阅读说明：本技术 风力发电机组对风不正校正方法、装置及控制器 (Wind misalignment correction method and device for wind driven generator group and controller ) 是由 钟慧超 杨勇 江容 于 2020-11-12 设计创作，主要内容包括：本申请公开了一种风力发电机组对风不正校正方法、装置及控制器,属于风力发电领域。该风力发电机组对风不正校正方法包括：采集一段时间内的多组偏航数据；按照风速划分多个风速区,针对每个风速区,对风速和运行功率进行拟合,得到第一拟合函数关系；利用风速区的端点值和第一拟合函数关系,对运行功率进行补偿,得到补偿后的运行功率；对风速区对应的补偿后的运行功率和对风角进行拟合,得到第二拟合函数关系；基于多个风速区对应的第二拟合函数关系和预设的对风角计算函数关系,得到目标对风角,并根据目标对风角执行偏航动作。根据本申请实施例能够降低或避免风力发电机组发电量的损失。(The application discloses a wind misalignment correction method, device and controller for a wind driven generator group, and belongs to the field of wind power generation. The wind misalignment correction method for the wind driven generator set comprises the following steps: collecting a plurality of groups of yaw data in a period of time; dividing a plurality of wind speed areas according to wind speed, and fitting the wind speed and the operating power aiming at each wind speed area to obtain a first fitting functional relation; compensating the operating power by using an endpoint value of the wind speed area and a first fitting function relation to obtain compensated operating power; fitting the compensated operating power and the wind angle corresponding to the wind speed area to obtain a second fitting functional relation; and calculating a functional relation based on the second fitting functional relations corresponding to the plurality of wind speed areas and a preset wind angle to obtain a target wind angle, and executing a yawing action according to the target wind angle. According to the embodiment of the application, the loss of the power generation amount of the wind generating set can be reduced or avoided.)

1. A wind power generation unit wind misalignment correction method is characterized by comprising the following steps:

collecting a plurality of groups of yaw data in a period of time, wherein each group of yaw data comprises wind speed, operating power of a wind generating set and a wind angle of the wind generating set;

dividing a plurality of wind speed areas according to wind speed, and fitting the wind speed and the operating power aiming at each wind speed area to obtain a first fitting functional relation;

compensating the operating power by using an endpoint value of the wind speed area and the first fitting function relation to obtain the compensated operating power;

fitting the compensated operating power and the wind angle corresponding to the wind speed area to obtain a second fitting functional relation;

and calculating a functional relation based on the second fitting functional relations corresponding to the plurality of wind speed areas and a preset wind angle to obtain a target wind angle, and executing a yaw action according to the target wind angle.

2. The method of claim 1, wherein the compensating the operating power using the endpoint values of the wind speed zone and the first fitted functional relationship to obtain the compensated operating power comprises:

calculating an average value of endpoint values of the wind speed area;

calculating to obtain compensation power by using the average value and the first fitting function relation;

calculating to obtain first power by utilizing the wind speed in the yaw data corresponding to the wind speed area and the first fitting function relation;

and determining a difference value between the operating power and a first power difference in the yaw data corresponding to the wind speed area as the compensated operating power, wherein the first power difference is the difference value between the first power and the compensated power.

3. The method according to claim 1, wherein the calculating a functional relationship based on the second fitted functional relationship corresponding to the plurality of wind speed regions and a preset wind angle to obtain a target wind angle comprises:

calculating a functional relation by using the second fitting functional relation corresponding to each wind speed area and a preset wind angle, and calculating to obtain a first wind angle corresponding to each wind speed area;

and obtaining the target wind subtending angle based on the first wind subtending angle corresponding to each wind speed area and the operating power corresponding to each wind speed area.

4. The method of claim 3, wherein calculating a functional relationship to wind angle comprises: the operating power is the product of the preset maximum power and a first cosine function value under the wind speed, the first cosine function value is a cosine function value of the n-th power of the wind angle, and n is a preset power coefficient;

the calculating a function relationship by using the second fitting function relationship corresponding to each wind speed area and a preset wind angle to obtain a first wind angle corresponding to each wind speed area includes:

calculating a quotient value of a derivative of the second fitting function relation corresponding to each wind speed zone and the second fitting function relation under a preset standard wind angle condition;

and calculating a functional relation by utilizing the quotient corresponding to each wind speed area and the wind angle to obtain a first wind angle corresponding to each wind speed area.

5. The method of claim 3, wherein the target wind angle comprises a quotient of a first sum and a second sum, the first sum being a product of a first wind angle and a third sum for each of the wind speed zones, the third sum for each of the wind speed zones being a sum of the operating power in the yaw data for each of the wind speed zones, the second sum being a sum of the third sums for each of the wind speed zones.

6. The method of claim 1, further comprising, prior to said partitioning the plurality of wind speed zones by wind speed:

selecting a target sliding window and a target window moving step length;

based on the target sliding window and the target window moving step length, acquiring the minimum value and/or the average value of the yaw data in the target sliding window moving each time in a plurality of groups of yaw data arranged according to the acquisition time;

and screening multiple groups of yaw data according to the minimum value and/or average value of the yaw data in the target sliding window and a preset first screening condition, and determining the retained yaw data.

7. The method of claim 1, wherein the first screening condition comprises one or both of:

the minimum value and/or the average value of the yaw data in the target sliding window meet the normal grid-connected operation condition of the wind generating set, and the yaw data of the group are reserved;

and the average value of the yaw data in the target sliding window is positioned in the running power preset range, the group of yaw data is reserved, the minimum value of the running power preset range is a limited power threshold value, and the maximum value of the running power preset range is a full power threshold value.

