A CFD-based Wind Resource Assessment and Power Generation Prediction Method and System

Abstract

The present invention relates to the technical field of wind farm simulation, and particularly relates to a method and system for wind resource assessment and power generation prediction based on CFD. The method includes obtaining wind condition data of a wind measurement point and all result points in a set of wind direction sectors through directional calculation, obtaining the wind measurement data of the wind measurement point at any wind direction, calculating the weights of two adjacent wind direction sectors to the wind direction of the wind measurement data under each working condition, establishing a wind condition mapping relationship between the wind measurement point and the result points, calculating and obtaining the equivalent wind data of the result points when the wind measurement point is at any wind direction, analyzing the equivalent wind data of all result points, assessing the wind resources of the target wind farm, and predicting the power generation of the target wind farm. The present invention can provide more accurate, efficient and reliable data support for wind resource assessment and power generation prediction through the equivalent wind data at all result points.

Description

Technical Field

[0001] The present invention relates to the technical field of wind farm simulation, and particularly to a method and system for wind resource assessment and power generation prediction based on CFD. Background Art

[0002] With the global climate warming, the development of new energy including wind power has been intensified. Therefore, how to capture wind energy economically and efficiently has become a long-term research topic in the wind energy industry. In particular, how to conduct accurate wind resource assessment and power generation calculation.

[0003] Currently, the core content of wind resource assessment and power generation calculation in a wind farm is divided into two steps, including directional calculation and comprehensive calculation. Directional calculation is to establish the wind parameter relationship between the wind measurement points and the wind farm (wind turbines); comprehensive calculation is to use the results of directional calculation, combined with wake models, wind farm layout, wind measurement data, and the characteristic curves of wind turbines, etc., to conduct wind resource assessment and power generation calculation without considering or considering the wake. However, in the above-mentioned wind farm resource assessment and power generation calculation, the wind measurement data obtained by devices such as wind measurement towers are difficult to cover the entire wind farm due to cost and limited data points, and cannot provide more accurate, efficient, and reliable data support for wind resource assessment and power generation prediction. Summary of the Invention

[0004] The technical problem to be solved by the embodiments of the present invention is to provide a method and system for wind resource assessment and power generation prediction based on CFD, so as to solve the problem in the prior art that it is difficult to cover the entire wind farm due to the acquisition of wind measurement data, resulting in the inability to provide more accurate, efficient, and reliable data support for wind resource assessment and power generation prediction.

[0005] The present invention discloses a method for wind resource assessment and power generation prediction based on CFD, including:

[0006] Establish a CFD model of the target wind farm, and obtain the wind condition data of the wind measurement points and all result points in a set of wind direction sectors through the directional calculation of the CFD model;

[0007] Obtain the wind measurement data of the wind measurement points in any wind direction, and determine two wind direction sectors adjacent to the wind direction of the wind measurement data;

[0008] According to the wind condition data corresponding to the wind measurement points in two wind direction sectors adjacent to the wind direction of the wind measurement data, calculate the weights of the two wind direction sectors adjacent to the wind direction of the wind measurement data under each working condition;

[0009] Establish the wind condition mapping relationship between the wind measurement point and the result point, and combine the obtained wind measurement data, the calculated weights, and the wind condition data corresponding to the wind measurement point and the result point in two wind direction sectors adjacent to the wind direction of the wind measurement data to calculate and obtain the equivalent wind data of the result point at any wind direction of the wind measurement point;

[0010] Analyze the equivalent wind data of all the result points to conduct wind resource assessment and power generation prediction for the target wind farm.

[0011] Optionally, the method for obtaining the wind condition data of the wind measurement point and all result points in a group of wind direction sectors through directional calculation includes:

[0012] Establish a group of the wind direction sectors with the same wind direction angle division range for the wind measurement point and each of the result points respectively;

[0013] Obtain the wind resources and power generation of the CFD model, and respectively obtain the directional calculation results of the wind measurement point and each of the result points in a group of the wind direction sectors through directional calculation. The directional calculation results include wind speed components and turbulent kinetic energy;

[0014] According to the directional calculation results of the wind measurement point and each of the result points, calculate and obtain the wind condition data of the wind measurement point and each of the result points in each of the wind direction sectors. The wind condition data includes wind acceleration factor, inflow angle, wind direction deflection angle, and calculated turbulence intensity.

[0015] Optionally, the method for calculating the weights of two wind direction sectors adjacent to the wind direction of the wind measurement data under each working condition includes:

[0016] Extract the wind direction angle from the wind measurement data, and based on the wind direction angle of the wind measurement data and the wind direction deflection angles of the wind measurement point corresponding to two wind direction sectors adjacent to the wind direction of the wind measurement data, obtain the weights of two wind direction sectors adjacent to the wind direction of the wind measurement data through interpolation calculation. The weight calculation formula is:

[0017]

[0018]

[0019] In the formula, represents the weight of the first wind direction sector adjacent to the wind direction of the wind measurement data, represents the wind direction angle of the first wind direction sector adjacent to the wind direction of the wind measurement data, represents the wind direction deflection angle of the wind measurement point corresponding to the first wind direction sector adjacent to the wind direction of the wind measurement data, represents the weight of the second wind direction sector adjacent to the wind direction of the wind measurement data, represents the wind direction angle of the second wind direction sector adjacent to the wind direction of the wind measurement data, Indicates the wind direction deflection angle of the wind measurement point corresponding to the second wind direction sector adjacent to the wind direction of the wind measurement data. Indicates wind direction of wind measurement data wind direction angle.

[0020] Optionally, the equivalent wind data obtained by calculation includes the wind direction angle of the result point, and the calculation method of the wind direction angle of the result point includes:

[0021] According to the wind direction angles of the two wind direction sectors adjacent to the wind direction of the wind measurement data and the wind direction deflection angle corresponding to the result point, an equivalent wind direction angle calculation formula for the result point under any wind direction is established. The equivalent wind direction angle calculation formula is:

[0022]

[0023] In the formula, Indicates any wind direction at the wind measurement point i The equivalent wind direction angle of the result point is Indicates the wind direction deflection angle of the result point corresponding to the first wind direction sector adjacent to the wind direction of the wind measurement data. Indicates the wind direction deflection angle of the result point corresponding to the second wind direction sector adjacent to the wind direction of the wind measurement data.

