Method, device and equipment for determining generating capacity of wind turbine generator, medium and product

Abstract

The invention relates to the technical field of wind power generation, and discloses a wind turbine generator generating capacity determination method, device and equipment, a medium and a product. The wind turbine generator generating capacity determination method comprises the steps of obtaining an atmospheric stability parameter of a target wind turbine generator, and determining the generating capacity of the target wind turbine generator according to a target characteristic parameter and the atmospheric stability parameter; analyzing the wind speed change rule of the preset to-be-built area; analyzing the wind speed of the impeller surface of the target wind turbine generator according to a wind speed vertical change function obtained by analyzing the geometric parameters of the target wind turbine generator, the atmospheric stability parameters and the wind speed change rule to obtain the equivalent wind speed of the impeller surface; determining Weibull distribution parameters according to the impeller surface equivalent wind speed; according to the Weibull distribution parameters, the preset wind speed power curve of the target wind turbine generator and the wind direction frequency determined according to the impeller surface equivalent wind speed, the annual energy output of the target wind turbine generator is determined, the influence of wind speed fluctuation on the annual energy output is considered, and the accuracy of the determined annual energy output is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of wind power generation, in particular to a method, device, equipment, medium and product for determining the power generation of a wind turbine. BACKGROUND

[0002] In the early development process of a wind power project, a wind measurement tower needs to be set up in the proposed wind farm area to collect wind measurement data, and the annual power generation of the wind turbine is determined in combination with the power generation performance of the target wind turbine. The annual power generation is used to evaluate the wind energy resource condition and study the feasibility of the wind power project.

[0003] In the related art, the method for determining the annual power generation of a wind turbine is to fit the Weibull distribution model based on the wind speed data of the wind measurement tower to obtain Weibull distribution parameters, to determine the frequency distribution of each wind speed segment in a year according to the Weibull distribution parameters, and to obtain the annual power generation of the wind turbine in combination with the power generation power of the wind turbine at the corresponding wind speed segment.

[0004] However, since the wind speed fluctuation on the impeller surface of the wind turbine also affects the annual power generation, the annual power generation obtained according to the method for determining the annual power generation of a wind turbine in the related art has a large error and is not accurate enough, which does not conform to the actual situation. SUMMARY

[0005] Therefore, the present application provides a method, device, equipment, medium and product for determining the power generation of a wind turbine to solve the problem that the method for determining the annual power generation of a wind turbine in the related art has a large error and is not accurate enough, which does not conform to the actual situation.

[0006] In a first aspect, the present application provides a method for determining the power generation of a wind turbine, comprising: obtaining an atmospheric stability parameter of a target wind turbine in a preset proposed area, analyzing the wind speed variation law of the preset proposed area according to a target characteristic parameter of the target wind turbine and the atmospheric stability parameter, and obtaining a wind speed vertical variation function; the target characteristic parameter of the target wind turbine is used to represent the effect of the geometric configuration of the target wind turbine and the underlying surface environment on the wind farm; the wind speed vertical variation function is used to represent the law of the change of wind speed with vertical height variable under the influence of atmospheric stability and target characteristic parameter; analyzing the wind speed of the impeller surface of the target wind turbine according to the geometric parameters of the target wind turbine, the atmospheric stability parameter and the wind speed vertical variation function, and obtaining the equivalent wind speed of the impeller surface; determining the Weibull distribution parameters corresponding to the equivalent wind speed of the impeller surface according to the equivalent wind speed of the impeller surface; the Weibull distribution parameters are used to represent the probability distribution of the equivalent wind speed of the impeller surface; determining the annual power generation of the target wind turbine according to the Weibull distribution parameters, the preset wind speed power curve of the target wind turbine and the wind direction frequency determined according to the equivalent wind speed of the impeller surface.

[0007] The application obtains the atmospheric stability parameters of the target wind turbine in the preset construction area, analyzes the wind speed variation law of the preset construction area according to the target characteristic parameters and the atmospheric stability parameters of the target wind turbine, and obtains the wind speed vertical variation function, which can accurately represent the vertical variation law of the wind speed under complex conditions and provide a reliable basis for subsequent analysis of the wind speed of the impeller surface. According to the geometric parameters of the target wind turbine, the atmospheric stability parameters and the wind speed vertical variation function, the wind speed of the impeller surface of the target wind turbine is analyzed, and the equivalent wind speed of the impeller surface is obtained. The geometric parameters of the application are the properties of the impeller itself. Combined with the atmospheric stability parameters and the wind speed vertical variation function, the wind speed of the impeller surface is analyzed and the equivalent wind speed is obtained. The complex vertically distributed wind speed can be converted into the equivalent wind speed suitable for the characteristics of the impeller surface, solving the problem that the wind speed at different heights of the impeller surface is inconsistent and difficult to be directly used for determining the power generation capacity. According to the equivalent wind speed of the impeller surface, the Weibull distribution parameters corresponding to the equivalent wind speed of the impeller surface are determined. The Weibull distribution is an effective model for describing the probability distribution of wind speed. Based on the equivalent wind speed of the impeller surface, the Weibull distribution parameters are determined, which can quantitatively present the probability characteristics of the equivalent wind speed of the impeller surface. The accurate Weibull distribution parameters improve the control of wind speed uncertainty in determining the power generation capacity, so that the subsequent annual power generation capacity is more in line with the actual long-term operation. According to the Weibull distribution parameters, the preset wind speed power curve of the target wind turbine and the wind direction frequency determined according to the equivalent wind speed of the impeller surface, the annual power generation capacity of the target wind turbine is determined. Compared with related technologies, the application considers the spatial and temporal distribution of the wind speed of the impeller surface, reduces the error of the obtained annual power generation capacity, makes the obtained annual power generation capacity more accurate and more in line with the actual situation.

[0008] In an optional embodiment, the atmospheric stability parameters include the Obukhov length, the friction velocity and the wind speed standard deviation of the horizontal average wind direction; obtaining the atmospheric stability parameters of the target wind turbine in the preset construction area includes: determining the friction velocity according to the wind speed fluctuation of the horizontal average wind direction, the covariance of the wind speed fluctuation of the horizontal direction perpendicular to the average wind direction and the wind speed fluctuation of the vertical direction; determining the Obukhov length according to the friction velocity, the air temperature fluctuation and the wind speed fluctuation of the vertical direction; and performing square root processing on the variance of the wind speed fluctuation of the horizontal average wind direction to obtain the wind speed standard deviation of the horizontal average wind direction.

[0009] In an optional implementation, the wind speed variation law of the preset region to be built is analyzed according to the target characteristic parameter of the target wind turbine and the atmospheric stability parameter, and a wind speed vertical variation function is obtained, including: determining a Coriolis parameter according to the latitude of the wind measurement tower in the preset region to be built and the earth rotation angular velocity; combining the Coriolis parameter, the friction velocity and the surface roughness to obtain a mid-layer mixing length; determining an atmospheric boundary layer height according to the quotient of the friction velocity and the Coriolis parameter; determining a turbulence scale parameter according to the quotient of the vertical height variable and the Obukhov length; correcting the wind speed profile by using the turbulence scale parameter to obtain a target correction term; determining whether the boundary layer is stable according to the quotient of the vertical height variable and the Obukhov length; if the boundary layer is stable, determining the wind speed vertical variation function according to the vertical height variable, the surface roughness, the Obukhov length, the atmospheric boundary layer height, the mid-layer mixing length, the hub height and the horizontal average wind speed; if the boundary layer is unstable, determining the wind speed vertical variation function according to the vertical height variable, the target correction term, the surface roughness, the Obukhov length, the atmospheric boundary layer height, the mid-layer mixing length, the hub height and the horizontal average wind speed.