8. The method of claim 6, wherein the yaw data further includes a blade pitch angle,

the method further comprises the following steps:

screening multiple groups of yaw data according to the blade pitch angle in the target sliding window and a preset second screening condition, and determining the retained yaw data;

the second screening condition includes:

and the change of the blade variable pitch angle in the target sliding window is not 0, or the blade variable pitch angle in the target sliding window is larger than or equal to a preset blade variable pitch angle threshold value, and the group of yaw data is reserved.

9. The method of claim 6, wherein the selecting the target sliding window and the target window moving step comprises:

selecting a plurality of groups of sliding windows and window moving step lengths;

obtaining the average value of the wind speed and the average value of the running power in the sliding window corresponding to each group of sliding windows and window moving step length according to each group of sliding windows and window moving step length;

and respectively determining the sliding window and the window moving step length with the highest covariance of the average value of the wind speed and the average value of the running power in the sliding window as the target sliding window and the target window moving step length.

10. A wind power generation unit is to wind misalignment correcting device which characterized in that includes:

the system comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for acquiring a plurality of groups of yaw data in a period of time, and each group of yaw data comprises wind speed, operating power of a wind generating set and a wind angle of the wind generating set;

the first calculation module is used for dividing a plurality of wind speed areas according to wind speeds, and fitting the wind speeds and the operating power aiming at each wind speed area to obtain a first fitting functional relation;

the second calculation module is used for compensating the operating power by using the endpoint value of the wind speed area and the first fitting function relation to obtain the compensated operating power;

the third calculation module is used for fitting the compensated operating power and the wind angle corresponding to the wind speed area to obtain a second fitting functional relation;

the fourth calculation module is used for calculating a functional relation based on the second fitting functional relations corresponding to the plurality of wind speed areas and a preset wind angle to obtain a target wind angle;

and the yaw control module is used for executing yaw action on the wind angle according to the target.

11. A wind generating set controller, comprising: a processor and a memory storing computer program instructions;

the processor, when executing the computer program instructions, implements a wind park misalignment correction method according to any of claims 1 to 9.

Technical Field

The application belongs to the field of wind power generation, and particularly relates to a wind misalignment correction method and device for a wind driven generator set and a controller.

Background

During operation of the wind turbine generator system, the wind direction may change. In order to improve the generating efficiency of the wind generating set, the wind generating set can yaw to adjust the impeller of the wind generating set to be in a windward state.

In the yawing process of the wind generating set, a certain relation exists between the power loss factor and the deviation of the wind angle. For example, if the deviation of the wind direction angle is not 0, the power of the wind turbine generator is lost to some extent. The wind vane is one of the key parts of the wind generator set to wind, and the wind vane can influence the yaw accuracy. The wind vane is not correct to wind due to the problems of installation error of the wind vane, looseness of the wind vane, influence of wake flow of blades of a wind generating set, zero drift of the wind vane, abnormal wind direction measuring quantity loop and the like. The wind vane is not correct to wind, so that a certain deviation exists between the actual wind alignment angle and the corresponding wind angle of the wind generating set in the yawing process, the wind generating set cannot operate at the optimal generating efficiency, and the generated energy of the wind generating set is lost.

Disclosure of Invention

The embodiment of the application provides a wind misalignment correction method, a wind misalignment correction device and a wind misalignment correction controller for a wind generating set, and the loss of the generating capacity of the wind generating set can be reduced or avoided.

In a first aspect, an embodiment of the present application provides a wind misalignment correction method for a wind turbine generator set, including: collecting a plurality of groups of yaw data in a period of time, wherein each group of yaw data comprises wind speed, operating power of a wind generating set and a wind angle of the wind generating set; dividing a plurality of wind speed areas according to wind speed, and fitting the wind speed and the operating power aiming at each wind speed area to obtain a first fitting functional relation; compensating the operating power by using an endpoint value of the wind speed area and a first fitting function relation to obtain compensated operating power; fitting the compensated operating power and the wind angle corresponding to the wind speed area to obtain a second fitting functional relation; and calculating a functional relation based on the second fitting functional relations corresponding to the plurality of wind speed areas and a preset wind angle to obtain a target wind angle, and executing a yawing action according to the target wind angle.

In a second aspect, an embodiment of the present application provides a wind misalignment correction device for a wind turbine generator group, including: the system comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for acquiring a plurality of groups of yaw data in a period of time, and each group of yaw data comprises wind speed, operating power of a wind generating set and wind angle of the wind generating set; the first calculation module is used for dividing a plurality of wind speed areas according to wind speeds, and fitting the wind speeds and the operating power aiming at each wind speed area to obtain a first fitting functional relation; the second calculation module is used for compensating the operating power by using the endpoint value of the wind speed area and the first fitting function relation to obtain the compensated operating power; the third calculation module is used for fitting the compensated operating power and the wind angle corresponding to the wind speed area to obtain a second fitting functional relation; the fourth calculation module is used for calculating a functional relation based on second fitting functional relations corresponding to the plurality of wind speed areas and a preset wind angle to obtain a target wind angle; and the yaw control module is used for executing yaw action on the wind angle according to the target.

In a third aspect, an embodiment of the present application provides a wind generating set controller, including: a processor and a memory storing computer program instructions; the processor, when executing the computer program instructions, implements the wind power generation group wind misalignment correction method of the first aspect.