[0024] Optionally, the equivalent wind data obtained by calculation include wind speed and turbulence intensity at the result point;

[0025] The calculation method of the wind speed at the result point includes:

[0026] The wind speed is extracted from the wind measurement data, and when any wind direction of the wind measurement point is established, the mapping relationship between the wind speed of the wind measurement data of the wind measurement point and the directional wind acceleration factor is expressed as follows:

[0027]

[0028] When establishing the mapping relationship between the wind speed at the result point and the directional wind acceleration factor at any wind direction of the wind measurement point, the relationship expression is:

[0029]

[0030] By combining the above two relational expressions, a calculation formula for the equivalent wind speed of the result point at any wind direction of the wind measurement point is established. The equivalent wind speed calculation formula is:

[0031]

[0032] In the formula, Indicates the equivalent wind speed of the result point at any wind direction of the wind measurement point. Indicates the wind speed at any wind direction at the wind measuring point. Denote the wind acceleration factor of the anemometry point corresponding to the first wind direction sector adjacent to the wind direction of the anemometry data, Denote the wind acceleration factor of the anemometry point corresponding to the second wind direction sector adjacent to the wind direction of the anemometry data; Denote the wind acceleration factor of the result point corresponding to the first wind direction sector adjacent to the wind direction of the anemometry data, Denote the wind acceleration factor of the result point corresponding to the second wind direction sector adjacent to the wind direction of the anemometry data, Positively correlated;

[0033] The calculation method of the turbulence intensity of the result point includes:

[0034] Obtain the measured environmental turbulence intensity corresponding to the wind direction of the anemometry data, and when the anemometry point is at any wind direction, obtain the interpolated calculated turbulence intensity of the anemometry point in two adjacent wind direction sectors, and calculate the intensity difference between the measured environmental turbulence intensity and the interpolated calculated turbulence intensity corresponding to the anemometry point;

[0035] When the anemometry point is at any wind direction, obtain the interpolated calculated turbulence intensity of the result point in two adjacent wind direction sectors;

[0036] According to the wind acceleration factors of the anemometry point and the result point in each wind direction sector, establish the ratio relationship of the wind acceleration factors corresponding to the anemometry point and the result point when the anemometry point is at any wind direction. The expression of the ratio relationship is:

[0037]

[0038] According to the intensity difference, the interpolated calculated turbulence intensity corresponding to the result point, and the ratio relationship, establish the equivalent turbulence intensity calculation formula of the result point at any wind direction. The equivalent turbulence intensity calculation formula is:

[0039]

[0040] In the formula, Denote the equivalent turbulence intensity of the result point when the anemometry point is at any wind direction, Denote the interpolated calculated turbulence intensity corresponding to the result point, Denote the intensity difference between the measured environmental turbulence intensity and the interpolated calculated turbulence intensity corresponding to the anemometry point, Denote the wind acceleration factor of the anemometry point when the anemometry point is at any wind direction, Denote the wind acceleration factor of the result point when the anemometry point is at any wind direction, Denote the ratio relationship of the wind acceleration factors corresponding to the anemometry point and the result point.

[0041] Optionally, the calculation of the intensity difference between the measured environmental turbulence intensity and the interpolated calculated turbulence intensity corresponding to the anemometry point includes:

[0042] Extract the wind speed and the standard deviation of the wind speed from the wind measurement data, and calculate the turbulence intensity of the measurement environment corresponding to the wind direction of the wind measurement data according to the wind speed and the standard deviation of the wind speed of the wind measurement data. The calculation formula of the turbulence intensity of the measurement environment is as follows:

[0043]

[0044] In the formula, represents the turbulence intensity of the measurement environment corresponding to the wind direction of the wind measurement data at the wind measurement point, represents the standard deviation of the wind speed at the wind measurement point corresponding to the wind direction of the wind measurement data, represents the wind speed at the wind measurement point corresponding to the wind direction of the wind measurement data;

[0045] Extract the wind speed component of the test point from the directional calculation result, and calculate the calculated turbulence intensity of the wind measurement point in the adjacent two wind direction sectors when the wind measurement point is at any wind direction. The calculation formula of the calculated turbulence intensity of the wind measurement point is as follows:

[0046]

[0047] In the formula, represents the calculated turbulence intensity of the wind measurement point in the adjacent wind direction sectors when the wind measurement point is at any wind direction i of the wind measurement point, represents the turbulent kinetic energy of the wind measurement point corresponding to the adjacent wind direction sector i to the wind direction of the wind measurement data, represents the wind speed component along the west-to-east direction of the wind measurement point corresponding to the adjacent wind direction sector i to the wind direction of the wind measurement data, represents the wind speed component along the south-to-north direction of the wind measurement point corresponding to the adjacent wind direction sector i to the wind direction of the wind measurement data, represents the wind speed component from bottom to top of the wind measurement point corresponding to the adjacent wind direction sector i to the wind direction of the wind measurement data;

[0048] According to the calculated turbulence intensity of the wind measurement point in the adjacent two wind direction sectors, obtain the interpolated calculated turbulence intensity of the wind measurement point in the adjacent two wind direction sectors through interpolation. The calculation formula of the interpolated calculated turbulence intensity is as follows:

[0049]

[0050] In the formula, represents the interpolated calculated turbulence intensity of the wind measurement point in the adjacent two wind direction sectors, represents the calculated turbulence intensity of the wind measurement point in the adjacent first wind direction sector when the wind measurement point is at any wind direction, It represents the calculated turbulence intensity of the wind measurement point in the adjacent second wind direction sector at any wind direction of the wind measurement point;

[0051] Based on the measured environmental turbulence intensity and the interpolated calculated turbulence intensity obtained by calculation, calculate the intensity difference. The calculation formula for the intensity difference is:

[0052]

[0053] In the formula, It represents the intensity difference between the measured environmental turbulence intensity and the interpolated calculated turbulence intensity.

[0054] Optionally, it further includes a method for obtaining different types of equivalent wind data according to the type of the wind measurement data:

[0055] Based on data acquisition, obtain the time series wind measurement data at the wind measurement point, and calculate the time series equivalent wind data of the result point at the wind measurement point at any wind direction through the equivalent wind data calculation of the time series wind measurement data;

[0056] Based on file upload, obtain the TAB format wind measurement data, and calculate the TAB format equivalent wind data of the result point at the wind measurement point at any wind direction through the equivalent wind data calculation of the TAB format wind measurement data;

[0057] If the TAB format wind measurement data uses the median to represent the wind speed bin interval, increase the bin width by a preset multiple for each wind speed bin interval in the TAB format wind measurement data, and then perform the equivalent wind data calculation on the processed TAB format wind measurement data;

[0058] If the TAB format wind measurement data uses the upper limit to represent the wind speed bin interval, perform the equivalent wind data calculation on the TAB format wind measurement data;

[0059] Compare and analyze the time series equivalent wind data and the TAB format equivalent wind data of all the result points, and conduct wind resource assessment and power generation prediction for the target wind farm.

[0060] Optionally, it further includes a method for calculating and obtaining the single-tower equivalent wind data of the result point according to different types of the wind measurement data:

[0061] When the wind measurement data is time series wind measurement data, calculate the time series equivalent wind data of the single tower at the result point at any wind direction of the wind measurement point through the equivalent wind data calculation of the wind measurement data;

[0062] When the wind measurement data is in TAB format, the wind measurement data is supplemented with wind speed intervals and wind direction sectors to obtain TAB format sub-divided wind measurement data. The TAB format sub-divided wind measurement data is calculated through equivalent wind data to obtain the result point TAB format sub-divided equivalent wind data. Then, all the result point TAB format sub-divided equivalent wind data is aggregated to obtain the result point single-tower TAB format equivalent wind data at any wind direction of the wind measurement point.