[0010] In an optional implementation, the wind speed of the impeller surface of the target wind turbine is analyzed according to the unit geometric parameter of the target wind turbine, the atmospheric stability parameter and the wind speed vertical variation function, and an equivalent wind speed of the impeller surface is obtained, including: determining a height interval according to the impeller radius and the hub height in the unit geometric parameter of the target wind turbine; performing weighted integration on the wind speed vertical variation function and the wind speed standard deviation of the horizontal average wind direction in the atmospheric stability parameter according to the height interval to obtain a weighted integration result; performing averaging and power processing on the weighted integration result according to the impeller radius to obtain the equivalent wind speed of the impeller surface.

[0011] In an optional implementation, the Weibull distribution parameter includes a shape parameter and a scale parameter; the Weibull distribution parameter corresponding to the equivalent wind speed of the impeller surface is determined according to the equivalent wind speed of the impeller surface; the Weibull distribution parameter is used to represent the probability distribution of the equivalent wind speed of the impeller surface, including: grouping the equivalent wind speed of the impeller surface according to the average wind direction data, analyzing the fluctuation degree of the equivalent wind speed of the impeller surface in each group to obtain a relative standard deviation; performing power correction on the relative standard deviation to obtain the shape parameter; obtaining the power mean of each group of equivalent wind speed of the impeller surface, and performing distribution correction processing on the power mean to obtain the scale parameter.

[0012] In an optional embodiment, the annual power generation of the target wind turbine is determined according to the Weibull distribution parameter, the preset wind speed-power curve of the target wind turbine, and the wind direction frequency determined according to the blade face equivalent wind speed, including: dividing each group of blade face equivalent wind speeds to obtain a plurality of wind speed intervals; analyzing the cumulative probability density corresponding to the plurality of wind speed intervals in each group of blade face equivalent wind speeds according to the Weibull distribution parameter to obtain a cumulative probability density function; determining the wind direction frequency of each group of blade face equivalent wind speeds according to the number of each group of blade face equivalent wind speeds and the total number of blade face equivalent wind speeds; analyzing the probability difference of the plurality of wind speed intervals in each group of blade face equivalent wind speeds according to the cumulative probability density function to obtain a wind speed interval probability difference; performing weighted summation on the product of the wind speed interval probability difference corresponding to the plurality of wind speed intervals in the plurality of groups of blade face equivalent wind speeds and the power generation power in the preset wind speed-power curve corresponding to each wind speed interval according to the wind direction frequency of each group of blade face equivalent wind speeds to obtain a power generation contribution value; and obtaining the annual power generation of the target wind turbine according to the product of the power generation contribution value and the annual hours.

[0013] In a second aspect, the present application provides a device for determining the power generation of a wind turbine, comprising: a wind speed variation law analysis module, configured to obtain the atmospheric stability parameter of a target wind turbine in a preset proposed area, analyze the wind speed variation law of the preset proposed area according to the target characteristic parameter of the target wind turbine and the atmospheric stability parameter, and obtain a wind speed vertical variation function; the target characteristic parameter of the target wind turbine is used to represent the effect of the geometric configuration of the target wind turbine and the underlying surface environment on the wind farm; the wind speed vertical variation function is used to represent the law of the change of wind speed with vertical height variable under the influence of atmospheric stability and target characteristic parameter; a blade face wind speed analysis module, configured to analyze the wind speed of the blade face of the target wind turbine according to the unit geometric parameter of the target wind turbine, the atmospheric stability parameter, and the wind speed vertical variation function, and obtain the blade face equivalent wind speed; a Weibull distribution analysis module, configured to determine the Weibull distribution parameter corresponding to the blade face equivalent wind speed according to the blade face equivalent wind speed; the Weibull distribution parameter is used to represent the probability distribution of the blade face equivalent wind speed; and an annual power generation determination module, configured to determine the annual power generation of the target wind turbine according to the Weibull distribution parameter, the preset wind speed-power curve of the target wind turbine, and the wind direction frequency determined according to the blade face equivalent wind speed.

[0014] In a third aspect, the present application provides a computer device, comprising: a memory and a processor, which are communicatively connected with each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the method for determining the power generation of a wind turbine according to the first aspect or any one of the corresponding embodiments thereof.

[0015] In a fourth aspect, the present application provides a computer readable storage medium, having stored thereon computer instructions for causing a computer to execute the wind turbine power generation determination method of the first aspect or any of the corresponding embodiments thereof.

[0016] In a fifth aspect, the present application provides a computer program product comprising computer instructions for causing a computer to execute the wind turbine power generation determination method of the first aspect or any of the corresponding embodiments thereof. BRIEF DESCRIPTION OF DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the specific embodiments of the present application or the technical solutions in the related art, the drawings needed to be used in the specific embodiments or the related art description will be briefly introduced. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without any creative effort on the basis of these drawings.

[0018] Figure 1 is a flowchart of the wind turbine power generation determination method according to an embodiment of the present application.

[0019] Figure 2 is a daily time series diagram of the standard deviation of wind speed in the horizontal average wind direction according to an embodiment of the present application.

[0020] Figure 3 is a diagram of the wind speed vertical variation function under different Obukhov lengths according to an embodiment of the present application.

[0021] Figure 4 is a flowchart of another wind turbine power generation determination method according to an embodiment of the present application.

[0022] Figure 5 is a daily time series diagram of the horizontal average wind speed and the equivalent wind speed of the impeller face according to an embodiment of the present application.

[0023] Figure 6 is a diagram of the Weibull distribution according to an embodiment of the present application.

[0024] Figure 7 is a flowchart of still another wind turbine power generation determination method according to an embodiment of the present application.

[0025] Figure 8 is a diagram of the preset wind speed-power curve according to an embodiment of the present application.

[0026] Figure 9 is a flowchart of still another wind turbine power generation determination method according to an embodiment of the present application.

[0027] Figure 10 is a structural block diagram of a wind turbine generator power generation amount determination device according to an embodiment of the present application.

[0028] Figure 11 is a hardware structure schematic diagram of a computer device according to an embodiment of the present application. DETAILED DESCRIPTION

[0029] In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some but not all of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0030] In the early development process of a wind power project, a wind measurement tower needs to be set up in a proposed wind farm area to collect wind measurement data, and corresponding methods are used to determine the annual power generation amount of a target wind turbine generator combined with the power generation performance of the target wind turbine generator. The annual power generation amount is used to evaluate the wind energy resource condition and study the feasibility of the wind power project.

[0031] At present, the method for determining the annual power generation amount of a wind turbine generator is generally as follows: based on wind speed data of a wind measurement tower, Weibull distribution parameters are calculated by fitting calculation using a Weibull distribution model, the frequency distribution of each wind speed segment in one year is determined according to the Weibull distribution parameters, and the annual power generation amount of the wind turbine generator is obtained by combining the power generation power of the wind turbine generator at the corresponding wind speed segment.

[0032] This method does not consider the wind speed spatial distribution condition on the impeller surface of the wind turbine generator. In general, the wind speed also increases with the increase of the height, and the function relationship between the wind speed and the height is affected by factors such as atmospheric stability, so that the total amount of wind energy captured by the wind turbine generator on the impeller surface changes; this method does not consider the instantaneous time change condition on the impeller surface of the wind turbine generator. Under the same average wind speed condition, the instantaneous wind speed fluctuation is also different, and has an influence on the total amount of wind energy on the impeller surface of the wind turbine generator. Therefore, the error of the annual power generation amount determined by this method is large and not accurate enough.