The embodiment of the application provides a wind misalignment correction method, a wind misalignment correction device and a wind misalignment correction controller for a wind driven generator set, and multiple groups of yaw data in a period of time are collected. Dividing a plurality of wind speed areas according to wind speeds in yaw data, fitting the wind speed and the operating power in the yaw data for the yaw data corresponding to each wind speed area, compensating the operating power, fitting the compensated operating power and the wind angle in the yaw data, and synthesizing a second fitting functional relation corresponding to the plurality of wind speed areas and a preset wind angle calculation functional relation to obtain a target wind angle serving as a basis for executing a yaw action. Through twice fitting and compensation, the influence of the wind speed on the yaw data is reduced, the error of the target wind angle obtained as the basis for executing the yaw action is reduced, and the accuracy of the target wind angle is improved. The target is utilized to execute yawing action on the wind angle, so that the wind generating set can run at the optimal generating efficiency or close to the optimal generating efficiency, and the loss of the generating capacity of the wind generating set is reduced or avoided.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments of the present application will be briefly described below, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.

FIG. 1 is a flow chart of an embodiment of a wind turbine generator group wind misalignment correction method according to a first aspect of the present disclosure;

FIG. 2 is a schematic diagram illustrating an example of a functional relationship between compensated operating power and a wind angle for a plurality of wind speed zones according to an embodiment of the present disclosure;

FIG. 3 is a flow chart of another embodiment of a wind turbine generator group wind misalignment correction method provided by the first aspect of the present application;

FIG. 4 is a flow chart of a wind turbine generator group wind misalignment correction method according to a first aspect of the present application;

FIG. 5 is a diagram illustrating an example of moving a sliding window according to a window moving step in an embodiment of the present application;

fig. 6 is a schematic diagram of another example of moving a sliding window by window moving steps in the embodiment of the present application;

FIG. 7 is a schematic structural diagram of an embodiment of a wind misalignment correction device for a wind turbine generator set according to a second aspect of the present application;

FIG. 8 is a schematic structural diagram of another embodiment of a wind turbine generator set wind misalignment correction device according to a second aspect of the present application;

fig. 9 is a schematic structural diagram of an embodiment of a wind generating set controller according to a third aspect of the present application.

Detailed Description

Features and exemplary embodiments of various aspects of the present application will be described in detail below, and in order to make objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are intended to be illustrative only and are not intended to be limiting. It will be apparent to one skilled in the art that the present application may be practiced without some of these specific details. The following description of the embodiments is merely intended to provide a better understanding of the present application by illustrating examples thereof.

In the operation process of the wind generating set, in order to improve the generating efficiency of the wind generating set, yawing is carried out according to the actual wind direction, and an impeller of the wind generating set is in a windward state. Specifically, the wind vane can be used for carrying out wind alignment to obtain a wind alignment angle, and the wind alignment angle is used for carrying out yaw. The deviation of the wind angle has a certain relation with the power loss of the wind generating set. And under the condition that the deviation of the wind angle is not 0, the power of the wind generating set has certain loss. The wind vane may have the problem of wind misalignment, which causes deviation of the obtained wind alignment angle, reduces the yaw accuracy, and enables the wind generating set not to operate at the optimal generating efficiency, thereby causing the loss of the generating capacity of the wind generating set.

The application provides a wind misalignment correction method, a wind misalignment correction device and a wind misalignment correction controller for a wind driven generator set. According to accurate yaw of the wind angle, the yaw accuracy can be improved, and the wind generating set can run at the optimal generating efficiency or close to the optimal generating efficiency, so that the loss of the generating capacity of the wind generating set is reduced or avoided.

The wind turbine generator system provided in the first aspect of the present application will be described below with reference to a wind misalignment correction method. Fig. 1 is a flowchart of an embodiment of a wind turbine generator group wind misalignment correction method according to a first aspect of the present application. As shown in fig. 1, the wind turbine generator set wind misalignment correction method may include steps S101 to S105.

In step S101, a plurality of sets of yaw data over a period of time are acquired.

Each set of yaw data corresponds to a point in time during the period of time, i.e., a corresponding set of yaw data may be acquired at a point in time during the period of time. The duration of the period of time may be set according to specific work scenarios and work requirements, and is not limited herein, for example, the duration of the period of time may be 1 month.

Each set of yaw data may include wind speed, operating power of the wind turbine generator system, and wind angle of the wind turbine generator system. The wind angle of the wind turbine generator set in the yaw data may be a wind angle measured by a wind angle measuring device, and the wind angle measuring device is not limited herein. The set of yaw data may include a wind speed collected at a point in time, an operating power of the wind turbine, a wind angle of the wind turbine.

In step S102, a plurality of wind speed regions are divided according to wind speed, and for each wind speed region, the wind speed and the operating power are fitted to obtain a first fitting functional relationship.

The plurality of wind speed zones may be obtained by dividing according to the size of the wind speed, and the manner of dividing the wind speed zones and the range of each wind speed zone are not limited herein. For example, wind speeds in sets of yaw data acquired over a period of time range from v1 to v6, where v1 < v 6. V1 to v6 can be divided into five wind speed areas, wherein the five wind speed areas are respectively [ v1, v2 ], [ v2, v3 ], [ v3, v4 ], [ v4, v5 ] and [ v5, v6], wherein v1 < v2 < v3 < v4 < v5 < v 6.

Each wind speed zone may correspond to multiple sets of yaw data. The wind speed in each group of yaw data corresponding to each wind speed zone falls into the wind speed zone. And fitting the wind speed and the operating power in each group of yaw data corresponding to each wind speed area to obtain a first fitting functional relation. The first fitting functional relation is a functional relation between the wind speed and the running power obtained through fitting. Each wind speed zone corresponds to a first fitted functional relationship. The first fitted functional relationship may be different for different wind speed zones.

The fitting algorithm and functional form of the first fitting functional relationship are not limited herein. For example, the functional form of the first fitted functional relationship may specifically include a cubic function, and the fitting algorithm may include a least squares method.