[0063] Optionally, it further includes a method for obtaining the result point multi-tower equivalent wind data based on the result point single-tower equivalent wind data:

[0064] Based on the result point single-tower equivalent wind data, multi-tower weighted comprehensive calculation is performed to obtain the result point multi-tower equivalent wind data. The calculation formula for the result point multi-tower equivalent wind data is:

[0065]

[0066]

[0067] In the formula, For Total number of wind measurement towers, is the confidence coefficient of the th wind measurement tower, is the wind speed component and turbulence intensity calculated based on the th wind measurement tower at the result point, is the distance from the result point to the th wind measurement tower, is the weighted average coefficient of the th wind measurement tower, is the result point multi-tower equivalent wind data.

[0068] The present invention also discloses an evaluation and prediction system, which adopts the above-mentioned CFD-based wind resource evaluation and power generation prediction method. The system includes:

[0069] A directional calculation module, which is used to establish a CFD model of the target wind farm and obtain the wind condition data of the wind measurement point and all result points in a set of wind direction sectors through directional calculation;

[0070] A data processing module, which is used to obtain the wind measurement data at the wind measurement point in any wind direction and determine the two wind direction sectors adjacent to the wind direction of the wind measurement data;

[0071] A weight calculation module, which is used to calculate the weights of the two wind direction sectors adjacent to the wind direction of the wind measurement data under each working condition according to the wind condition data of the two wind direction sectors adjacent to the wind direction of the wind measurement data;

[0072] An equivalent wind data calculation module, which is used to establish the wind condition mapping relationship between the wind measurement point and the result point, and calculate and obtain the equivalent wind data of the result point at any wind direction of the wind measurement point by combining the obtained wind measurement data, the calculated weight, and the wind condition data of two wind direction sectors adjacent to the wind direction of the wind measurement data;

[0073] An evaluation and prediction module, which is used to analyze the equivalent wind data of all result points and conduct wind resource evaluation and power generation prediction for the target wind farm.

[0074] Compared with the prior art, the beneficial effects of the method and system for wind resource evaluation and power generation prediction based on CFD provided by the embodiments of the present invention are as follows:

[0075] By the directional calculation of the CFD model of the target wind farm, the wind condition data of the analysis objects including the wind measurement point and all result points in a group of wind direction sectors within the calculation domain are provided. By calculating the weights of two wind direction sectors adjacent to the wind direction of the wind measurement data under each working condition, and using the calculation of the equivalent wind data of the result points, the wind measurement data of the wind measurement point can be mapped to the result points, so that the result points have data in the same form as the wind measurement data, in order to obtain the equivalent wind data at all result points. Therefore, based on the equivalent wind data at all result points, more accurate, efficient, and reliable data support can be provided for wind resource evaluation and power generation prediction. BRIEF DESCRIPTION OF THE DRAWINGS

[0076] The technical solutions of the present invention will be further described in detail below in conjunction with the drawings and embodiments. In the drawings:

[0077] Figure 1 is a schematic block diagram of the steps of the method for wind resource evaluation and power generation prediction based on CFD provided by the embodiments of the present invention;

[0078] Figure 2 is a relationship diagram of the directional results of the result points and the corresponding wind measurement points in adjacent wind direction sectors at any wind direction provided by the embodiments of the present invention;

[0079] Figure 3 is a schematic block diagram of the process for calculating the equivalent wind data of a single wind measurement tower and multiple wind measurement towers based on time series data and TAB format data provided by the embodiments of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0080] It should be noted that, without conflict, the embodiments in the present application and the features in the embodiments can be combined with each other. Now, in conjunction with the drawings, the preferred embodiments of the present invention will be described in detail.

[0081] The present invention discloses a method for wind resource evaluation and power generation prediction based on CFD, as Figure 1 shown, including:

[0082] S1. Establish a CFD model of the target wind farm, and obtain the wind condition data of the anemometry points and all result points in a set of wind direction sectors through the directional calculation of the CFD model;

[0083] S2. Obtain the anemometry data of the anemometry points at any wind direction, and determine two wind direction sectors adjacent to the wind direction of the anemometry data;

[0084] S3. Calculate the weights of the two wind direction sectors adjacent to the wind direction of the anemometry data under each working condition according to the wind condition data corresponding to the anemometry points in the two wind direction sectors adjacent to the wind direction of the anemometry data;

[0085] S4. Establish the wind condition mapping relationship between the anemometry points and the result points, and combine the obtained anemometry data, the calculated weights, and the wind condition data corresponding to the anemometry points and the result points in the two wind direction sectors adjacent to the wind direction of the anemometry data to calculate and obtain the equivalent wind data of the result points when the anemometry points are at any wind direction;

[0086] S5. Analyze the equivalent wind data of all result points, and conduct wind resource assessment and power generation prediction for the target wind farm.

[0087] Through the implementation of the above embodiments of the wind resource assessment and power generation prediction method, Computational Fluid Dynamics (CFD) is a science that studies fluid flow through numerical methods and computer simulations. It can simulate the discrete distribution of fluid in a continuous region by solving the differential equations of fluid motion, so as to approximately simulate the actual fluid flow situation. Based on CFD wind farm modeling, by obtaining some terrain parameters of the target wind farm, a CFD model of the target wind farm can be established, and directional calculations using the CFD model of the target wind farm can be used to provide the wind condition data of the analysis objects including anemometry points and all result points in a set of wind direction sectors within the computational domain, that is, the directional results of anemometry points and the directional results of result points. By calculating the weights of the two wind direction sectors adjacent to the wind direction of the anemometry data under each working condition and using the calculation of the equivalent wind data of the result points, the anemometry data of the anemometry points can be mapped to the result points, so that the result points have data in the same form as the anemometry data, so as to synthesize the equivalent wind data at all result points, cover the entire target wind farm, and estimate the average wind force received by the target wind farm based on the wind direction, wind speed, turbulence intensity, etc. data included in the equivalent wind data of the result points, and the power generation of the target wind farm can be predicted based on the equivalent wind speed. Furthermore, by collecting and analyzing these data, more accurate, efficient, and reliable data support can be provided for wind resource assessment and power generation prediction.

[0088] Further, obtaining the wind condition data of the anemometry points and all result points in a set of wind direction sectors through directional calculation includes:

[0089] A set of wind direction sectors with the same wind direction angle division range is established for the wind measurement points and each result point respectively.

[0090] Obtain the wind resource and power generation of the CFD model, and respectively obtain the directional calculation results of the wind measurement points and each result point in a set of wind direction sectors through directional calculation. The directional calculation results include wind speed components and turbulent kinetic energy.

[0091] According to the directional calculation results of the wind measurement points and each result point, obtain the wind condition data of the wind measurement points and each result point in each wind direction sector through calculation. The wind condition data includes wind acceleration factor, inflow angle, wind direction deflection angle, and calculated turbulence intensity.

