of meteorological parameters corresponding to the target time period. For example, the following table 1: Table 1:

[0104] Furthermore, based on the refined classification results of the wind condition parameters corresponding to each candidate machine site, the design parameters of the wind turbines at each candidate machine site can be adaptively designed to form a key wind resource parameter threshold table. The key wind resource parameter threshold table is shown in Table 2 below: Table 2:

[0105] The method provided in this embodiment firstly performs fine classification on the time series data of wind condition parameters of different sectors corresponding to 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, so as to obtain the fine classification results of wind condition parameters corresponding to each candidate machine site, wherein the fine classification results of wind condition parameters corresponding to each candidate machine site at least include the parameter metrics 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, and the parameter metrics are used to characterize: the target time period in which the probability of occurrence of meteorological parameters meets the preset conditions and the threshold value of meteorological parameters corresponding to the target time period; then, based on the fine classification results of wind condition parameters corresponding to each candidate machine site, the design parameters of wind turbines at each candidate machine site are adaptively designed to form a threshold table of key wind resource parameters.

[0106] The present invention creatively combines measured data (meteorological parameters) and terrain data (terrain complexity under complex terrain conditions), taking into account the comprehensive impact of complex terrain on wind condition parameter components, and then designs the design parameters of the wind turbine group at each candidate machine site based on the wind condition parameter time series data of different sectors corresponding to each candidate machine site and the terrain complexity level corresponding to each candidate machine site, thereby improving the accuracy of determining the design parameters of the wind turbine group.

[0107] According to a method for determining design parameters of a wind turbine generator set based on complex terrain conditions provided by the present invention, the method further includes: The initial deep learning network is trained using the sample meteorological parameters of each candidate generator site, the terrain complexity level of each candidate generator site, and the label data of each candidate generator site to obtain a refined wind turbine design parameter determination model; The refined wind turbine design parameter determination model is used to determine the wind turbine design parameter values ​​at the target machine site.

[0108] Specifically, in some embodiments, the method further includes: The sample meteorological parameters of each candidate machine site, the terrain complexity level of each candidate machine site, and the label data of each candidate machine site are used to train the initial deep learning network to obtain a refined wind turbine design parameter determination model. Among them, deep learning networks are a type of artificial neural network composed of multiple layers, which can learn multi-level representation and abstraction of data. The process of training to obtain a refined wind turbine design parameter determination model is as follows: First, the sample meteorological parameters of each candidate station and the terrain complexity level of each candidate station are used as sample data, and the label data of each candidate station is used as the label corresponding to the sample data, and are input into the initial deep learning network together; After the preset number of iterations is met, the model parameters at the time of iteration termination are determined as the model parameters of the refined wind turbine design parameter determination model, thereby completing the deep learning model training.

[0109] Furthermore, the refined wind turbine design parameter determination model can be used to determine the wind turbine design parameter values ​​of the target machine site, and the wind turbine design parameter determination model after training can be used to determine the wind turbine design parameter values ​​of the target machine site with high accuracy.

[0110] In this embodiment, the sample meteorological parameters of each candidate machine site, the terrain complexity level of each candidate machine site and the label data of each candidate machine site are first used to train the initial deep learning network to obtain a refined wind turbine design parameter determination model. Then, the refined wind turbine design parameter determination model is used to determine the wind turbine design parameter values ​​of the target machine site, thereby improving the accuracy of parameter determination.

[0111] Figure 5 FIG. 2 is a flow chart of a method for determining design parameters of a wind turbine generator system based on complex terrain conditions provided by the present invention. Figure 5 As shown, the specific steps include: Step 501: Select a target machine location in a wind farm.

[0112] The target machine point is a representative machine point. The method for selecting the target machine point can refer to the above method for determining the target machine point, which will not be described in detail here.

[0113] Step 502: Calculate the turbulence intensity at the target aircraft point and classify it into sectors.

[0114] Step 503: Calculate the wind direction deflection rate of the target aircraft position and classify it into sectors.

[0115] Step 504: Calculate the vertical wind shear at the target aircraft site and classify it into sectors.

[0116] Step 505: Calculate the terrain slope angle corresponding to the sector 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.