In step S103, the operating power is compensated by using the endpoint value of the wind speed region and the first fitting function relationship, so as to obtain a compensated operating power.

The end point values of the wind speed zone comprise the two end point values of the range of wind speed zone representation, in particular the maximum value and the minimum value of the range of wind speed zone representation. For example, the endpoint values of the wind speed zone [ v1, v2) in the above example include v1 and v 2.

Wind changes of the surrounding environment of the wind generating set are various, and wind speed in yaw data may bring influences on accuracy of the yaw data. The end point value of the wind speed area can be utilized to compensate the operating power in the yaw data corresponding to the wind speed area, so that the influence of the wind speed on the yaw data is reduced. Specifically, the compensation power of the operating power can be calculated according to the endpoint value of the wind speed area and the first fitting function relationship, and the operating power in the yaw data is compensated by using the compensation power to obtain the compensated operating power. The influence of the wind speed on the compensated running power is reduced, and the accuracy is improved.

In step S104, the compensated operating power and the wind angle corresponding to the wind speed zone are fitted to obtain a second fitting functional relationship.

And for any wind speed area, fitting the compensated operating power corresponding to the wind speed area with the wind angle in the yaw data corresponding to the wind speed area to obtain a second fitting functional relation. The second fitting function relationship is a function relationship between the compensated operation power and the wind angle obtained through fitting. And each wind speed area corresponds to a second fitting function relation. The second fitted functional relationship may be different for different wind speed regions.

The fitting algorithm and functional form of the second fitting functional relationship are not limited herein. For example, the wind speed range defined by each wind speed zone is smaller than the wind speed range defined by the wind speeds in the plurality of sets of yaw data collected over a period of time, and the functional form of the first fitted functional relationship may specifically include a quadratic function.

For example, fig. 2 is a schematic diagram of an example of a functional relationship between compensated operating power and a wind angle corresponding to a plurality of wind speed zones in the embodiment of the present application. As shown in fig. 2, the abscissa is the wind direction angle in degrees; the ordinate is the compensated operating power in kilowatts. The eight function curves A1-A8 represent second fitted function relations corresponding to eight wind speed regions, and each function curve represents a second fitted function relation corresponding to one wind speed region.

In step S105, a functional relationship is calculated based on the second fitting functional relationships corresponding to the plurality of wind speed regions and a preset wind angle, so as to obtain a target wind angle, and a yaw action is performed according to the target wind angle.

For any wind speed area, calculating a functional relation by using a second fitting function corresponding to the wind speed area and a preset wind angle, and obtaining the wind angle with improved accuracy corresponding to the wind speed area. And integrating the wind alignment angles of the accuracy promotion corresponding to the plurality of wind speed areas to obtain a target wind alignment angle. The accuracy of the obtained target to the wind angle is high, and the target is utilized to yaw the wind angle, so that the yaw accuracy is improved.

In an embodiment of the present application, multiple sets of yaw data are acquired over a period of time. Dividing a plurality of wind speed areas according to wind speeds in yaw data, fitting the wind speed and the operating power in the yaw data for the yaw data corresponding to each wind speed area, compensating the operating power, fitting the compensated operating power and the wind angle in the yaw data, and synthesizing a second fitting functional relation corresponding to the plurality of wind speed areas and a preset wind angle calculation functional relation to obtain a target wind angle serving as a basis for executing a yaw action. Through twice fitting and compensation, the influence of the wind speed on the yaw data is reduced, the error of the target wind angle obtained as the basis for executing the yaw action is reduced, and the accuracy of the target wind angle is improved. The target is utilized to execute yawing action on the wind angle, so that the wind generating set can run at the optimal generating efficiency or close to the optimal generating efficiency, and the loss of the generating capacity of the wind generating set is reduced or avoided.

The following will describe specific implementations of the steps in the above embodiments. Fig. 3 is a flowchart of another embodiment of a wind turbine generator group wind misalignment correction method provided in the first aspect of the present application. Fig. 3 differs from fig. 1 in that step S103 in fig. 1 may be specifically detailed as step S1031 to step S1034 in fig. 3, and step S105 in fig. 1 may be specifically detailed as step S1051 and step S1052 in fig. 3.

In step S1031, the average of the endpoint values of the wind speed zone is calculated.

For any one wind speed zone, the average of the endpoint values for that wind speed zone is calculated. For example, for the wind velocity region [ v1, v2) in the above example, calculation is requiredFor the wind velocity region [ v2, v3) in the above example, calculation is required

In step S1032, the compensation power is calculated by using the average value and the first fitting function relationship.

And for any wind speed area, substituting the average value of the endpoint values of the wind speed area into the first fitting function relation to obtain the compensation power corresponding to the wind speed area. For example, the cubic function that can characterize the first fitting functional relationship obtained after fitting is shown as equation (1):

P(v)＝a₁×v³+b₁×v²+c₁×v+d₁ (1)

wherein P (v) is the operating power, v is the wind speed, a₁、b₁、c₁And d₁Are fitting coefficients.

End point values of the wind speed region include v_minAnd v_maxAverage value v of the endpoint values of the wind speed zone_middleIs composed ofCompensating power P (v)_middle) Can pass through a₁×v_middle ³+b₁×v_middle ²+c₁×v_middle+d₁And (4) calculating.

In step S1033, a first power is calculated by using the wind speed in the yaw data corresponding to the wind speed region and the first fitting function relationship.