[0092] Through the implementation of the above embodiments of the wind resource assessment and power generation prediction method, since the wind direction angle is usually the angle measured clockwise from the north direction, and the range is from 0° (due north) to 360°. Therefore, the wind direction angle can be divided according to a certain interval, so that each wind direction sector in a set of wind direction sectors corresponds to a wind direction angle and is included in the range of 0° - 360°, as shown in the wind direction sector division table:

[0093] Wind Direction Sector Division Table

[0094]

[0095] As shown in the wind direction sector division table, the embodiment of the present invention preferably divides 16 wind direction sectors in the range of 0° - 360°. And for the convenience of interpolation calculation, on the basis of the 16 wind direction sectors, an additional directional calculation result in the specific direction of 360° is added, which is the same as 0°. Among them, in the wind direction sector division table, each wind direction sector corresponds to a box for statistics of wind condition data such as wind acceleration factor S, inflow angle In, wind direction deflection angle Dev, and calculated turbulence intensity TI for each point position. That is, the test points and each result point perform statistics of wind condition data through the above wind direction sector division table. Here, only the division of a set of wind direction sectors is shown in tabular form, without involving the statistics of specific data.

[0096] In addition, through directional calculation, the calculation results of the wind measurement points and each result point in a set of wind direction sectors are respectively obtained. The directional calculation results mainly include wind speed components (u, v, w), turbulent kinetic energy (k), atmospheric pressure (p), air density ( Calculations of physical fields such as (etc.). Among them, the wind speed component usually refers to the projection of the wind speed in the direction of the wind direction angle, and the turbulent kinetic energy is a parameter describing the turbulence intensity of the fluid. Based on the wind speed component and the turbulent kinetic energy, wind condition data such as the wind acceleration factor S, the inflow angle In, the wind direction deflection angle Dev, and the calculated turbulence intensity TI can be obtained through relevant defined formulas. Among them, the wind acceleration factor describes the degree of wind acceleration during the flow process and is usually used to evaluate the potential of wind energy resources. The inflow angle refers to the angle between the wind direction and the plane of the wind turbine blade, which affects the capture efficiency of wind energy. The wind direction deflection angle describes the angle difference between the actual wind direction and the reference wind direction (usually the wind direction at the wind measurement point). The calculated turbulence intensity measures the intensity of turbulence and has an important impact on the stability and performance of wind turbines. Therefore, by calculating, the wind acceleration factor, inflow angle, wind direction deflection angle, and calculated turbulence intensity at the wind measurement point and each result point in each wind direction sector are obtained to provide accurate, efficient, and reliable data for subsequent equivalent wind data calculations.

[0097] As described above, in step S2, while obtaining the wind measurement data, it is also necessary to prepare the analysis object, including obtaining the coordinates of the wind measurement point and each result point in the unified coordinate system. Since in step S1, based on the CFD model of the target wind field, the wind acceleration factor of the wind measurement point and all result points in a group of wind direction sectors is obtained through directional calculation S、 Inflow angle In , Wind direction deflection angle Dev , Calculated turbulence intensity TI, Through the coordinates of the wind measurement point and each result point, the wind acceleration factor S、 Inflow angle In , Wind direction deflection angle Dev , Calculated turbulence intensity TI and other wind field information at any point can be quickly located and retrieved, so as to facilitate subsequent equivalent data calculations.

[0098] Furthermore, as shown in Figure 2 , calculate the weights of the two wind direction sectors adjacent to the wind direction of the wind measurement data under each working condition, including:

[0099] Extract the wind direction angle from the wind measurement data. According to the wind direction angle of the wind measurement data and the wind direction deflection angles of the corresponding wind measurement points in the two wind direction sectors adjacent to the wind direction of the wind measurement data, the weights of the two wind direction sectors adjacent to the wind direction of the wind measurement data are obtained through interpolation calculation. The weight calculation formula is:

[0100]

[0101]

[0102] In the formula, represents the weight of the first wind direction sector adjacent to the wind direction of the wind measurement data, represents the wind direction angle of the first wind direction sector adjacent to the wind direction of the wind measurement data represents the wind direction deflection angle of the wind measurement point corresponding to the first wind direction sector adjacent to the wind direction of the wind measurement data represents the weight of the second wind direction sector adjacent to the wind direction of the wind measurement data represents the wind direction angle of the second wind direction sector adjacent to the wind direction of the wind measurement data represents the wind direction deflection angle of the wind measurement point corresponding to the second wind direction sector adjacent to the wind direction of the wind measurement data represents the wind direction angle of the wind direction i of the wind measurement data

[0103] Through the implementation of the above embodiments of the wind resource assessment and power generation prediction method, combined with the above wind direction sector division table, for example, the wind direction angle of the wind measurement data is 50°, then calculate the weights of the 45° wind direction sector and the 67.5° wind direction sector .

[0104] Furthermore, as shown in combination with Figure 2 , the obtained equivalent wind data includes the result point wind direction angle, and the calculation method of the result point wind direction angle includes:

[0105] According to the wind direction angles of two wind direction sectors adjacent to the wind direction of the wind measurement data, and the wind direction deflection angles of the corresponding result points, establish an equivalent wind direction angle calculation formula for the result point under any wind direction. The equivalent wind direction angle calculation formula is:

[0106]

[0107] In the formula, represents the equivalent wind direction angle of the result point at any wind direction of the wind measurement point i , represents the wind direction deflection angle of the result point corresponding to the first wind direction sector adjacent to the wind direction of the wind measurement data represents the wind direction deflection angle of the result point corresponding to the second wind direction sector adjacent to the wind direction of the wind measurement data

[0108] Furthermore, the obtained equivalent wind data includes the result point wind speed and turbulence intensity;

[0109] The calculation method of the result point wind speed includes:

[0110] Extract the wind speed from the wind measurement data, and establish the mapping relationship between the wind measurement data wind speed of the wind measurement point and the directional wind acceleration factor at any wind direction of the wind measurement point. The relationship expression is:

[0111]

[0112] When establishing an arbitrary wind direction at a wind measurement point, the mapping relationship between the wind speed at the result point and the directional wind acceleration factor is expressed as follows:

[0113]

[0114] Combining the above two relational expressions, the calculation formula for the equivalent wind speed of the result point at any wind direction at the wind measurement point is established. The calculation formula for the equivalent wind speed is:

[0115]

[0116] In the formula, Indicates the equivalent wind speed of the result point at any wind direction of the wind measurement point. Indicates the wind speed at any wind direction at the wind measuring point. Indicates the wind acceleration factor of the wind measurement point corresponding to the first wind direction sector adjacent to the wind direction of the wind measurement data. Indicates the wind acceleration factor of the wind measurement point corresponding to the second wind direction sector adjacent to the wind direction of the wind measurement data; Indicates the wind acceleration factor of the result point corresponding to the first wind direction sector adjacent to the wind direction of the wind measurement data. Indicates the wind acceleration factor of the result point corresponding to the second wind direction sector adjacent to the wind direction of the wind measurement data. Positive correlation;

[0117] The calculation methods of turbulence intensity at result points include:

[0118] Obtain the measured environmental turbulence intensity corresponding to the wind direction of the wind measurement data, and the interpolated turbulence intensity of the wind measurement point in two adjacent wind direction sectors when the wind measurement point has any wind direction, and calculate the intensity difference between the measured environmental turbulence intensity and the interpolated turbulence intensity corresponding to the wind measurement point;

[0119] When obtaining any wind direction at a wind measuring point, the turbulence intensity is calculated by interpolating the result point in two adjacent wind direction sectors;

[0120] According to the wind acceleration factors of the wind measuring point and the result point in each wind direction sector, the ratio relationship between the wind measuring point and the corresponding wind acceleration factors of the result point is established when the wind measuring point has any wind direction. The ratio relationship expression is:

[0121]

[0122] According to the intensity difference, the interpolation calculation of the turbulence intensity and the ratio relationship corresponding to the result point, the equivalent turbulence intensity calculation formula of the result point under any wind direction is established. The equivalent turbulence intensity calculation formula is:

[0123]

[0124] In the formula, It represents the equivalent turbulence intensity of the result point at any wind direction of the wind measurement point. Represents the interpolated turbulence intensity corresponding to the result point, Represents the intensity difference between the measured environmental turbulence intensity and the interpolated turbulence intensity corresponding to the anemometry point, Represents the wind acceleration factor of the anemometry point at any wind direction of the anemometry point, Represents the wind acceleration factor of the result point at any wind direction of the anemometry point, Represents the ratio relationship of the wind acceleration factors corresponding to the anemometry point and the result point.