[0033] The embodiments of the present application provide a method for determining the annual power generation amount of a wind turbine generator, which considers the influence of wind speed fluctuation on the annual power generation amount, so as to improve the accuracy of the determined annual power generation amount.

[0034] According to the embodiment of the present application, a method for determining the power generation of a wind turbine is provided. It should be noted that the steps shown in the flowchart of the drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described herein can be executed in an order different from that shown.

[0035] In the present embodiment, a method for determining the power generation of a wind turbine is provided, which can be used in a computer device, Figure 1 is a flowchart of the method for determining the power generation of a wind turbine according to the embodiment of the present application, as shown in Figure 1 The flowchart includes the following steps:

[0036] In step S101, the atmospheric stability parameter of the target wind turbine in the preset region to be built is obtained, and the wind speed variation law of the preset region to be built is analyzed according to the target characteristic parameter of the target wind turbine and the atmospheric stability parameter, so as to obtain a wind speed vertical variation function; the target characteristic parameter of the target wind turbine is used to represent the effect of the geometric configuration of the target wind turbine and the underlying surface environment on the wind farm; and the wind speed vertical variation function is used to represent the law of the variation of the wind speed with the vertical height variable under the influence of the atmospheric stability and the target characteristic parameter.

[0037] In the present embodiment, the target wind turbine is a wind turbine whose annual power generation needs to be determined; the preset region to be built is a region constructed by the target wind turbine; and the atmospheric stability parameter is used to represent the turbulence intensity, momentum exchange capacity and stable state of the atmospheric boundary layer.

[0038] In some optional embodiments, the atmospheric stability parameter includes the Obukhov length, the friction velocity and the wind speed standard deviation of the horizontal average wind direction; obtaining the atmospheric stability parameter of the target wind turbine in the preset region to be built includes: determining the friction velocity according to the wind speed fluctuation of the horizontal average wind direction of the preset region to be built, the covariance of the wind speed fluctuation of the horizontal direction perpendicular to the average wind direction and the wind speed fluctuation of the vertical direction; determining the Obukhov length according to the friction velocity, the air temperature fluctuation and the wind speed fluctuation of the vertical direction; and performing square root processing on the variance of the wind speed fluctuation of the horizontal average wind direction to obtain the wind speed standard deviation of the horizontal average wind direction.

[0039] The obtaining process of the wind speed fluctuation amount of the horizontal average wind direction of the preset building area, the wind speed fluctuation amount of the horizontal direction perpendicular to the average wind direction, and the wind speed fluctuation amount of the vertical direction is as follows: three-dimensional wind speed data is obtained, the three-dimensional wind speed data including the wind speed of the horizontal average wind direction, the wind speed of the horizontal direction perpendicular to the average wind, and the wind speed of the vertical direction; the wind speed of the horizontal average wind direction is converted through a rotation matrix to obtain the instantaneous wind speed along the average wind direction and the instantaneous wind speed perpendicular to the average wind direction; the instantaneous wind speed along the average wind direction in a preset time period is averaged to obtain the average instantaneous wind speed along the average wind direction, and the instantaneous wind speed perpendicular to the average wind direction in the preset time period is averaged to obtain the average instantaneous wind speed perpendicular to the average wind direction; the wind speed fluctuation amount of the horizontal average wind direction is obtained according to the difference between the instantaneous wind speed along the average wind direction and the average instantaneous wind speed along the average wind direction, and the wind speed fluctuation amount of the horizontal direction perpendicular to the average wind direction is obtained according to the difference between the instantaneous wind speed perpendicular to the average wind direction and the average instantaneous wind speed along the average wind direction; the wind speed of the vertical direction in the preset time period is averaged to obtain the average wind speed of the vertical direction; and the wind speed fluctuation amount of the vertical direction is obtained according to the difference between the wind speed of the vertical direction and the average wind speed of the vertical direction.

[0040] In some optional embodiments, the process of determining the air temperature fluctuation amount is as follows: air temperature data is obtained, the air temperature data in a preset time period is averaged to obtain the average air temperature data, and the air temperature fluctuation amount is obtained according to the difference between the air temperature data at each time and the average air temperature data.

[0041] The preset time period can be 10 minutes, a wind measurement tower is set up in the preset building area, and a three-dimensional ultrasonic anemometer and an air temperature sensor are installed at the hub height of the wind measurement tower to obtain three-dimensional wind speed data and air temperature data, and the sampling frequency of the three-dimensional ultrasonic anemometer is above 10 HZ. The time length of the wind measurement data of the wind measurement tower is 1 year or above.

[0042] Exemplarily, the formula for determining the friction velocity is as follows:

[0043]

[0044] wherein, u * is the friction velocity, u' is the wind speed fluctuation amount of the horizontal average wind direction, v' is the wind speed fluctuation amount of the horizontal direction perpendicular to the average wind direction, and w' is the wind speed fluctuation amount of the vertical direction.

[0045] Exemplarily, the formula for determining the Obukhov length is as follows:

[0046]

[0047] wherein, L is the Obukhov length, u * is the friction velocity, Let be the temperature fluctuation, κ be the Karman constant (taken as 0.4), and g be the gravitational acceleration (taken as 9.8 m / s²). 2 (meters per second squared), where w' is the vertical wind speed pulsation.

[0048] For example, the formula for determining the standard deviation of wind speed in the horizontal mean wind direction is:

[0049]

[0050] Where σ is the standard deviation of wind speed in the horizontal mean wind direction, and u' is the wind speed fluctuation in the horizontal mean wind direction.

[0051] For example, such as Figure 2 The figure shows a daily time series diagram of the standard deviation of wind speed in the horizontal mean wind direction, from August 1, 2008 to July 31, 2009. The horizontal axis represents time: Aug for August, Sep for September, Oct for October, Nov for November, Dec for December, Jan for January, Feb for February, Mar for March, Apr for April, May for May, Jun for June, and Jul for July. The vertical axis represents the standard deviation of wind speed, in m / s (meters per second).

[0052] In some optional implementations, based on the target characteristic parameters and atmospheric stability parameters of the target wind turbine, the wind speed variation pattern of the pre-designed construction area is analyzed to obtain the vertical wind speed variation function, including: determining the Coriolis parameter based on the latitude of the wind measurement tower and the Earth's rotation angular velocity in the pre-designed construction area; combining the Coriolis parameter, friction velocity, and surface roughness to obtain the mid-level mixing length; determining the atmospheric boundary layer height based on the quotient of friction velocity and Coriolis parameter; determining the turbulence scale parameter based on the quotient of vertical height variable and Obukhov length; and utilizing... The wind speed profile is corrected using turbulence-scale parameters to obtain the target correction term. The stability of the wind crust is determined based on the vertical height variable and the Obukhov length. If the wind crust is stable, the vertical wind speed variation function is determined based on the vertical height variable, surface roughness, Obukhov length, atmospheric boundary layer height, meso-level mixing length, hub height, and horizontal average wind speed. If the wind crust is unstable, the vertical wind speed variation function is determined based on the vertical height variable, the target correction term, surface roughness, Obukhov length, atmospheric boundary layer height, meso-level mixing length, hub height, and horizontal average wind speed.

[0053] For example, the formula for determining the Coriolis parameter is:

[0054] f = 2Ωsinφ

[0055] Where f is the Coriolis parameter, Ω is the Earth's rotational angular velocity, and φ is the latitude of the wind measurement tower in the pre-defined area, which can be 41.34°.