And for any wind speed area, substituting the wind speed in the yaw data corresponding to the wind speed area into the first fitting function relation to obtain the first power corresponding to the wind speed in the yaw data. For example, the cubic function equation obtained after fitting and capable of characterizing the first fitting function relationship is as shown in the above equation (1), and the first power P (v)_real) Can pass through a₁×v_real ³+b₁×v_real ²+c₁×v_real+d₁And (4) calculating.

In step S1034, a difference between the operating power in the yaw data corresponding to the wind speed zone and the first power difference is determined as the compensated operating power.

The first power difference is a difference between the first power and the compensation power. For example, as in the above example, the compensated operating power may be calculated by equation (2);

P_compensation＝P_real-[P(v_real)-P(v_middle)] (2)

wherein, P_compensationFor compensated operating power, P_realOperating power, P (v), in yaw data corresponding to wind speed zones_real)-P(v_middle) Is the first power.

In step S1051, a first wind angle corresponding to each wind speed region is calculated by using the second fitting functional relationship corresponding to each wind speed region and a preset wind angle calculation functional relationship.

For example, the quadratic function that characterizes the second fitting function after fitting can be expressed as equation (3):

P(α)＝a₂×α²+b₂×α+c₁ (3)

and calculating a functional relation according to a second fitting functional relation corresponding to the wind speed area and a preset wind angle to obtain a first wind angle corresponding to a certain wind speed area. The preset wind angle calculation function relationship may include a function relationship between a wind angle and an operating power under a constant wind speed. Specifically, the preset wind angle calculation function relationship may include that the operation power is a product of a preset maximum power at the wind speed and a first cosine function value. The first cosine function value is a cosine function value of the n power of the wind angle, and n is a preset power coefficient. The preset wind angle calculation function relationship can be expressed by the following equation (4):

P(α)＝P₁×cos(α)ⁿ (4)

wherein P (alpha) is the operating power corresponding to the wind angle under the preset wind angle calculation function relationship, P₁The maximum power is preset at the wind speed in the wind speed area, and alpha is the wind angle. In equation (4), n is an unknown number.

And calculating the quotient of the derivative of the second fitting function relation corresponding to each wind speed area and the second fitting function relation under the condition of a preset standard wind angle. And calculating a functional relation by utilizing the quotient and the wind angle corresponding to each wind speed area to obtain a first wind angle corresponding to each wind speed area.

By calculating the derivative of the functional relationship to the wind angle and calculating the functional relationship itself to the wind angle, the normalized slope of the functional relationship to the wind angle can be calculated. For example, the wind angle calculation function may be as shown in equation (4) in the above example, and correspondingly, the normalized slope of the wind angle calculation function may be obtained according to equation (5) below:

wherein, K_pFor the normalized slope of the wind angle calculation function, P (α)' is the derivative of the wind angle calculation function, and the meanings of other parameters can be referred to the relevant descriptions in the above embodiments, which are not repeated herein.

For example, equation (6) can be obtained from equation (5), and the first wind angle of the wind speed region can be calculated by equation (6), where equation (6) is as follows:

wherein alpha is_rAt a first wind angle, K_pFor calculating the normalized slope of the functional relationship for the wind angle, the meanings of other parameters can be referred to the relevant description in the above embodiments, and are not repeated herein.

In order to be able to calculate the first wind angle of this wind speed region, a known K is required_pAnd the value of n. N may be assigned according to a specific work scenario and a work requirement, and is not limited herein. In some examples, n may take a value between 3 and 4.5. K can be obtained according to the quotient of the derivative of the second fitting function relation corresponding to each wind speed area and the second fitting function relation under the condition of the value of the preset standard wind angle_pThe value of (c). Specifically, the value of the standard wind angle may be substituted into the derivative of the second fitting function relationship corresponding to each wind speed region and the second fitting function relationship, and the quotient of the derivative of the second fitting function relationship substituted into the value of the standard wind angle and the second fitting function relationship may be used as the obtained K_pThe value of (c). The standard wind angle may be set according to the working scene and the working requirement, and is not limited herein. In some examples, the standard wind angle may be 180 °.

For example, K_pThe value of (c) can be obtained according to the following equation (7):

wherein, P (180 °) is a derivative value of the second fitting function relationship under the condition of 180 ° of the standard wind angle corresponding to the wind speed region, and P (180 °) is a value of the second fitting function relationship under the condition of 180 ° of the standard wind angle corresponding to the wind speed region.

K calculated according to equation (7)_pThe first diagonal angle of the wind speed zone can be obtained by substituting the value of (2) into the above equation (6).

In step S1052, a target wind angle is obtained based on the first wind angle corresponding to each wind speed zone and the operating power corresponding to each wind speed zone, and a yaw action is performed according to the target wind angle.

The target wind subtend angle can be obtained by utilizing a weighting algorithm based on the first wind subtend angle corresponding to each wind speed zone. The weight of the first wind angle corresponding to a certain wind speed zone in the weighting algorithm may be the sum of the operating powers in each set of yaw data corresponding to the wind speed zone.

Specifically, the target wind angle includes a quotient of the first sum and the second sum. The first sum is a product of the first diagonal angle and the third sum corresponding to each wind speed zone. The third summation corresponding to each wind speed zone is the summation of the operating power in the yaw data corresponding to each wind speed zone. The second sum is the sum of the third sums corresponding to each wind speed zone. For example, the first wind angle is calculated as shown in the above example as equation (6), and the target wind angle can be obtained according to the following equation (8):

wherein alpha is_combineIs a target wind angle, alpha_r,iA first wind angle P corresponding to the ith wind speed zone_iFor the third sum, Sigma P, corresponding to the ith wind speed zone_iFor the second addition, Σ (α)_r,i×P_i) Is the first addition.