[0125] Furthermore, calculating the intensity difference between the measured environmental turbulence intensity and the interpolated turbulence intensity corresponding to the anemometry point includes:

[0126] Extract the wind speed and wind speed standard deviation from the anemometry data, and calculate the measured environmental turbulence intensity corresponding to the wind direction of the anemometry data according to the wind speed and standard deviation of the anemometry data. The calculation formula for the measured environmental turbulence intensity is:

[0127]

[0128] In the formula, Represents the measured environmental turbulence intensity of the anemometry point corresponding to the wind direction of the anemometry data, Represents the wind speed standard deviation of the anemometry point corresponding to the wind direction of the anemometry data, Represents the wind speed of the anemometry point corresponding to the wind direction of the anemometry data;

[0129] Extract the wind speed components of the test point from the directional calculation results, and calculate the calculated turbulence intensity of the anemometry point in the adjacent two wind direction sectors at any wind direction of the anemometry point. The calculation formula for the calculated turbulence intensity of the anemometry point is:

[0130]

[0131] In the formula, Represents the calculated turbulence intensity of the anemometry point in the adjacent wind direction sectors at any wind direction of the anemometry point of, Represents the adjacent wind direction sector to the wind direction of the anemometry data corresponding to the turbulent kinetic energy of the anemometry point, Represents the adjacent wind direction sector to the wind direction of the anemometry data corresponding to the wind speed component of the anemometry point along the west-east direction, Represents the adjacent wind direction sector to the wind direction of the anemometry data corresponding to the wind speed component of the anemometry point along the south-north direction, Represents the adjacent wind direction sector to the wind direction of the anemometry data corresponding to the wind speed component of the anemometry point from bottom to top;

[0132] According to the calculated turbulence intensity of the wind measuring point in two adjacent wind direction sectors, the interpolation calculation of the turbulence intensity of the wind measuring point in two adjacent wind direction sectors is obtained by interpolation calculation. The calculation formula of the interpolation calculation of turbulence intensity is:

[0133]

[0134] In the formula, It indicates the interpolation calculation of turbulence intensity at the wind measuring point in two adjacent wind direction sectors. It represents the calculated turbulence intensity of the wind measuring point in the first adjacent wind direction sector when the wind measuring point has any wind direction. It represents the calculated turbulence intensity of the wind measuring point in the adjacent second wind direction sector when the wind direction is arbitrary at the wind measuring point;

[0135] According to the calculated measured environmental turbulence intensity and the interpolated turbulence intensity, the intensity difference is calculated. The calculation formula of the intensity difference is:

[0136]

[0137] In the formula, Represents the intensity difference between the measured ambient turbulence intensity and the interpolated turbulence intensity.

[0138] Combining the above calculation formulas, we can further obtain the equivalent turbulence intensity calculation formula:

[0139]

[0140]

[0141] Furthermore, combined with Figure 3 As shown, it also includes a method for obtaining different types of equivalent wind data according to the type of wind measurement data:

[0142] Based on data collection, the time series wind measurement data at the wind measurement point is obtained, and the time series wind measurement data is calculated through equivalent wind data to obtain the time series equivalent wind data of the result point at any wind direction of the wind measurement point;

[0143] Obtain TAB format wind measurement data based on file upload, calculate the TAB format wind measurement data through equivalent wind data, and obtain TAB format equivalent wind data of the result point at any wind direction;

[0144] If the TAB format wind measurement data uses the middle value to represent the wind speed bin interval, the bin width of each wind speed bin interval in the TAB format wind measurement data is increased by a preset multiple, and then the equivalent wind data is calculated for the processed TAB format wind measurement data;

[0145] When the TAB - formatted wind measurement data represents the wind speed bin interval with the upper limit value, equivalent wind data calculation is performed on the TAB - formatted wind measurement data;

[0146] Compare and analyze the time - series equivalent wind data and the TAB - formatted equivalent wind data of all result points to conduct wind resource assessment and power generation prediction for the target wind farm.

[0147] Through the implementation of the above - mentioned embodiments of the wind resource assessment and power generation prediction method, the wind measurement data includes wind measurement data from meteorological towers, mesoscale data, multi - mesoscale data, etc., and its types are further divided into time - series wind measurement data and TAB - formatted wind measurement data.

[0148] The time - series wind measurement data is represented by wind measurement data from meteorological towers with time stamps, radar wind measurement data, mesoscale data, etc. The meteorological towers participating in the comprehensive calculation need to use the wind measurement data at the highest altitude. Its data variables are as shown in the time - series wind measurement data variable table, including time (date&time), wind speed (v), wind direction (dir), turbulence intensity (ti), standard deviation (std), temperature (tem), relative humidity (rh), and air pressure (p).

[0149] Time - series wind measurement data variable table

[0150]

[0151] The TAB - formatted wind measurement data is further divided into two types. One type comes from the conversion of time - series data, and the other type comes from file upload. And the TAB - formatted wind measurement data based on file upload also includes two types:

[0152] (1) If the TAB - formatted data comes from types such as Windographer that represent the wind speed bin interval with the median value, additional processing is required for the wind speed used in calculating the average wind speed, energy density, annual power generation, etc., by adding 0.5*bin. This is because the wind speed reported by software such as Windographer is an estimate of the median value of each bin, while the actual average wind speed or energy density and other parameters may require more accurate bin boundary values;

[0153] (2) If the TAB - formatted data comes from types such as MeteodynWT that represent the wind speed bin interval with the upper limit value, no additional processing is required for the wind speed used in calculating the average wind speed, energy density, annual power generation, etc. This means that the central value (i.e., the median value of the bin) of each wind speed bin can be directly used to calculate parameters such as the average wind speed, energy density, and annual power generation. Since the wind speed reported by software such as MeteodynWT is the upper limit value of each bin, directly using the bin median value is accurate enough.

[0154] As described above, Windographer is a wind resource and visualization tool designed specifically for meteorological professionals, mainly used for importing, analyzing, and visualizing wind resource data measured by meteorological towers, sodars, or lidars. Meteodyn WT is a software mainly used for wind resource assessment in complex terrains. Its core is a set of computational fluid dynamics (CFD) codes dedicated to studying atmospheric flows, which can significantly reduce the uncertainties in wind farm design caused by complex terrains (such as mountains, forests, tidal flats, etc.) and improve the accuracy of wind energy resource assessment.