[0056] Exemplarily, a formula for determining the mid-layer mixing length is:

[0057]

[0058] wherein, L M is the mid-layer mixing length, u * is the wind speed fluctuation in the horizontal average wind direction, f is the Coriolis parameter, z0 is the surface roughness, which can be 0.03 m, and is estimated according to the surface coverage type, c0 is the first empirical parameter, which can be 5.

[0059] Exemplarily, a formula for determining the atmospheric boundary layer height is:

[0060]

[0061] wherein, z h is the atmospheric boundary layer height, c1 is the second empirical parameter, which can be 0.1, u * is the wind speed fluctuation in the horizontal average wind direction, f is the Coriolis parameter, c2 is the third empirical parameter, which can be 0.22, L is the Obukhov length, and z is the vertical height variable.

[0062] Exemplarily, a formula for determining the turbulence scale parameter is:

[0063]

[0064] wherein, x is the turbulence scale parameter, z is the vertical height variable, and L is the Obukhov length.

[0065] Exemplarily, a formula for determining the target correction term is:

[0066]

[0067] wherein, is the target correction term, x is the turbulence scale parameter, z is the vertical height variable, and L is the Obukhov length.

[0068] In some optional embodiments, judging whether the boundary layer is stable according to the vertical height variable and the Obukhov length comprises: when a quotient of the vertical height variable and the Obukhov length is greater than or equal to 0, judging that the boundary layer is stable; and when the quotient of the vertical height variable and the Obukhov length is less than 0, judging that the boundary layer is unstable.

[0069] Exemplarily, a formula for determining the wind speed vertical variation function is:

[0070]

[0071] wherein, U(z) is a wind speed vertical variation function, z is a vertical height variable, z0 is a ground roughness, L is an Obukhov length, z h is an atmospheric boundary layer height, L M is a mid-layer mixing length, z hub is a hub height, is a horizontal mean wind speed, ψ m is a target correction term.

[0072] Exemplarily, as shown in FIG. 1, it is a wind speed vertical variation function diagram under different Obukhov lengths, the horizontal coordinate is a dimensionless wind speed, which is a quotient of the wind speed vertical variation function and the wind speed fluctuation of the horizontal mean wind direction, used to represent a characteristic velocity of the atmospheric turbulence in the near-surface layer, the vertical coordinate is a vertical height variable, with a unit of m, in different Obukhov length intervals, the wind speed vertical variation functions are different. Figure 3

[0073] Step S102, analyzing the wind speed of the impeller surface of the target wind turbine according to the turbine geometric parameters of the target wind turbine, the atmospheric stability parameters and the wind speed vertical variation function, to obtain an equivalent wind speed of the impeller surface.

[0074] In some optional embodiments, the analyzing the wind speed of the impeller surface of the target wind turbine according to the turbine geometric parameters of the target wind turbine, the atmospheric stability parameters and the wind speed vertical variation function, to obtain an equivalent wind speed of the impeller surface, comprises: determining a height interval according to the hub height and the impeller radius in the turbine geometric parameters of the target wind turbine; performing weighted integration on the wind speed vertical variation function and the wind speed standard deviation of the horizontal mean wind direction in the atmospheric stability parameters according to the height interval, to obtain a weighted integration result; performing averaging and power processing on the weighted integration result according to the impeller radius, to obtain the equivalent wind speed of the impeller surface.

[0075] wherein, the turbine geometric parameters comprise the impeller radius and the hub height and the like, exemplarily, the impeller radius can be 70 m, and the hub height can be 90 m.

[0076] In some optional embodiments, the height interval is obtained according to the sum of the hub height and the impeller radius in the turbine geometric parameters of the target wind turbine, and the difference between the hub height and the impeller radius in the turbine geometric parameters of the target wind turbine.

[0077] Step S103, determining a Weibull distribution parameter corresponding to the equivalent wind speed of the impeller surface according to the equivalent wind speed of the impeller surface; the Weibull distribution parameter is used to represent the probability distribution of the equivalent wind speed of the impeller surface.

[0078] ​In some optional embodiments, the Weibull distribution parameters include a shape parameter and a scale parameter; the Weibull distribution parameters corresponding to the equivalent wind speed of the impeller surface are determined according to the equivalent wind speed of the impeller surface; the Weibull distribution parameters are used to represent the probability distribution of the equivalent wind speed of the impeller surface, including: grouping the equivalent wind speed of the impeller surface according to the average wind direction data, analyzing the fluctuation degree of each group of the equivalent wind speed of the impeller surface to obtain a relative standard deviation; performing power correction on the relative standard deviation to obtain the shape parameter; obtaining the power mean of each group of the equivalent wind speed of the impeller surface, and performing distribution correction processing on the power mean to obtain the scale parameter.

[0079] In step S104, the annual power generation of the target wind turbine is determined according to the Weibull distribution parameters, the preset wind speed-power curve of the target wind turbine, and the wind direction frequency determined according to the equivalent wind speed of the impeller surface.

[0080] In some optional embodiments, the annual power generation of the target wind turbine is determined according to the Weibull distribution parameters, the preset wind speed-power curve of the target wind turbine, and the wind direction frequency determined according to the equivalent wind speed of the impeller surface, including: dividing each group of the equivalent wind speed of the impeller surface to obtain a plurality of wind speed intervals; analyzing the cumulative probability density corresponding to the plurality of wind speed intervals in each group of the equivalent wind speed of the impeller surface according to the Weibull distribution parameters to obtain a cumulative probability density function; determining the wind direction frequency of each group of the equivalent wind speed of the impeller surface according to the number of each group of the equivalent wind speed of the impeller surface and the total number of the equivalent wind speed of the impeller surface; analyzing the probability difference of the plurality of wind speed intervals in each group of the equivalent wind speed of the impeller surface according to the cumulative probability density function to obtain a wind speed interval probability difference; weighting and summing the product of the wind speed interval probability difference corresponding to the plurality of wind speed intervals in each group of the equivalent wind speed of the impeller surface and the power generation power in the preset wind speed-power curve corresponding to each wind speed interval according to the wind direction frequency of each group of the equivalent wind speed of the impeller surface to obtain a power generation contribution value; and obtaining the annual power generation of the target wind turbine according to the product of the power generation contribution value and the annual hours.

[0081] The method for determining the power generation of a wind turbine provided in the embodiment comprises the following steps: obtaining an atmospheric stability parameter of a target wind turbine in a preset region to be built; analyzing a wind speed variation law of the preset region to be built according to a target characteristic parameter of the target wind turbine and the atmospheric stability parameter, and obtaining a wind speed vertical variation function; and analyzing a wind speed of a blade surface of the target wind turbine according to a geometric parameter of the target wind turbine, the atmospheric stability parameter and the wind speed vertical variation function, and obtaining an equivalent wind speed of the blade surface. The geometric parameter of the target wind turbine is a property of the blade itself, and the equivalent wind speed is obtained by analyzing the wind speed of the blade surface in combination with the atmospheric stability parameter and the wind speed vertical variation function. The equivalent wind speed of the blade surface is obtained by converting the complex vertically distributed wind speed into the equivalent wind speed that is suitable for the characteristics of the blade surface, thereby solving the problem that the wind speed at different heights of the blade surface is inconsistent and is difficult to be directly used for determining the power generation. According to the equivalent wind speed of the blade surface, a Weibull distribution parameter corresponding to the equivalent wind speed of the blade surface is determined. The Weibull distribution is an effective model for describing the probability distribution of the wind speed, and the Weibull distribution parameter is determined based on the equivalent wind speed of the blade surface, so that the probability characteristics of the equivalent wind speed of the blade surface can be quantitatively presented, and the accurate Weibull distribution parameter improves the control of the wind speed uncertainty in the determination of the power generation, so that the annual power generation obtained subsequently is more in line with the actual long-term operation condition. According to the Weibull distribution parameter, a preset wind speed power curve of the target wind turbine and a wind direction frequency determined according to the equivalent wind speed of the blade surface, the annual power generation of the target wind turbine is determined. Compared with the related art, the method considers the spatial and temporal distribution of the wind speed of the blade surface, reduces the error of the annual power generation obtained, makes the annual power generation obtained more accurate, and is more in line with the actual situation.