[0117] Step 506: Count the terrain complexity level corresponding to each sector.

[0118] Step 507: Refine resource data statistics.

[0119] Step 508: Perform security analysis on the adaptability of the target machine site.

[0120] The method for determining design parameters of a wind turbine based on complex terrain conditions provided by an embodiment of the present invention has the following advantages: Combined analysis of meteorological parameters and terrain parameters: Through 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 for the first time takes into account the comprehensive impact of complex terrain on meteorological parameters in the assessment method; refined design of sector load calculation: load calculation is performed based on different levels of complex terrain, wind resource parameters in each sector, and the time period of occurrence of each parameter variable. Refined load calculation and verification of each sector are performed by referring to actual values. This method is directly applied to the design stage of wind turbines, ensuring the performance optimization and structural safety of the unit under complex terrain conditions, and significantly improving the pertinence and adaptability of the unit design; targeted design parameter regulation for high turbulence and high shear sectors: in response to the problem that traditional wind turbines often use direct shutdown methods in high turbulence sectors, resulting in loss of power generation, it is proposed to use time series data to obtain the corresponding occurrence time of high turbulence and high shear, and bring the parameters of high turbulence and high sectors into the unit control strategy according to the design method of threshold time matrix table lookup, so as to achieve stable operation and efficient power generation of the unit in a high turbulence environment, and improve the economic benefits of the entire field.

[0121] The following is a description of the device for determining design parameters of a wind turbine based on complex terrain conditions provided by the present invention. The device for determining design parameters of a wind turbine based on complex terrain conditions described below and the method for determining design parameters of a wind turbine based on complex terrain conditions described above can refer to each other.

[0122] Figure 6 is a schematic diagram of the structure of the device for determining the design parameters of a wind turbine generator system based on complex terrain conditions provided by the present invention, referring to Figure 6 As shown, the wind turbine design parameter determination device 600 based on complex terrain conditions includes: a turbine division module 610, a design parameter determination model 602; wherein: The unit division module 610 is used to determine at least two candidate unit locations according to the incoming flow direction of the wind farm and the preliminary unit arrangement plan; the preliminary unit arrangement plan is used to characterize the location arrangement of the wind turbine units in the wind farm plant area; The design parameter determination module 620 determines, for any of the candidate station locations, time series data of wind condition parameters of different sectors corresponding to the candidate station location according to the meteorological parameters of the candidate station location and a preset number of sectors included in the candidate station location; Determine the terrain complexity level corresponding to the candidate station 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 station 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, and extremely complex; The design parameters of the wind turbine generator set at each candidate generator site are designed according to the time series data of wind condition parameters of different sectors corresponding to each candidate generator site and the terrain complexity level corresponding to each candidate generator site.

[0123] The device for determining design parameters of a wind turbine generator set based on complex terrain conditions provided by the present invention comprises: a unit division module 610 and a design parameter determination module 620. First, the unit division module 610 determines at least two candidate generator sites according to the incoming flow direction of the wind farm and the preliminary generator arrangement plan, wherein the preliminary generator arrangement plan is used to characterize the generator site arrangement position of the wind turbine generator set in the wind farm plant area; then, the design parameter determination module 620 determines, for any candidate generator site, the wind condition parameter time series data of different sectors corresponding to the candidate generator site according to the meteorological parameters of the candidate generator site and the preset number of sectors included in the candidate generator site, and determines the terrain complexity level corresponding to the candidate generator site, wherein 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 generator 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, and extremely complex; further, the wind turbine design parameters of each candidate generator site can be designed according to the wind condition parameter time series data of different sectors corresponding to each candidate generator site and the terrain complexity level corresponding to each candidate generator site.

[0124] In the present invention, measured data (meteorological parameters) and terrain data (terrain complexity under complex terrain conditions) are creatively combined, and the comprehensive influence of complex terrain on wind condition parameter components is taken into account. Furthermore, the design parameters of the wind turbine set at each candidate machine site are designed 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, thereby improving the accuracy of determining the design parameters of the wind turbine set.