In order to further improve the accuracy of the obtained first wind direction angle corresponding to each wind speed area and further improve the accuracy of the target wind direction angle, the yaw data can be processed through the target sliding window and the target window moving step length, the yaw data are screened according to the processed yaw data and preset screening conditions, and the first wind direction angle, the target wind direction angle and the like are calculated by using the yaw data reserved by screening in the subsequent calculation process.

Fig. 4 is a flowchart of a wind turbine generator group wind misalignment correction method according to a further embodiment of the present application. Fig. 4 is different from fig. 1 in that the wind generating set wind misalignment correction method shown in fig. 4 may further include steps S106 to S108.

In step S106, a target sliding window and a target window moving step are selected.

The target sliding window is a sliding window used for processing data in the embodiment of the application. The sliding window has a length, which may be a length of time. The target window moving step is a window moving step used for processing data in the embodiment of the present application. The window moving step length is the time length of each moving of the sliding window. For example, the length of the target sliding window may be 600 seconds, and the target window moving step may be 150 seconds.

In some examples, multiple sets of sliding windows and window movement steps may be taken. And obtaining the average value of the wind speed and the average value of the running power in the sliding window corresponding to each group of sliding windows and window moving step length according to each group of sliding windows and window moving step length. And respectively determining the sliding window and the window moving step length with the highest covariance of the average value of the wind speed and the average value of the running power in the sliding window as the target sliding window and the target window moving step length.

A set of sliding windows and window movement steps includes one sliding window and one window movement step. For example, five sets of sliding windows and window moving steps are selected, the first set includes sliding window B1 and window moving step C1, the second set includes sliding window B2 and window moving step C2, the third set includes sliding window B3 and window moving step C3, the fourth set includes sliding window B4 and window moving step C4, and the fifth set includes sliding window B5 and window moving step C5. At least one of the sliding window and the window moving step size is different in different groups.

In the process of selecting the target sliding window and the target window moving step, the wind speed and the operating power in the sliding window may be the wind speed and the operating power in the yaw data acquired in step S101, or may be the historical wind speed dedicated to selecting the target sliding window and the target window moving step and the operating power of the wind turbine generator corresponding to the historical wind speed, which is not limited herein.

And for a group of sliding windows and window moving step lengths, aligning one end of each sliding window with the starting point of the time corresponding to the wind speed and the operating power, and gradually moving the sliding windows according to the window moving step lengths until the other end of each sliding window moves to the end point of the time corresponding to the wind speed and the operating power. During the moving of the sliding window, the average value of the wind speed and the average value of the running power in each sliding window are calculated.

For example, fig. 5 is a schematic diagram of an example of moving a sliding window according to a window moving step in the embodiment of the present application. Fig. 6 is a schematic diagram of another example of moving the sliding window by the window moving step in the embodiment of the present application. As shown in fig. 5 and 6, 23 sets of wind speed and operating power are included in a period of 0 to 1100 seconds, and each point above the time axis represents the wind speed and operating power collected at that point in time on the time axis. For convenience of representation, the 23 points are labeled as D1 to D23 in order of time from small to large.

In fig. 5, the length of the sliding window is 600 seconds, the window moving step is 100 seconds, and the sliding window is moved five times in accordance with the window moving step in a period of 0 to 1100 seconds. The sliding window is located at the initial position, namely 0-600 seconds, the window comprises D1-D13, the average value of the wind speed corresponding to D1-D13 and the average value of the running power corresponding to D1-D13 are calculated; after the sliding window moves for the first time, namely 100 to 700 seconds, the window comprises D3 to D15, and the average value from the wind speed corresponding to D3 to the wind speed corresponding to D15 and the average value from the running power corresponding to D3 to the running power corresponding to D15 are calculated; after the sliding window is moved for the second time, namely 200 to 800 seconds, the window comprises D5 to D17, and the average value from the wind speed corresponding to D5 to the wind speed corresponding to D17 and the average value from the running power corresponding to D5 to the running power corresponding to D17 are calculated; and in analogy, 500 to 1100 seconds are obtained after the sliding window is moved for the fifth time, the window comprises D12 to D23, and the average value from the wind speed corresponding to D12 to the wind speed corresponding to D23 and the average value from the running power corresponding to D12 to the running power corresponding to D23 are obtained through calculation.

In fig. 6, the length of the sliding window is 500 seconds, the window moving step is 200 seconds, and the sliding window is moved three times in accordance with the window moving step in a period of 0 to 1100 seconds. The sliding window is located at the initial position, namely 0-500 seconds, D1-D11 are included in the window, and the average value from the wind speed corresponding to D1 to the wind speed corresponding to D11 and the average value from the running power corresponding to D1 to the running power corresponding to D11 are calculated; after the sliding window moves for the first time, namely 200 to 700 seconds, the window comprises D5 to D15, and the average value from the wind speed corresponding to D5 to the wind speed corresponding to D15 and the average value from the running power corresponding to D5 to the running power corresponding to D15 are calculated; after the sliding window is moved for the second time, namely 400 to 900 seconds, the window comprises D9 to D19, and the average value from the wind speed corresponding to D9 to the wind speed corresponding to D19 and the average value from the running power corresponding to D9 to the running power corresponding to D19 are calculated; and after the sliding window is moved for the third time, namely 600 to 1100 seconds, the window comprises D9 to D19, and the average value from the wind speed corresponding to D14 to the wind speed corresponding to D23 and the average value from the running power corresponding to D14 to the running power corresponding to D23 are calculated.