[0155] For TAB format wind measurement data based on file upload, for wind measurement data files with timestamps, wind speeds, wind directions, and standard deviations of wind speeds, without considering data truncation errors, it is approximately equivalent to 1 frequency distribution table + 1 turbulence intensity table + 1 relative standard deviation table of turbulence intensity. The frequency distribution table shows the frequency distributions of wind speed and wind direction. It usually contains various intervals (bins) of wind speed and corresponding wind speed values, as well as the number of wind speed occurrences (frequencies) within each wind direction sector. In TAB format wind measurement data, wind speed and wind direction are recorded according to timestamps, and the frequency distribution table can reflect the statistical characteristics of wind speed and wind direction; the turbulence intensity table records the turbulence intensities under different wind speed and wind direction conditions. Turbulence intensity is usually represented by the standard deviation of wind speed, which reflects the volatility of wind speed. In the approximate conversion, this table will be filled based on the standard deviation of wind speed in the wind measurement data, and each wind speed interval and wind direction sector corresponds to a turbulence intensity value; the relative standard deviation table of turbulence intensity provides the relative standard deviation of turbulence intensity, that is, the ratio of the standard deviation of turbulence intensity to the average turbulence intensity. The relative standard deviation is a relative measure that can help understand the degree of fluctuation of turbulence intensity relative to the average level. Through this approximation, complex TAB format wind measurement data can be simplified into a more easily analyzable and comparable tabular form.

[0156] Furthermore, it also includes a method for calculating the equivalent wind data of a single tower at the result point according to different types of wind measurement data:

[0157] When the wind measurement data is time series wind measurement data, the wind measurement data is calculated through equivalent wind data to obtain the equivalent wind data of the single tower at the result point at any wind direction, as shown in the equivalent wind data table of the single tower in the time series at the result point;

[0158] Equivalent wind data table of the single tower in the time series at the result point

[0159]

[0160] When the wind measurement data is in TAB format, the wind speed intervals and wind direction sectors are added to the wind measurement data to obtain the TAB format sub-divided wind measurement data. The TAB format sub-divided wind measurement data is calculated through equivalent wind data to obtain the result point TAB format sub-divided equivalent wind data. Then, all the result point TAB format sub-divided equivalent wind data is aggregated to obtain the result point single-tower TAB format equivalent wind data at any wind direction.

[0161] Here, taking the wind speed in the range of [7, 8) and the wind direction in the range of [45, 67.5) as an example, assuming its frequency is , and the turbulence intensity is , with the wind speed V at an interval of 0.2 m / s and the wind direction Dir at an interval of 2.5°, the sub-divided frequency matrix is evenly divided according to the original grid data for distance, and the increased wind speed intervals and wind direction sectors are presented through 1 frequency distribution table + 1 turbulence intensity table + 1 relative standard deviation table of turbulence intensity, without involving specific data:

[0162] Frequency distribution table

[0163]

[0164] Turbulence intensity table

[0165]

[0166] Relative standard deviation table of turbulence intensity

[0167]

[0168] Furthermore, it also includes a method for obtaining the multi-tower result point equivalent wind data based on the result point single-tower equivalent wind data:

[0169] Based on the result point single-tower equivalent wind data, multi-tower weighted comprehensive calculation is performed to obtain the multi-tower result point equivalent wind data. The calculation formula for the multi-tower result point equivalent wind data is:

[0170]

[0171]

[0172] In the formula, For Total number of wind measurement towers, is the confidence coefficient of the th wind measurement tower, is the wind speed component and turbulence intensity calculated based on the th wind measurement tower at the result point, is the distance from the result point to the i th wind measurement tower, is the weighted average coefficient of the i th wind measurement tower, It is the equivalent wind data of multiple towers for the result points.

[0173] Among them, for the time series data of multiple towers integrated, the result vectors (such as wind speed) are weighted by vectors, and the scalars (such as turbulence intensity) are weighted by scalars.

[0174] As described above, when the wind measurement data is time series wind measurement data, the multi-tower weighted integration calculation can be directly performed on the equivalent wind data of a single tower at the result points in the time series; when the wind measurement data is in TAB format, considering that the TAB format wind measurement data is an approximation of the time series wind measurement data, and the error is related to the wind speed interval and the size of the wind direction sector division. To reduce this approximation error, it is often further refined on the basis of the TAB format wind measurement data, and the equivalent wind data formula is used to calculate the equivalent wind data of the TAB format subdivision at the result points. The equivalent wind data of the TAB format subdivision at the result points is obtained through multi-tower weighted integration calculation to obtain the equivalent wind data of the multi-tower TAB format subdivision at the result points, and finally aggregated into the equivalent wind data of the multi-tower TAB format in the general sense (refer to Figure 3 )

[0175] The method for wind resource assessment and power generation prediction based on CFD in the embodiments of the present invention includes the equivalent wind data based on time series data and the equivalent wind data based on TAB format data for a single wind measurement tower and multiple wind measurement towers. The essence of the equivalent wind data calculation is to establish a set of relationships through directional calculation, providing information such as wind acceleration factors, wind direction deviations, inflow angles, and turbulence intensities in specific wind directions of all result points (point elements of all analysis objects including wind measurement points, etc.) within the calculation domain, and mapping the wind measurement data information at the wind measurement points to the analysis objects, so that the result points in the analysis objects have data in the same form as the wind measurement data, in order to provide more accurate, efficient, and reliable data support for wind resource assessment and power generation prediction through the equivalent wind data at all result points.

[0176] Based on the above wind resource assessment and power generation prediction method, the present invention also discloses an assessment and prediction system, including:

[0177] A directional calculation module, configured to establish a CFD model of the target wind farm and obtain the wind condition data of the wind measurement points and all result points in a group of wind direction sectors through directional calculation;

[0178] A data processing module, configured to obtain the wind measurement data of the wind measurement points in any wind direction and determine two wind direction sectors adjacent to the wind direction of the wind measurement data;

[0179] A weight calculation module, configured to calculate the weights of the two wind direction sectors adjacent to the wind direction of the wind measurement data under each working condition according to the wind condition data of the two wind direction sectors adjacent to the wind direction of the wind measurement data;

[0180] The equivalent wind data calculation module is used to establish the mapping relationship of wind conditions between the wind measurement points and the result points, and calculate and obtain the equivalent wind data of the result points at any wind direction of the wind measurement points by combining the obtained wind measurement data, the calculated weights, and the wind condition data of the two wind direction sectors adjacent to the wind direction of the wind measurement data.

[0181] The evaluation and prediction module is used to analyze the equivalent wind data of all result points and conduct wind resource evaluation and power generation prediction for the target wind farm.

[0182] Based on the above wind resource evaluation and power generation prediction method, the present invention also discloses a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above wind resource evaluation and power generation prediction method are implemented.

[0183] Based on the above wind resource evaluation and power generation prediction method, the present invention also discloses a computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. The feature is that when the processor executes the computer program, the steps of the above wind resource evaluation and power generation prediction method are implemented.