[0125] 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 specifically used for: Determine the time series data of the wind condition parameters of the candidate station location according to the meteorological parameters of the candidate station location; According to the preset number of sectors, the wind condition parameter time series data of each candidate station location is sector-classified to obtain the wind condition parameter time series data of different sectors corresponding to the candidate station location.

[0126] 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 a horizontal circle with the candidate machine site as the center; the wind condition parameter time series data includes turbulence intensity, wind direction deflection rate and wind shear; The design parameter determination module 620 is further used to: For any of the candidate machine sites, based on the turbulence intensity corresponding to each of the sectors in the candidate machine site, determine a first metric standard set corresponding to each of the sectors in different time periods; the first metric standard set includes at least one of the following: the probability of occurrence of turbulence intensity in the time period, the average turbulence intensity, and the standard deviation of the average turbulence intensity; Counting the probability of occurrence of turbulence intensity in the time period, the average turbulence intensity and the standard deviation of the average turbulence intensity in the same time period, all of which meet the first metric standard set corresponding to the first preset threshold value; Based on the wind direction deflection rate corresponding to each of the sectors, determining a second metric standard set corresponding to each of the sectors in different time periods; the second metric standard set includes at least one of the following: the probability of occurrence 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 probability of occurrence 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 in the same time period, all of which meet the second metric standard set corresponding to the second preset threshold value; Based on the vertical wind shear of each of the sectors, determine a third metric standard set corresponding to each of the sectors in different time periods; the third metric standard set includes at least one of the following: the probability of occurrence of vertical wind shear in the time period, the average vertical wind shear, and the standard deviation of the average vertical wind shear; Counting the probability of vertical wind shear occurring in the time period, the average vertical wind shear, and the average vertical wind shear standard deviation in the same time period, all of which satisfy the third metric standard set corresponding to the third preset threshold value; Based on the first set of metric standards that all meet the corresponding first preset thresholds, the second set of metric standards that all meet the corresponding second preset thresholds, and the third set of metric standards that all meet the corresponding third preset thresholds, the wind condition parameter time series data of different sectors corresponding to the candidate machine site are determined.

[0127] 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 used for: Determining the turbulence intensity corresponding to each of the sectors in different time periods based on the wind speed standard deviation corresponding to each of the sectors and the average wind speed corresponding to each of the sectors; Based on the wind direction data at the first height corresponding to each of the sectors and the wind direction data at the second height corresponding to each of the sectors, the wind direction deflection rate of each of the sectors in different time periods is determined; the first height is the height of the hub of the wind turbine at the candidate machine site, and the first height is higher than the second height; Based on the wind speed at the third height corresponding to each of the sectors and the wind speed at the fourth height corresponding to each of the sectors, the vertical wind shear of each of the sectors in different time periods is determined.

[0128] According to the device 600 for determining design parameters of a wind turbine generator set based on complex terrain conditions provided by the present invention, the step of determining the terrain complexity level corresponding to the candidate generator site includes: Based on a preset number of sectors included in the candidate station site, determining a sector where the main wind direction of the candidate station site is located; 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 a functional relationship between the radius of a horizontal plane circle with the candidate machine 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, determining the terrain slope angle of the sector where the main wind direction is located; Based on the mapping relationship between the preset terrain slope angle and the complexity of the terrain corresponding to the sector, the terrain complexity level corresponding to the candidate machine site is determined.

[0129] According to the device 600 for determining design parameters of a wind turbine generator system based on complex terrain conditions provided by the present invention, the method further includes: Determine a sector where the main wind direction of the candidate station site is located, and a first sector and a second sector respectively adjacent to the sector where the main wind direction of the candidate station site is located; respectively determining a terrain complexity level corresponding to a sector where the main wind direction of the candidate machine site is located, a terrain complexity level corresponding to the first sector, and a terrain complexity level corresponding to the second sector; The design parameters of the wind turbine generator set at each candidate generator site are designed according to the time series data of wind condition parameters of different sectors corresponding to each candidate generator site and the terrain complexity level corresponding to each candidate generator site, including: The design parameters of the wind turbines at each of the candidate machine sites are designed according to the complexity level of the terrain corresponding to the sector where the main wind direction corresponding to each of the candidate machine sites is located, the complexity level of the terrain corresponding to the first sector corresponding to each of the candidate machine sites, and the complexity level of the terrain corresponding to the second sector.