The higher the covariance of the average value of the wind speed and the average value of the running power corresponding to a group of sliding windows and window moving steps is, the higher the accuracy of the wind speed and the running power processed by the group of sliding windows and window moving steps is, therefore, the sliding window and the window moving step with the highest covariance of the average value of the wind speed and the average value of the running power in the sliding window are respectively determined as a target sliding window and a target window moving step, so that the actual situation of the yaw data can be more reflected by the yaw data processed by the target sliding window and the target window moving step.

In step S107, based on the target sliding window and the target window moving step, the minimum value and/or the average value of the yaw data in the target sliding window that moves each time among the plurality of sets of yaw data arranged according to the acquisition time is obtained.

The minimum value and/or average value of the yaw data in the target sliding window specifically refers to the minimum value and/or average value of each yaw data in the target sliding window. For example, where the yaw data includes wind speed, operating power, and wind angle, the minimum and/or average of the yaw data within the target sliding window may include a minimum and/or average of wind speed within the target sliding window, a minimum and/or average of operating power within the target sliding window, and a minimum and/or average of wind angle within the target sliding window.

The following description will be given taking yaw data acquired over a period of time as an example as shown in fig. 5 above. Each point in fig. 5 represents a set of yaw data. The length of the target sliding window is 600 seconds, and the target window moving step size is 100 seconds. The minimum value and/or average value of the yaw data in the target sliding window at the initial position, i.e., 0 to 600 seconds, the minimum value and/or average value of the yaw data in the target sliding window after the first movement, i.e., 100 to 700 seconds, the minimum value and/or average value of the yaw data in the target sliding window after the second movement, i.e., 200 to 800 seconds, the minimum value and/or average value of the yaw data in the target sliding window after the third movement, i.e., 300 to 900 seconds, the minimum value and/or average value of the yaw data in the target sliding window after the fourth movement, i.e., 400 to 1000 seconds, and the minimum value and/or average value of the yaw data in the target sliding window after the fifth movement, i.e., 500 to 1100 seconds, are obtained.

In step S108, multiple sets of yaw data are filtered according to the minimum value and/or the average value of the yaw data in the target sliding window and a preset first filtering condition, so as to determine remaining yaw data.

Individual data with low accuracy may exist in the collected multiple sets of yaw data, and in order to avoid the influence of the yaw data with low accuracy on the calculation of the first wind angle and the target wind angle, the yaw data need to be screened. The minimum value and/or the average value of the yaw data in the target sliding window can reflect whether the wind generating set normally operates, whether the wind generating set is normally connected to the grid, whether the wind generating set operates under the power limiting condition, whether the wind generating set operates under the full power generating condition and the like. The wind generating set runs abnormally, is connected to the grid abnormally, runs under the condition of limited power and runs under the condition of full power, collected yaw data can influence the accuracy of the first wind direction angle and the target wind direction angle, and the yaw data are not used for participating in calculation of the first wind direction angle and the target wind direction angle. The method is characterized in that the collected yaw data are abandoned, namely the wind generating set runs abnormally, is connected to the grid abnormally, runs under the condition of limited power and runs under the condition of full power, and other yaw data are reserved.

In some examples, the first screening condition includes one or both of: 1. the minimum value and/or the average value of the yaw data in the target sliding window meet the normal grid-connected operation condition of the wind generating set, and the group of yaw data are reserved; 2. and the average value of the yaw data in the target sliding window is located in a preset operating power range, the group of yaw data is reserved, the minimum value of the preset operating power range is a limited power threshold value, and the maximum value of the preset operating power range is a full power threshold value.

The minimum value and/or the average value of the yaw data can reflect whether the wind generating set is normally operated in a grid-connected mode. The normal grid-connected operation condition of the wind generating set is used for judging whether the wind generating set is in normal grid-connected operation or not, and can be set according to a working scene and a working requirement, and is not limited herein.

And the average value of the yaw data is lower than the power limit threshold value, which indicates that the wind generating set operates under the power limit condition. And the average value of the yaw data is higher than the full power threshold value, and the wind generating set runs under the full power condition. The power limit threshold and the full power threshold may be set according to a working scenario and a working requirement, and are not limited herein.

In some examples, the yaw data may also include blade pitch angle. And screening multiple groups of yaw data according to the blade pitch angle in the target sliding window and a preset second screening condition to determine the retained yaw data. Abandon the driftage data that the precision is lower through the second screening condition, keep the higher driftage data of precision. Wherein the second screening condition comprises: and if the change of the blade pitch angle in the target sliding window is not 0, or the blade pitch angle in the target sliding window is larger than or equal to a preset blade pitch angle threshold value, and the group of yaw data is reserved. The preset blade pitch angle threshold may be specifically set according to a working scene and a working requirement, and is not limited herein. For example, the preset blade pitch angle threshold may be 7 °.

And the retained yaw data are used for participating in the calculation of the wind angle of the target, so that the interference can be removed, and the accuracy of the wind angle of the target is further improved. Under the condition of utilizing the target to execute yawing action on the wind angle, the wind generating set can be operated at the optimal generating efficiency or closer to the optimal generating efficiency, so that the loss of the generating capacity of the wind generating set is further reduced or avoided.

The second aspect of the application provides a wind misalignment correction device for a wind driven generator set. Fig. 7 is a schematic structural diagram of an embodiment of a wind turbine generator group wind misalignment correction device according to a second aspect of the present application. As shown in fig. 7, the wind power generation group wind misalignment correction device 200 further includes an acquisition module 201, a first calculation module 202, a second calculation module 203, a third calculation module 204, a fourth calculation module 205, and a yaw control module 206.

The collection module 201 may be configured to collect multiple sets of yaw data over a period of time, where each set of yaw data includes a wind speed, an operating power of a wind turbine generator system, and a wind angle of the wind turbine generator system.