[0082] A method for determining the power generation of a wind turbine is provided in the embodiment, which can be used for a computer device, Figure 4 is a flowchart of another method for determining the power generation of a wind turbine according to the embodiment of the present application, as shown in Figure 4 The flowchart comprises the following steps:

[0083] In step S401, an atmospheric stability parameter of a target wind turbine in a preset region to be built is obtained, a wind speed vertical variation function is obtained by analyzing a wind speed variation law of the preset region to be built according to a target characteristic parameter of the target wind turbine and the atmospheric stability parameter; the target characteristic parameter of the target wind turbine is used to represent the effect of the geometric configuration of the target wind turbine and the underlying surface environment on the wind farm; and the wind speed vertical variation function is used to represent the variation law of the wind speed with the vertical height variable under the influence of the atmospheric stability and the target characteristic parameter. For details, refer to step S101 of the embodiment shown in Figure 1 , which will not be described here again.

[0084] Step S402, according to the wind turbine geometry parameters of the target wind turbine, the atmospheric stability parameters and the wind speed vertical variation function, the wind speed of the impeller surface of the target wind turbine is analyzed to obtain the equivalent wind speed of the impeller surface.

[0085] Specifically, the above step S402 comprises:

[0086] Step S4021, according to the impeller radius and hub height in the wind turbine geometry parameters of the target wind turbine, the height interval is determined.

[0087] Step S4022, according to the height interval, the wind speed standard deviation of the horizontal average wind direction is weightedly integrated by using the wind speed vertical variation function and the atmospheric stability parameters to obtain the weighted integration result.

[0088] Step S4023, according to the impeller radius, the weighted integration result is averaged and processed by power to obtain the equivalent wind speed of the impeller surface.

[0089] Exemplarily, the formula for determining the equivalent wind speed of the impeller surface is:

[0090]

[0091] Wherein, U eq is the equivalent wind speed of the impeller surface, R is the impeller radius, z hub is the hub height, U(z) is the wind speed vertical variation function, and σ is the wind speed standard deviation of the horizontal average wind direction.

[0092] Exemplarily, as shown in Figure 5 , it is a daily time sequence diagram of the horizontal average wind direction wind speed and the equivalent wind speed of the impeller surface. The time is from August 1, 2008 to July 31, 2009. The annual average value of the horizontal average wind direction wind speed is 7.98 m / s, and the annual average value of the equivalent wind speed of the impeller surface is 8.20 m / s.

[0093] Step S403, according to the equivalent wind speed of the impeller surface, the Weibull distribution parameters corresponding to the equivalent wind speed of the impeller surface are determined; the Weibull distribution parameters are used to characterize the probability distribution of the equivalent wind speed of the impeller surface.

[0094] Specifically, the above step S403 comprises:

[0095] Step S4031, according to the average wind direction data, the equivalent wind speed of the impeller surface is grouped, and the fluctuation degree of the equivalent wind speed of the impeller surface in each group is analyzed to obtain the relative standard deviation.

[0096] Wherein, based on the average wind direction data of the preset time period, the equivalent wind speed of the impeller surface is grouped according to the wind direction from 0 to 360 degrees, which is classified into 1 group every 22.5 degrees, and 16 groups of the equivalent wind speed of the impeller surface are obtained.

[0097] Step S4032, power correction is performed on the relative standard deviation to obtain a shape parameter.

[0098] Exemplarily, the formula for determining the shape parameter is as follows:

[0099]

[0100] wherein B k is the shape parameter of the kth group of impeller face equivalent wind speed, STD is a standard deviation function, U eq,k is the kth group of impeller face equivalent wind speed.

[0101] Step S4033, the power mean of each group of impeller face equivalent wind speed is obtained, and distribution correction is performed on the power mean to obtain a scale parameter.

[0102] Exemplarily, the formula for determining the scale parameter is as follows:

[0103]

[0104] wherein C k is the scale parameter of the kth group of impeller face equivalent wind speed, is the mean of the kth group of impeller face equivalent wind speed, U eq,k is the kth group of impeller face equivalent wind speed, Γ is a gamma function, B k is the shape parameter of the kth group of impeller face equivalent wind speed.

[0105] In some optional embodiments, the corresponding wind direction record number is counted respectively, and then divided by the total wind direction record number of the 16 groups of data, so as to calculate the wind direction frequency corresponding to each group of impeller face equivalent wind speed. Exemplarily, the wind direction frequencies corresponding to the 16 groups of impeller face equivalent wind speed are 4.1%, 4.4%, 5.6%, 4.0%, 2.4%, 1.1%, 1.0%, 1.9%, 7.7%, 15.6%, 11.8%, 12.6%, 9.7%, 7.0%, 6.1% and 5.0% respectively.

[0106] Exemplarily, the shape parameter of the first group of impeller face equivalent wind speed is 2.57, and the scale parameter is 9.21 m / s. As shown in FIG. 4, it is a Weibull distribution diagram, the horizontal coordinate is the impeller face equivalent wind speed, and the unit is m / s, and the vertical coordinate is the wind direction frequency. Figure 6

[0107] Step S404, the annual power generation of the target wind turbine is determined according to the Weibull distribution parameters, the preset wind speed-power curve of the target wind turbine and the wind direction frequency determined according to the impeller face equivalent wind speed. For details, please refer to step S104 of the embodiment shown in FIG. 1, which will not be described here again. Figure 1

[0108] ​​The embodiment provides a method for determining power generation of a wind turbine generator, which can be used for a computer device, Figure 7 is a flowchart of still another method for determining power generation of a wind turbine generator according to an embodiment of the present application, as shown in the figure, the flow includes the following steps: Figure 7

[0109] In step S701, an atmospheric stability parameter of a target wind turbine generator in a preset proposed area is obtained, a wind speed variation law of the preset proposed area is analyzed according to a target characteristic parameter of the target wind turbine generator and the atmospheric stability parameter, and a wind speed vertical variation function is obtained; the target characteristic parameter of the target wind turbine generator is used to represent the effect of the geometric configuration of the target wind turbine generator and the underlying surface environment on the wind farm; and the wind speed vertical variation function is used to represent the law of the variation of the wind speed with the vertical height variable under the influence of the atmospheric stability and the target characteristic parameter. For details, refer to step S101 of the embodiment shown in Figure 1 , which will not be repeated here.

[0110] In step S702, the wind speed of the impeller surface of the target wind turbine generator is analyzed according to the geometric parameters of the wind turbine generator, the atmospheric stability parameter and the wind speed vertical variation function, and the equivalent wind speed of the impeller surface is obtained. For details, refer to steps S102 and S402 of the embodiments shown in Figure 1 and Figure 4 , which will not be repeated here.

[0111] In step S703, the Weibull distribution parameter corresponding to the equivalent wind speed of the impeller surface is determined according to the equivalent wind speed of the impeller surface; the Weibull distribution parameter is used to represent the probability distribution of the equivalent wind speed of the impeller surface. For details, refer to steps S103 and S403 of the embodiments shown in Figure 1 and Figure 4 , which will not be repeated here.