[0130] 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 used for: According to the terrain complexity level corresponding to each candidate station site, the terrain complexity level corresponding to the first sector corresponding to each candidate station site, and the terrain complexity level corresponding to the second sector, the wind condition parameter time series data of different sectors corresponding to each candidate station site are finely classified to obtain a fine classification result of the wind condition parameters corresponding to each candidate station site; The refined classification results of the wind condition parameters corresponding to each of the candidate machine locations at least include parameter metrics of the sectors where the main wind direction corresponding to each of the candidate machine locations is located, the first sectors, and the second sectors in different time periods, and the parameter metrics are used to characterize: the target time period in which the probability of occurrence of meteorological parameters meets the preset conditions and the threshold value of the meteorological parameters corresponding to the target time period; Based on the refined classification results of the wind condition parameters corresponding to each of the candidate machine sites, the design parameters of the wind turbines at each of the candidate machine sites are adaptively designed to form a key wind resource parameter threshold table.

[0131] 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; The deep learning model training module is used to: Using the sample meteorological parameters of each candidate machine site, the terrain complexity level of each candidate machine site, and the label data of each candidate machine site, the initial deep learning network is trained to obtain a refined wind turbine design parameter determination model; The refined wind turbine design parameter determination model is used to determine the wind turbine design parameter values ​​at the target machine site.

[0132] Figure 7 is a schematic diagram of the structure of the electronic device provided by the present invention, such as Figure 7 As shown, the electronic device may include: a processor 710, a communications interface 720, a memory 730 and a communication bus 740, wherein the processor 710, the communications interface 720 and the memory 730 communicate with each other through the communication bus 740. The processor 710 may call the logic instructions in the memory 730 to execute a method for determining design parameters of a wind turbine generator set based on complex terrain conditions, the method comprising: Determine at least two candidate generator sites according to the incoming flow direction of the wind farm and the preliminary generator arrangement plan; the preliminary generator arrangement plan is used to characterize the generator site arrangement positions of the wind turbine generators in the wind farm plant area; For any of the candidate station locations, according to the meteorological parameters of the candidate station location and a preset number of sectors included in the candidate station location, determine the time series data of wind condition parameters of different sectors corresponding to the candidate station location; Determine the terrain complexity level corresponding to the candidate station 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 station 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, and extremely complex; The design parameters of the wind turbine generator set at each candidate generator site are designed according to the time series data of wind condition parameters of different sectors corresponding to each candidate generator site and the terrain complexity level corresponding to each candidate generator site.

[0133] In addition, the logic instructions in the above-mentioned memory 730 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on this understanding, the technical solution of the present invention can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0134] On the other hand, the present invention further provides a computer program product, the computer program product comprising a computer program, the computer program can be stored in 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 methods, the method comprising: Determine at least two candidate generator sites according to the incoming flow direction of the wind farm and the preliminary generator arrangement plan; the preliminary generator arrangement plan is used to characterize the generator site arrangement positions of the wind turbine generators in the wind farm plant area; For any of the candidate station locations, according to the meteorological parameters of the candidate station location and a preset number of sectors included in the candidate station location, determine the time series data of wind condition parameters of different sectors corresponding to the candidate station location; Determine the terrain complexity level corresponding to the candidate station 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 station 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, and extremely complex; The design parameters of the wind turbine generator set at each candidate generator site are designed according to the time series data of wind condition parameters of different sectors corresponding to each candidate generator site and the terrain complexity level corresponding to each candidate generator site.