[0184] The present invention is described according to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products of the specific embodiments. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for implementing the specified functions in one process Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0185] These computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing devices to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured product including an instruction device, and the instruction device implements the specified functions in one process Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0186] These computer program instructions can also be loaded onto a computer or other programmable data processing devices, so that a series of operation steps are executed on the computer or other programmable devices to generate a computer-implemented process. Therefore, the instructions executed on the computer or other programmable devices provide for implementing the specified functions in one process Figure 1One process or multiple processes and / or boxes Figure 1 Steps of the functions specified in one box or multiple boxes.

[0187] It should be understood that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. For those skilled in the art, the technical solutions recorded in the above embodiments can be modified, or some of the technical features can be equivalently replaced; and all such modifications and replacements should fall within the protection scope of the appended claims of the present invention.

Claims

1. A CFD-based wind resource assessment and power generation prediction method, characterized in that, The wind resource assessment and power generation prediction method includes: Establish a CFD model of the target wind farm, and obtain the wind condition data of the anemometry point and all result points in a set of wind direction sectors through the directional calculation of the CFD model, including establishing a set of the wind direction sectors with the same wind direction angle division range for the anemometry point and each of the result points respectively, obtaining the wind condition data of the anemometry point and each of the result points in each of the wind direction sectors, and the wind condition data includes wind acceleration factor, inflow angle, wind direction deflection angle, and calculated turbulence intensity; Obtain the anemometry data of the anemometry point at any wind direction, and determine two of the wind direction sectors adjacent to the wind direction of the anemometry data; According to the wind condition data corresponding to the anemometry point in two of the wind direction sectors adjacent to the wind direction of the anemometry data, calculate the weights of two of the wind direction sectors adjacent to the wind direction of the anemometry data under each working condition, including extracting the wind direction angle from the anemometry data, and according to the wind direction angle of the anemometry data and the wind direction deflection angles corresponding to the anemometry point in two of the wind direction sectors adjacent to the wind direction of the anemometry data, obtaining the weights of two of the wind direction sectors adjacent to the wind direction of the anemometry data through interpolation calculation, and the weight calculation formula is: In the formula, represents the weight of the first wind direction sector adjacent to the wind direction of the wind measurement data, represents the wind direction angle of the first wind direction sector adjacent to the wind direction of the wind measurement data, represents the wind direction deflection angle of the wind measurement point corresponding to the first wind direction sector adjacent to the wind direction of the wind measurement data, represents the weight of the second wind direction sector adjacent to the wind direction of the wind measurement data, represents the wind direction angle of the second wind direction sector adjacent to the wind direction of the wind measurement data, represents the wind direction deflection angle of the wind measurement point corresponding to the second wind direction sector adjacent to the wind direction of the wind measurement data, represents the wind direction angle of the wind direction i of the wind measurement data; Establish the wind condition mapping relationship between the anemometry point and the result points, and combine the obtained anemometry data, the calculated weights, and the wind condition data corresponding to the anemometry point and the result points in two of the wind direction sectors adjacent to the wind direction of the anemometry data, and calculate and obtain the equivalent wind data of the result points when the anemometry point is at any wind direction, including the equivalent wind speed of the result points when the anemometry point is at any wind direction, and the equivalent turbulence intensity of the result points at any wind direction; The calculation formula for the equivalent wind speed of the result points when the anemometry point is at any wind direction is: In the formula, represents the equivalent wind speed of the result point at any wind direction of the wind measurement point, represents the wind speed of the wind measurement point at any wind direction of the wind measurement point, represents the wind acceleration factor corresponding to the wind measurement point in the first wind direction sector adjacent to the wind direction of the wind measurement data, represents the wind acceleration factor corresponding to the wind measurement point in the second wind direction sector adjacent to the wind direction of the wind measurement data; represents the wind acceleration factor corresponding to the result point in the first wind direction sector adjacent to the wind direction of the wind measurement data, represents the wind acceleration factor corresponding to the result point in the second wind direction sector adjacent to the wind direction of the wind measurement data, is positively correlated; The calculation formula for the equivalent turbulence intensity of the result points at any wind direction is: In the formula, represents the equivalent turbulence intensity of the result point at any wind direction of the wind measurement point, represents the interpolated turbulence intensity corresponding to the result point, represents the intensity difference between the measured environmental turbulence intensity and the interpolated turbulence intensity corresponding to the wind measurement point, represents the wind acceleration factor of the wind measurement point at any wind direction, represents the wind acceleration factor of the result point at any wind direction of the wind measurement point, represents the ratio relationship of the wind acceleration factors corresponding to the wind measurement point and the result point; Analyze the equivalent wind data of all the result points, and conduct wind resource assessment and power generation prediction for the target wind farm.

2. The CFD-based wind resource assessment and power generation prediction method according to claim 1, wherein The obtaining the wind condition data of the anemometry point and all result points in a set of wind direction sectors through the directional calculation of the CFD model includes: Obtain the wind resources and power generation of the CFD model, and respectively obtain the directional calculation results of the anemometry point and each of the result points in a set of the wind direction sectors through directional calculation, and the directional calculation results include wind speed components and turbulent kinetic energy; According to the directional calculation results of the anemometry point and each of the result points, calculate and obtain the wind condition data of the anemometry point and each of the result points in each of the wind direction sectors, and the wind condition data includes wind acceleration factor, inflow angle, wind direction deflection angle, and calculated turbulence intensity.

3. The CFD-based wind resource assessment and power generation prediction method according to claim 2, wherein The calculated and obtained equivalent wind data includes the wind direction angle of the result points, and the calculation method of the wind direction angle of the result points includes: According to the wind direction angles of two of the wind direction sectors adjacent to the wind direction of the anemometry data and the wind direction deflection angles corresponding to the result points, establish an equivalent wind direction angle calculation formula for the result points at any wind direction, and the equivalent wind direction angle calculation formula is: In the formula, represents the equivalent wind direction angle of the result point at any wind direction of the wind measurement point i when, represents the wind direction deflection angle of the result point corresponding to the first wind direction sector adjacent to the wind direction of the wind measurement data, represents the wind direction deflection angle of the result point corresponding to the second wind direction sector adjacent to the wind direction of the wind measurement data.

4. The CFD-based wind resource assessment and power generation prediction method according to claim 2, wherein The calculated and obtained equivalent wind data includes the wind speed and turbulence intensity of the result points; The calculation method of the wind speed of the result points includes: The wind speed is extracted from the wind measurement data, and when any wind direction of the wind measurement point is established, the mapping relationship between the wind speed of the wind measurement data of the wind measurement point and the directional wind acceleration factor is expressed as follows: When establishing the mapping relationship between the wind speed at the result point and the directional wind acceleration factor at any wind direction of the wind measurement point, the relationship expression is: Combining the above two relational expressions, a calculation formula for the equivalent wind speed of the result point at any wind direction of the wind measurement point is established; The calculation method of the turbulence intensity at the result point includes: Obtaining the measured environment turbulence intensity corresponding to the wind direction of the wind measurement data, and the interpolated calculated turbulence intensity of the wind measurement point in two adjacent wind direction sectors when the wind measurement point has any wind direction, and calculating the intensity difference between the measured environment turbulence intensity and the interpolated calculated turbulence intensity corresponding to the wind measurement point; When obtaining any wind direction at the wind measuring point, the turbulence intensity is calculated by interpolating the result point in two adjacent wind direction sectors; According to the wind acceleration factors of the wind measuring point and the result point in each wind direction sector, a ratio relationship between the wind measuring point and the result point corresponding to the wind acceleration factors when the wind measuring point has any wind direction is established, and the ratio relationship expression is: According to the intensity difference, the interpolated turbulence intensity corresponding to the result point, and the ratio relationship, a calculation formula for the equivalent turbulence intensity of the result point under any wind direction is established.