[0112] In step S704, the annual power generation of the target wind turbine generator is determined according to the Weibull distribution parameter, the preset wind speed power curve of the target wind turbine generator and the wind direction frequency determined according to the equivalent wind speed of the impeller surface.

[0113] Specifically, the above step S704 includes:

[0114] In step S7041, each group of equivalent wind speeds of the impeller surface is divided to obtain a plurality of wind speed intervals.

[0115] For example, each group of equivalent wind speeds of the impeller surface is classified into one interval (such as 0.5-1.5 m / s, 1.5-2.5 m / s) starting from 0.5 m / s per 1 m / s according to the average wind speed, and the equivalent wind speeds of the impeller surface of m wind speed intervals are obtained respectively.

[0116] ​Step S7042, according to the Weibull distribution parameters, the cumulative probability density corresponding to multiple wind speed intervals in each group of impeller face equivalent wind speed is analyzed to obtain a cumulative probability density function.

[0117] Exemplarily, the formula for determining the cumulative probability density function is as follows:

[0118]

[0119] wherein, W k (i) is the cumulative probability density function corresponding to the i th wind speed interval in the k th group of impeller face equivalent wind speed, C k is the scale parameter of the k th group of impeller face equivalent wind speed, B k is the shape parameter of the k th group of impeller face equivalent wind speed.

[0120] Step S7043, according to the number of each group of impeller face equivalent wind speed and the total number of impeller face equivalent wind speed, the wind direction frequency of each group of impeller face equivalent wind speed is determined.

[0121] Step S7044, according to the cumulative probability density function, the probability difference of multiple wind speed intervals in each group of impeller face equivalent wind speed is analyzed to obtain a wind speed interval probability difference.

[0122] Step S7045, according to the wind direction frequency of each group of impeller face equivalent wind speed, the wind speed interval probability difference corresponding to multiple wind speed intervals in multiple groups of impeller face equivalent wind speed and the power generation power in the preset wind speed power curve corresponding to each wind speed interval are weighted and summed to obtain a power generation contribution value.

[0123] wherein, the preset wind speed power curve is the power generation power corresponding to different wind speeds of the target wind turbine, which is obtained from the technical specification of the target wind turbine, and exemplarily, as shown in FIG. 4, it is a schematic diagram of the preset wind speed power curve, the horizontal coordinate is wind speed, the unit is m / s, and the vertical coordinate is power, the unit is KW. Figure 8

[0124] Step S7046, according to the product of the power generation contribution value and the annual hours, the annual power generation of the target wind turbine is obtained.

[0125] Exemplarily, the formula for determining the annual power generation of the target wind turbine is as follows:

[0126]

[0127] wherein, E is the annual power generation of the target wind turbine, H is the annual hours, which can be 8760h, F k is the wind direction frequency of the k th group of impeller face equivalent wind speed, W k ​(i) is the cumulative probability density function corresponding to the i-th wind speed interval of the k-th group of equivalent wind speed of the rotor surface, and P(i) is the power generation of the target wind turbine in the i-th wind speed interval of the preset wind speed power curve.

[0128] Exemplarily, the annual power generation of the target wind turbine determined according to the embodiment of the present application is 14.048 million kWh (kilowatt-hour).

[0129] In the embodiment, a method for determining the power generation of a wind turbine is provided, which can be used in a computer device, Figure 9 is a flowchart of still another method for determining the power generation of a wind turbine according to the embodiment of the present application, as shown in the figure, the flow includes the following steps: Figure 9

[0130] data acquisition; determining the atmospheric stability related parameters; determining the wind speed vertical variation function; determining the equivalent wind speed of the rotor surface; grouping the equivalent wind speed of the rotor surface according to the wind direction and determining the wind direction frequency of each group; dividing the wind speed intervals and determining the Weibull distribution parameters; determining the annual power generation of the wind turbine.

[0131] In the embodiment, a device for determining the power generation of a wind turbine is also provided, which is used to implement the above-mentioned embodiments and preferred embodiments, and will not be described here. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware, or a combination of software and hardware is also possible and contemplated.

[0132] The embodiment provides a device for determining the power generation of a wind turbine, as shown in the figure, comprising: Figure 10

[0133] The wind speed variation law analysis module 1001 is configured to obtain the atmospheric stability parameters of the target wind turbine in a preset proposed area, analyze the wind speed variation law of the preset proposed area according to the target characteristic parameters of the target wind turbine and the atmospheric stability parameters, and obtain the wind speed vertical variation function; the target characteristic parameters of the target wind turbine are used to represent the effect of the geometric configuration of the target wind turbine and the underlying surface environment on the wind farm; the wind speed vertical variation function is used to represent the law of the variation of the wind speed with the vertical height variable under the influence of the atmospheric stability and the target characteristic parameters.

[0134] The rotor surface wind speed analysis module 1002 is configured to analyze the wind speed of the rotor surface of the target wind turbine according to the unit geometric parameters of the target wind turbine, the atmospheric stability parameters and the wind speed vertical variation function, and obtain the equivalent wind speed of the rotor surface.

[0135] ​​The Weibull distribution analysis module 1003 is configured to determine Weibull distribution parameters corresponding to the equivalent wind speed of the impeller surface according to the equivalent wind speed of the impeller surface, and the Weibull distribution parameters are used to represent the probability distribution of the equivalent wind speed of the impeller surface.

[0136] The annual power generation determination module 1004 is configured to determine the annual power generation of the target wind turbine according to the Weibull distribution parameters, a preset wind speed-power curve of the target wind turbine, and a wind direction frequency determined according to the equivalent wind speed of the impeller surface.

[0137] In some optional embodiments, the wind speed variation law analysis module 1001 comprises:

[0138] The friction velocity determination unit is configured to determine the friction velocity according to the wind speed fluctuation amount of the horizontal average wind direction of the preset region to be built, the covariance of the wind speed fluctuation amount of the horizontal direction perpendicular to the average wind direction and the wind speed fluctuation amount of the vertical direction.

[0139] The Obukhov length determination unit is configured to determine the Obukhov length according to the friction velocity, the temperature fluctuation amount, and the wind speed fluctuation amount of the vertical direction.

[0140] The wind speed standard deviation determination unit is configured to square the variance of the wind speed fluctuation amount of the horizontal average wind direction to obtain the wind speed standard deviation of the horizontal average wind direction.

[0141] In some optional embodiments, the wind speed variation law analysis module 1001 further comprises:

[0142] The Coriolis parameter determination unit is configured to determine the Coriolis parameter according to the latitude of the wind measurement tower in the preset region to be built and the earth rotation angular velocity.

[0143] The mid-layer mixing length determination unit is configured to combine the Coriolis parameter, the friction velocity, and the surface roughness to obtain the mid-layer mixing length.

[0144] The atmospheric boundary layer height determination unit is configured to determine the atmospheric boundary layer height according to the quotient of the friction velocity and the Coriolis parameter.

[0145] The turbulent scale parameter determination unit is configured to determine the turbulent scale parameter according to the quotient of the vertical height variable and the Obukhov length.

[0146] The target correction term determination unit is configured to correct the wind speed profile by using the turbulent scale parameter to obtain the target correction term.

[0147] The judgment unit is configured to determine whether the boundary layer is stable according to the vertical height variable and the Obukhov length.