[0135] In another aspect, the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon, which is implemented when the computer program is executed by a processor to execute the wind turbine design parameter determination method based on complex terrain conditions provided by the above methods, the method comprising: Determine at least two candidate generator sites according to the incoming flow direction of the wind farm and the preliminary generator arrangement plan; the preliminary generator arrangement plan is used to characterize the generator site arrangement positions of the wind turbine generators in the wind farm plant area; For any of the candidate station locations, according to the meteorological parameters of the candidate station location and a preset number of sectors included in the candidate station location, determine the time series data of wind condition parameters of different sectors corresponding to the candidate station location; Determine the terrain complexity level corresponding to the candidate station 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 station 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, and extremely complex; The design parameters of the wind turbine generator set at each candidate generator site are designed according to the time series data of wind condition parameters of different sectors corresponding to each candidate generator site and the terrain complexity level corresponding to each candidate generator site.

[0136] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0137] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for 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.

[0138] 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 it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for determining design parameters of a wind turbine generator system based on complex terrain conditions, characterized in that: include: Determine at least two candidate generating station locations based on the wind farm's incoming flow direction and the preliminary generating station layout plan; The preliminary unit arrangement plan is used to characterize the unit site arrangement positions of the wind turbine units in the wind farm plant area; For any of the candidate station locations, according to the meteorological parameters of the candidate station location and a preset number of sectors included in the candidate station location, determine the time series data of wind condition parameters of different sectors corresponding to the candidate station location; Determine the terrain complexity level corresponding to the candidate station 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 station 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, and extremely complex; The design parameters of the wind turbine generator set at each candidate generator site are designed according to the time series data of wind condition parameters of different sectors corresponding to each candidate generator site and the terrain complexity level corresponding to each candidate generator site.

2. The method for determining design parameters of a wind turbine generator system based on complex terrain conditions according to claim 1, characterized in that: The step of determining the time series data of wind condition parameters of different sectors corresponding to the candidate station site according to the meteorological parameters of the candidate station site and a preset number of sectors included in the candidate station site includes: Determine the time series data of the wind condition parameters of the candidate station location according to the meteorological parameters of the candidate station location; According to the preset number of sectors, the wind condition parameter time series data of each candidate station location is sector-classified to obtain the wind condition parameter time series data of different sectors corresponding to the candidate station location.

3. The method for determining design parameters of a wind turbine generator system based on complex terrain conditions according to claim 2, characterized in that: The preset number of sectors is obtained by dividing a horizontal circle with the candidate machine position as the center; the wind condition parameter time series data includes turbulence intensity, wind direction deflection rate and wind shear; The step of performing sector classification on the wind condition parameter time series data of each candidate station location according to the preset number of sectors to obtain the wind condition parameter time series data of different sectors corresponding to the candidate station location includes: For any of the candidate machine sites, based on the turbulence intensity corresponding to each of the sectors in the candidate machine site, determine a first metric standard set corresponding to each of the sectors in different time periods; the first metric standard set includes at least one of the following: the probability of occurrence of turbulence intensity in the time period, the average turbulence intensity, and the standard deviation of the average turbulence intensity; Counting the probability of occurrence of turbulence intensity in the time period, the average turbulence intensity and the average turbulence intensity standard deviation in the same time period, all of which meet the first preset threshold values ​​corresponding to the first metric standard set; Based on the wind direction deflection rate corresponding to each of the sectors, determining a second metric standard set corresponding to each of the sectors in different time periods; the second metric standard set includes at least one of the following: the probability of occurrence 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 probability of occurrence 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 in the same time period, all of which meet the second metric standard set corresponding to the second preset threshold value; Based on the vertical wind shear of each of the sectors, determine a third metric standard set corresponding to each of the sectors in different time periods; the third metric standard set includes at least one of the following: the probability of occurrence of vertical wind shear in the time period, the average vertical wind shear, and the standard deviation of the average vertical wind shear; Counting the probability of vertical wind shear occurring in the time period, the average vertical wind shear, and the average vertical wind shear standard deviation in the same time period, all of which satisfy the third metric standard set corresponding to the third preset threshold value; Based on the first set of metric standards that all meet the corresponding first preset thresholds, the second set of metric standards that all meet the corresponding second preset thresholds, and the third set of metric standards that all meet the corresponding third preset thresholds, the wind condition parameter time series data of different sectors corresponding to the candidate machine site are determined.