5. The CFD-based wind resource assessment and power generation prediction method according to claim 4, wherein The calculating the intensity difference between the measured environment turbulence intensity and the interpolated calculated turbulence intensity corresponding to the wind measurement point comprises: The wind speed and the wind speed standard deviation are extracted from the wind measurement data, and the measured environmental turbulence intensity corresponding to the wind direction of the wind measurement data is calculated based on the wind speed and the wind speed standard deviation of the wind measurement data. The calculation formula for the measured environmental turbulence intensity is: In the formula, represents the measurement environmental turbulence intensity corresponding to the wind direction of the wind measurement data at the wind measurement point, represents the standard deviation of the wind speed at the wind measurement point corresponding to the wind direction of the wind measurement data, represents the wind speed at the wind measurement point corresponding to the wind direction of the wind measurement data; The wind speed component of the wind measuring point is extracted from the directional calculation result, and the turbulence intensity of the wind measuring point in two adjacent wind direction sectors is calculated when obtaining any wind direction of the wind measuring point. The calculation formula for the turbulence intensity of the wind measuring point is: In the formula, represents the calculated turbulence intensity at the wind measurement point for any wind direction in the adjacent wind direction sectors of the wind measurement point i , represents the turbulent kinetic energy of the wind measurement point corresponding to the adjacent wind direction sector of the wind direction of the wind measurement data i , represents the wind speed component along the west-east direction of the wind measurement point corresponding to the adjacent wind direction sector of the wind direction of the wind measurement data i , represents the wind speed component along the south-north direction of the wind measurement point corresponding to the adjacent wind direction sector of the wind direction of the wind measurement data i , represents the wind speed component from bottom to top of the wind measurement point corresponding to the adjacent wind direction sector of the wind direction of the wind measurement data i . According to the calculated turbulence intensity of the wind measuring point in two adjacent wind direction sectors, the interpolated calculated turbulence intensity of the wind measuring point in two adjacent wind direction sectors is obtained by interpolation calculation. The calculation formula of the interpolated calculated turbulence intensity is: In the formula, represents the interpolated calculation of the turbulence intensity at the wind measurement point in two adjacent wind direction sectors, represents the calculated turbulence intensity at the wind measurement point in the adjacent first wind direction sector at any wind direction of the wind measurement point, represents the calculated turbulence intensity at the wind measurement point in the adjacent second wind direction sector at any wind direction of the wind measurement point; The intensity difference is calculated according to the measured environment turbulence intensity obtained by calculation and the interpolation calculated turbulence intensity. The calculation formula of the intensity difference is: In the formula, represents the intensity difference between the measured environmental turbulence intensity and the interpolated calculated turbulence intensity.

6. The CFD-based wind resource assessment and power generation prediction method according to any one of claims 1-5, characterized in that The method also includes obtaining different types of equivalent wind data according to the type of wind measurement data: Based on data collection, the time series wind measurement data at the wind measurement point is acquired, and the time series wind measurement data is calculated through equivalent wind data to obtain the time series equivalent wind data of the result point at the wind measurement point in any wind direction; Acquire TAB format wind measurement data based on file upload, calculate the TAB format wind measurement data through equivalent wind data, and obtain TAB format equivalent wind data of the result point at any wind direction of the wind measurement point; When the wind measurement data in TAB format uses the median value to represent the wind speed bin interval, increase the bin width by a preset multiple for each wind speed bin interval in the TAB format wind measurement data, and then perform equivalent wind data calculation on the processed TAB format wind measurement data; When the wind measurement data in TAB format uses the upper limit to represent the wind speed bin interval, perform equivalent wind data calculation on the TAB format wind measurement data; Compare and analyze the time series equivalent wind data and TAB format equivalent wind data of all the result points, and conduct wind resource assessment and power generation prediction for the target wind farm.

7. The CFD-based wind resource assessment and power generation prediction method according to claim 6, wherein It also includes a method for calculating the single-tower equivalent wind data of the result points based on different types of the wind measurement data: When the wind measurement data is time series wind measurement data, perform equivalent wind data calculation on the wind measurement data to obtain the single-tower time series equivalent wind data of the result points at any wind direction of the wind measurement point; When the wind measurement data is TAB format wind measurement data, add wind speed intervals and wind direction sectors to the wind measurement data to obtain the TAB format detailed wind measurement data, perform equivalent wind data calculation on the TAB format detailed wind measurement data to obtain the TAB format detailed equivalent wind data of the result points, and then aggregate all the TAB format detailed equivalent wind data of the result points to obtain the single-tower TAB format equivalent wind data of the result points at any wind direction of the wind measurement point.

8. The CFD-based wind resource assessment and power generation prediction method according to claim 7, wherein It also includes a method for obtaining the multi-tower equivalent wind data of the result points based on the single-tower equivalent wind data of the result points: Based on the single-tower equivalent wind data of the result points, perform multi-tower weighted comprehensive calculation to obtain the multi-tower equivalent wind data of the result points. The calculation formula for the multi-tower equivalent wind data of the result points is: Wherein, is The total number of wind measurement towers, is the confidence coefficient of the th wind measurement tower, is the wind speed component and turbulence intensity calculated for the result point based on the th wind measurement tower, is the distance from the result point to the th wind measurement tower, is the weighted average coefficient of the th wind measurement tower, is the multi-tower equivalent wind data of the result point.

9. An evaluation and prediction system that adopts the CFD-based wind resource assessment and power generation prediction method according to any one of claims 1-8. The system includes: A directional calculation module, configured to establish a CFD model of the target wind farm and obtain the wind condition data of the wind measurement point and all result points in a set of wind direction sectors through directional calculation; A data processing module, configured to obtain the wind measurement data of the wind measurement point at any wind direction and determine two wind direction sectors adjacent to the wind direction of the wind measurement data; A weight calculation module, configured to calculate the weights of the two wind direction sectors adjacent to the wind direction of the wind measurement data under each working condition according to the wind condition data of the two wind direction sectors adjacent to the wind direction of the wind measurement data; An equivalent wind data calculation module, configured to establish a wind condition mapping relationship between the wind measurement point and the result points, and calculate and obtain the equivalent wind data of the result points at any wind direction of the wind measurement point by combining the obtained wind measurement data, the calculated weights, and the wind condition data of the two wind direction sectors adjacent to the wind direction of the wind measurement data; An evaluation and prediction module, configured to analyze the equivalent wind data of all result points and conduct wind resource assessment and power generation prediction for the target wind farm.

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