[0148] The wind speed vertical variation function determining unit is configured to determine the wind speed vertical variation function according to the vertical height variable, the surface roughness, the Obukhov length, the atmospheric boundary layer height, the mid-layer mixing length, the hub height, and the horizontal average wind speed according to the stable stratification; and determine the wind speed vertical variation function according to the vertical height variable, the target correction term, the surface roughness, the Obukhov length, the atmospheric boundary layer height, the mid-layer mixing length, the hub height, and the horizontal average wind speed according to the unstable stratification.

[0149] In some optional embodiments, the rotor plane wind speed analysis module 1002 comprises:

[0150] The height interval determining unit is configured to determine the height interval according to the rotor radius and the hub height in the unit geometry parameters of the target wind turbine.

[0151] The weighted integral result determining unit is configured to perform weighted integral on the wind speed vertical variation function and the wind speed standard deviation of the horizontal average wind direction in the atmospheric stability parameter according to the height interval, to obtain the weighted integral result.

[0152] The rotor plane equivalent wind speed determining unit is configured to average and power process the weighted integral result according to the rotor radius, to obtain the rotor plane equivalent wind speed.

[0153] In some optional embodiments, the Weibull distribution analysis module 1003 comprises:

[0154] The relative standard deviation determining unit is configured to group the rotor plane equivalent wind speed according to the average wind direction data, analyze the fluctuation degree of each group of rotor plane equivalent wind speed, and obtain the relative standard deviation.

[0155] The power correction unit is configured to power correct the relative standard deviation, to obtain the shape parameter.

[0156] The scale parameter determining unit is configured to obtain the power mean of each group of rotor plane equivalent wind speed, and perform distribution correction processing on the power mean, to obtain the scale parameter.

[0157] In some optional embodiments, the annual energy production determining module 1004 comprises:

[0158] The interval dividing unit is configured to divide each group of rotor plane equivalent wind speed, to obtain a plurality of wind speed intervals.

[0159] The probability density analysis unit is configured to analyze the cumulative probability density corresponding to the plurality of wind speed intervals in each group of rotor plane equivalent wind speed according to the Weibull distribution parameters, to obtain the cumulative probability density function.

[0160] The wind direction frequency determination unit is configured to determine the wind direction frequency of each group of blade surface equivalent wind speeds according to the number of blade surface equivalent wind speeds in each group and the total number of blade surface equivalent wind speeds.

[0161] The probability difference analysis unit is configured to analyze the probability difference of multiple wind speed intervals in each group of blade surface equivalent wind speeds according to the cumulative probability density function, to obtain the wind speed interval probability difference.

[0162] The contribution value determination unit is configured to weight and sum the product of the wind speed interval probability difference corresponding to the multiple wind speed intervals in the multiple groups of blade surface equivalent wind speeds and the power generation power in the preset wind speed power curve corresponding to each wind speed interval according to the wind direction frequency of each group of blade surface equivalent wind speeds, to obtain the power generation contribution value.

[0163] The annual power generation determination unit is configured to obtain the annual power generation of the target wind turbine according to the product of the power generation contribution value and the annual hours.

[0164] Further function description of the above-mentioned various modules and units is the same as that of the corresponding embodiments, and will not be repeated here.

[0165] The wind turbine power generation determination device in the embodiment is in the form of a functional unit, and the unit herein refers to an ASIC (Application Specific Integrated Circuit, Application Specific Integrated Circuit) circuit, a processor and a memory executing one or more software or fixed programs, and / or other devices that can provide the above-mentioned functions.

[0166] The embodiment of the present application also provides a computer device with the wind turbine power generation determination device shown in the above-mentioned Figure 10 .

[0167] Please refer to Figure 11 , Figure 11 is a structural schematic diagram of a computer device provided by an optional embodiment of the present application, as shown in Figure 11As shown, the computer device includes one or more processors 1110, memory 1120, and interfaces 1130 for external devices such as a keyboard and a mouse and a disk. The one or more processors 1110 can be a single-core processor or a plurality of processors suitable for the parallel processing of information. The one or more memory 1120 can include a single storage device or a plurality of storage devices such as disk drives. In some embodiments, the one or more memory 1120 can include a volatile memory or a non-volatile memory. In some embodiments, the one or more memory 1120 can include a memory buffer for storing data. The one or more interfaces 1130 can include a wired interface or a wireless interface. The one or more interfaces 1130 can transmit and / or receive data, control signaling, or both. Figure 11 The processor 1110 is used as an example in the embodiments.

[0168] The processor 1110 can be a central processing unit, a network processor, or a combination thereof. The processor 1110 can further include a hardware chip. The hardware chip can be an application specific integrated circuit, a programmable logic device, or a combination thereof. The programmable logic device can be a complex programmable logic device, a field programmable logic device, a general array logic, or any combination thereof.

[0169] The memory 1120 stores instructions executable by the at least one processor 1110, so that the at least one processor 1110 performs the method shown in the above embodiments.

[0170] The memory 1120 can include a program region and a data region. The program region can store an operating system and an application required by at least one function. The data region can store data created according to the use of the computer device. In addition, the memory 1120 can include a high-speed random access memory, and can further include a non-transitory memory such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state memory device. In some alternative embodiments, the memory 1120 can optionally include a memory disposed remotely with respect to the processor 1110, and these remote memories can be connected to the computer device through a network. Examples of the network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0171] The memory 1120 can include a volatile memory such as a random access memory, and can also include a non-volatile memory such as a flash memory, a hard disk, or a solid state disk. The memory 1120 can further include a combination of the above-mentioned memories.

[0172] The computer device also includes a communication interface 1130 for the computer device to communicate with other devices or communication networks.

[0173] The embodiments of the present application further provide a computer readable storage medium, and the method according to the embodiments of the present application can be implemented in hardware, firmware, or recorded in a storage medium, or be implemented as computer code originally stored in a remote storage medium or non-transitory machine readable storage medium and downloaded to a local storage medium and stored in the local storage medium, so that the method described herein can be processed by such software on a storage medium using a general purpose computer, a special purpose processor, or programmable or special purpose hardware. The storage medium can be a magnetic disk, an optical disk, a read-only memory, a random access memory, a flash memory, a hard disk, or a solid state disk, etc. Further, the storage medium can also include a combination of the above-mentioned types of memories. It can be understood that the computer, the processor, the microprocessor controller, or the programmable hardware includes a storage component that can store or receive software or computer code, when the software or computer code is accessed and executed by the computer, the processor, or the hardware, the method shown in the above embodiments is implemented.

[0174] Part of the present application can be applied as a computer program product, for example, computer program instructions, when executed by a computer, through the operation of the computer, the method and / or technical solutions according to the present application can be invoked or provided. Those skilled in the art should understand that the form of computer program instructions in a computer readable medium includes but is not limited to source files, executable files, installation package files, etc. Correspondingly, the way of computer program instructions executed by a computer includes but is not limited to: the computer directly executes the instructions, or the computer executes the corresponding compiled program after compiling the instructions, or the computer reads and executes the instructions, or the computer reads and installs the instructions and then executes the corresponding installed program. Here, the computer readable medium can be any available computer readable storage medium or communication medium accessible to the computer.

[0175] Although the embodiments of the present application are described in conjunction with the accompanying drawings, various modifications and changes can be made by those skilled in the art without departing from the spirit and scope of the present application, and such modifications and changes fall within the scope defined by the appended claims.