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

5. The method for determining design parameters of a wind turbine generator system based on complex terrain conditions according to claim 1, characterized in that: Determining the terrain complexity level corresponding to the candidate machine location includes: Based on a preset number of sectors included in the candidate station site, determining a sector where the main wind direction of the candidate station site is located; 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 a functional relationship between the radius of a horizontal plane circle with the candidate machine 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, determining the terrain slope angle of the sector where the main wind direction is located; Based on the mapping relationship between the preset terrain slope angle and the complexity of the terrain corresponding to the sector, the terrain complexity level corresponding to the candidate machine site is determined.

6. The method for determining design parameters of a wind turbine generator system based on complex terrain conditions according to claim 5, characterized in that: The method further comprises: Determine a sector where the main wind direction of the candidate station site is located, and a first sector and a second sector respectively adjacent to the sector where the main wind direction of the candidate station site is located; respectively determining a terrain complexity level corresponding to a sector where the main wind direction of the candidate machine site is located, a terrain complexity level corresponding to the first sector, and a terrain complexity level corresponding to the second sector; The design parameters of the wind turbine generator set at each candidate generator site are designed according to the time series data of wind condition parameters of different sectors corresponding to each candidate generator site and the terrain complexity level corresponding to each candidate generator site, including: The design parameters of the wind turbines at each of the candidate machine sites are designed according to the complexity level of the terrain corresponding to the sector where the main wind direction corresponding to each of the candidate machine sites is located, the complexity level of the terrain corresponding to the first sector corresponding to each of the candidate machine sites, and the complexity level of the terrain corresponding to the second sector.

7. The method for determining design parameters of a wind turbine generator system based on complex terrain conditions according to claim 6, characterized in that: The design parameters of the wind turbine generator set at each candidate generator site are designed according to the time series data of wind condition parameters of different sectors corresponding to each candidate generator site and the terrain complexity level corresponding to each candidate generator site, including: According to the terrain complexity level corresponding to each candidate station site, the terrain complexity level corresponding to the first sector corresponding to each candidate station site, and the terrain complexity level corresponding to the second sector, the wind condition parameter time series data of different sectors corresponding to each candidate station site are finely classified to obtain a fine classification result of the wind condition parameters corresponding to each candidate station site; The refined classification results of the wind condition parameters corresponding to each of the candidate machine locations at least include parameter metrics of the sectors where the main wind direction corresponding to each of the candidate machine locations is located, the first sectors, and the second sectors in different time periods, and the parameter metrics are used to characterize: the target time period in which the probability of occurrence of meteorological parameters meets the preset conditions and the threshold value of the meteorological parameters corresponding to the target time period; Based on the refined classification results of the wind condition parameters corresponding to each of the candidate machine sites, the design parameters of the wind turbines at each of the candidate machine sites are adaptively designed to form a key wind resource parameter threshold table.

8. The method for determining design parameters of a wind turbine generator system based on complex terrain conditions according to any one of claims 1 to 7, characterized in that: The method further comprises: Using the sample meteorological parameters of each candidate machine site, the terrain complexity level of each candidate machine site, and the label data of each candidate machine site, the initial deep learning network is trained to obtain a refined wind turbine design parameter determination model; The refined wind turbine design parameter determination model is used to determine the wind turbine design parameter values ​​at the target machine site.

9. A method for determining design parameters of a wind turbine generator system based on complex terrain conditions, characterized in that: include: A unit division module is used to determine at least two candidate unit locations according to the wind farm's incoming flow direction and the preliminary unit arrangement plan; The preliminary unit arrangement plan is used to characterize the unit site arrangement positions of the wind turbine units in the wind farm plant area; Design a parameter determination model, for any of the candidate station locations, determine the time series data of wind condition parameters of different sectors corresponding to the candidate station location according to the meteorological parameters of the candidate station location and a preset number of sectors included in the candidate station location; Determine the terrain complexity level corresponding to the candidate station 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 station 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, and extremely complex; The design parameters of the wind turbine generator set at each candidate generator site are designed according to the time series data of wind condition parameters of different sectors corresponding to each candidate generator site and the terrain complexity level corresponding to each candidate generator site.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the method for determining design parameters of a wind turbine generator system based on complex terrain conditions as described in any one of claims 1 to 8 is implemented.

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