Claims

1. A method for determining the power generation of a wind turbine generator, characterized in that, The method includes: Atmospheric stability parameters of the target wind turbine in a pre-defined construction area are obtained. Based on the target characteristic parameters of the target wind turbine and the atmospheric stability parameters, the wind speed variation pattern in the pre-defined construction area is analyzed to obtain a vertical wind speed variation function. The target characteristic parameters of the target wind turbine are used to characterize the effect of the geometric configuration of the target wind turbine and the underlying surface environment on the wind farm. The vertical wind speed variation function is used to characterize the variation of wind speed with vertical height under the influence of atmospheric stability and the target characteristic parameters. Based on the unit geometric parameters of the target wind turbine, the atmospheric stability parameters, and the vertical wind speed variation function, the wind speed on the rotor surface of the target wind turbine is analyzed to obtain the equivalent wind speed on the rotor surface. Based on the equivalent wind speed on the impeller surface, the Weibull distribution parameters corresponding to the equivalent wind speed on the impeller surface are determined; the Weibull distribution parameters are used to characterize the probability distribution of the equivalent wind speed on the impeller surface. The annual power generation of the target wind turbine is determined based on the Weibull distribution parameters, the preset wind speed-power curve of the target wind turbine, and the wind direction frequency determined based on the equivalent wind speed of the rotor surface.

2. The method according to claim 1, characterized in that, The atmospheric stability parameters include Obukhov length, friction velocity, and standard deviation of wind speed in the horizontal mean wind direction; obtaining the atmospheric stability parameters of the target wind turbine in the preset proposed construction area includes: The friction speed is determined based on the covariance between the wind speed fluctuation in the horizontal average wind direction of the preset proposed area, the wind speed fluctuation in the horizontal direction perpendicular to the average wind direction, and the wind speed fluctuation in the vertical direction. The Obukhov length is determined based on the friction speed, temperature fluctuation, and vertical wind speed fluctuation. The standard deviation of wind speed in the horizontal average wind direction is obtained by taking the square root of the variance of the wind speed fluctuation in the horizontal average wind direction.

3. The method according to claim 2, characterized in that, The step involves analyzing the wind speed variation pattern of the pre-designed area based on the target characteristic parameters of the target wind turbine and the atmospheric stability parameters to obtain a vertical wind speed variation function, including: The Coriolis parameters are determined based on the latitude of the wind measurement tower in the pre-defined proposed area and the Earth's rotation angular velocity. The Coriolis parameter, the friction velocity, and the surface roughness are combined to obtain the intermediate mixing length; The atmospheric boundary layer height is determined based on the quotient of the friction velocity and the Coriolis parameter. The turbulence scale parameters are determined based on the quotient of the vertical height variable and the Obukhov length. The wind speed profile is corrected using the turbulence scale parameters to obtain the target correction term; Based on the vertical height variable and the Obukhov length, determine whether the stratum is stable; If the stratum is stable, the vertical wind speed variation function is determined based on the vertical height variable, the surface roughness, the Obukhov length, the atmospheric boundary layer height, the mid-level mixing length, the hub height, and the horizontal average wind speed. If the stratum is unstable, the vertical variation function of wind speed is determined based on the vertical height variable, the target correction term, the surface roughness, the Obukhov length, the atmospheric boundary layer height, the mid-level mixing length, the hub height, and the horizontal average wind speed.

4. The method according to claim 2, characterized in that, The step of analyzing the wind speed on the rotor surface of the target wind turbine based on the turbine's geometric parameters, atmospheric stability parameters, and the vertical wind speed variation function to obtain the equivalent wind speed on the rotor surface includes: The height range is determined based on the rotor radius and hub height in the geometric parameters of the target wind turbine unit; Based on the height range, a weighted integral is obtained by using the vertical variation function of wind speed and the standard deviation of wind speed in the horizontal mean wind direction in the atmospheric stability parameters. Based on the impeller radius, the weighted integral result is averaged and exponentially processed to obtain the equivalent wind speed on the impeller surface.

5. The method according to any one of claims 1 to 4, characterized in that, The Weibull distribution parameters include shape parameters and scale parameters; the Weibull distribution parameters corresponding to the equivalent wind speed on the impeller surface are determined based on the equivalent wind speed on the impeller surface. The Weibull distribution parameters are used to characterize the probability distribution of the equivalent wind speed on the impeller surface, including: The equivalent wind speed of the impeller surface is grouped according to the average wind direction data, and the fluctuation of the equivalent wind speed of the impeller surface in each group is analyzed to obtain the relative standard deviation. The shape parameters are obtained by power-law correction of the relative standard deviation. Obtain the power-law mean of the equivalent wind speed on the impeller surface for each group, and perform distribution correction processing on the power-law mean to obtain the scale parameter.

6. The method according to claim 5, characterized in that, The step of determining the annual power generation of the target wind turbine based on the Weibull distribution parameters, the preset wind speed-power curve of the target wind turbine, and the wind direction frequency determined based on the equivalent wind speed of the rotor surface includes: The equivalent wind speed of each group of impeller surfaces is divided to obtain multiple wind speed intervals; Based on the Weibull distribution parameters, the cumulative probability density corresponding to multiple wind speed intervals in each group of equivalent wind speeds on the impeller surface is analyzed to obtain the cumulative probability density function; Based on the number of equivalent wind velocities on the impeller surface in each group and the total number of equivalent wind velocities on the impeller surface, determine the wind direction frequency of the equivalent wind velocities on the impeller surface in each group; The probability difference of multiple wind speed intervals in each group of equivalent wind speeds on the impeller surface is analyzed based on the cumulative probability density function to obtain the wind speed interval probability difference. Based on the wind direction frequency of the equivalent wind speed of each group of impeller surfaces, the product of the probability difference of the wind speed intervals corresponding to multiple wind speed intervals in the multiple groups of equivalent wind speeds of impeller surfaces and the power generation in the preset wind speed power curve corresponding to each wind speed interval is weighted and summed to obtain the power generation contribution value. The annual power generation of the target wind turbine is obtained by multiplying the power generation contribution value by the number of hours per year.

7. A device for determining the power generation of a wind turbine generator set, characterized in that, The device includes: The wind speed variation analysis module is used to obtain the atmospheric stability parameters of the target wind turbine in the preset construction area. Based on the target characteristic parameters of the target wind turbine and the atmospheric stability parameters, the module analyzes the wind speed variation pattern in the preset construction area to obtain the vertical wind speed variation function. The target characteristic parameters of the target wind turbine are used to characterize the effect of the geometric configuration of the target wind turbine and the underlying surface environment on the wind farm. The vertical wind speed variation function is used to characterize the variation of wind speed with vertical height under the influence of atmospheric stability and the target characteristic parameters. The impeller surface wind speed analysis module is used to analyze the wind speed on the impeller surface of the target wind turbine based on the unit geometric parameters, the atmospheric stability parameters, and the vertical wind speed variation function, and to obtain the equivalent wind speed on the impeller surface. The Weibull distribution analysis module is used to determine the Weibull distribution parameters corresponding to the equivalent wind speed on the impeller surface based on the equivalent wind speed on the impeller surface; the Weibull distribution parameters are used to characterize the probability distribution of the equivalent wind speed on the impeller surface. The annual power generation determination module is used to determine the annual power generation of the target wind turbine based on the Weibull distribution parameters, the preset wind speed-power curve of the target wind turbine, and the wind direction frequency determined based on the equivalent wind speed of the rotor surface.

8. A computer device, characterized in that, include: A memory and a processor are interconnected, the memory stores computer instructions, and the processor executes the computer instructions to perform the method for determining the power generation of the wind turbine as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to execute the method for determining the power generation of the wind turbine generator as described in any one of claims 1 to 6.

10. A computer program product, characterized in that, Includes computer instructions for causing a computer to execute the method for determining the power generation of a wind turbine as described in any one of claims 1 to 6.

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