The first calculation module 202 may be configured to divide a plurality of wind speed regions according to wind speed, and fit the wind speed and the operating power for each wind speed region to obtain a first fit functional relationship.

The second calculation module 203 may be configured to compensate the operating power by using the endpoint value of the wind speed region and the first fitting function relationship, so as to obtain a compensated operating power.

The third calculation module 204 may be configured to fit the compensated operating power and the wind angle corresponding to the wind speed zone to obtain a second fit functional relationship.

The fourth calculating module 205 may be configured to calculate a functional relationship based on the second fitting functional relationships corresponding to the plurality of wind speed regions and a preset wind angle, so as to obtain a target wind angle.

The yaw control module 206 may be used to perform a yaw maneuver on the wind angle based on the target.

In an embodiment of the present application, multiple sets of yaw data are acquired over a period of time. Dividing a plurality of wind speed areas according to wind speeds in yaw data, fitting the wind speed and the operating power in the yaw data for the yaw data corresponding to each wind speed area, compensating the operating power, fitting the compensated operating power and the wind angle in the yaw data, and synthesizing a second fitting functional relation corresponding to the plurality of wind speed areas and a preset wind angle calculation functional relation to obtain a target wind angle serving as a basis for executing a yaw action. Through twice fitting and compensation, the influence of the wind speed on the yaw data is reduced, the error of the target wind angle obtained as the basis for executing the yaw action is reduced, and the accuracy of the target wind angle is improved. The target is utilized to execute yawing action on the wind angle, so that the wind generating set can run at the optimal generating efficiency or close to the optimal generating efficiency, and the loss of the generating capacity of the wind generating set is reduced or avoided.

In some examples, the second computing module 203 described above may be configured to: calculating the average value of the endpoint values of the wind speed area; calculating to obtain compensation power by using the average value and the first fitting function relation; calculating to obtain first power by utilizing the wind speed in the yaw data corresponding to the wind speed area and the first fitting function relation; and determining the difference between the operating power in the yaw data corresponding to the wind speed area and the first power difference as the compensated operating power, wherein the first power difference is the difference between the first power and the compensated power.

In some examples, the fourth computing module 205 may be to: calculating a function relation by utilizing the second fitting function relation corresponding to each wind speed area and a preset wind angle, and calculating to obtain a first wind angle corresponding to each wind speed area; and obtaining a target wind angle based on the first wind angle corresponding to each wind speed area and the operating power corresponding to each wind speed area.

Optionally, calculating the functional relationship to wind angle comprises: the operation power is the product of the preset maximum power under the wind speed and a first cosine function value, the first cosine function value is a cosine function value of the n power of the wind angle, and n is a preset power coefficient.

Correspondingly, the fourth calculation module 205 may be configured to: calculating a quotient value of a derivative of a second fitting function relation corresponding to each wind speed area and the second fitting function relation under a preset standard wind angle condition; and calculating a functional relation by utilizing the quotient and the wind angle corresponding to each wind speed area to obtain a first wind angle corresponding to each wind speed area.

Optionally, the target wind angle includes a quotient of a first sum and a second sum, the first sum being a product of the first wind angle and a third sum corresponding to each wind speed zone, the third sum corresponding to each wind speed zone being a sum of operating power in the yaw data corresponding to each wind speed zone, and the second sum being a sum of the third sums corresponding to each wind speed zone.

Fig. 8 is a schematic structural diagram of another embodiment of a wind turbine generator group wind misalignment correction device provided in the second aspect of the present application. Fig. 8 is different from fig. 7 in that the wind power generation group wind misalignment correction device 200 shown in fig. 8 further includes a window selection module 207, a fifth calculation module 208, and a filtering module 209.

The window selection module 207 may be configured to select a target sliding window and a target window moving step.

The fifth calculation module 208 may be configured to obtain a minimum value and/or an average value of the yaw data in the target sliding window of each movement in the multiple sets of yaw data arranged according to the acquisition time based on the target sliding window and the target window movement step size.

The screening module 209 may be configured to screen multiple sets of yaw data according to the minimum value and/or the average value of the yaw data within the target sliding window and a preset first screening condition, so as to determine the retained yaw data.

Optionally, the first screening condition comprises one or both of: the minimum value and/or the average value of the yaw data in the target sliding window meet the normal grid-connected operation condition of the wind generating set, and the group of yaw data are reserved; and the average value of the yaw data in the target sliding window is located in a preset operating power range, the group of yaw data is reserved, the minimum value of the preset operating power range is a limited power threshold value, and the maximum value of the preset operating power range is a full power threshold value.

In some examples, the yaw data may also include blade pitch angle. The screening module 209 described above may also be configured to: and screening the multiple groups of yaw data according to the blade pitch angle in the target sliding window and a preset second screening condition, and determining the retained yaw data.

Optionally, the second screening condition comprises: and if the change of the blade pitch angle in the target sliding window is not 0, or the blade pitch angle in the target sliding window is larger than or equal to a preset blade pitch angle threshold value, and the group of yaw data is reserved.

In some examples, the window selection module 207 may be configured to: selecting a plurality of groups of sliding windows and window moving step lengths; obtaining the average value of the wind speed and the average value of the running power in the sliding window corresponding to each group of sliding windows and window moving step length according to each group of sliding windows and window moving step length; and respectively determining the sliding window and the window moving step length with the highest covariance of the average value of the wind speed and the average value of the running power in the sliding window as the target sliding window and the target window moving step length.

A third aspect of the present application provides a wind generating set controller. Fig. 9 is a schematic structural diagram of an embodiment of a wind generating set controller according to a third aspect of the present application. As shown in fig. 9, the wind park controller 300 comprises a memory 301, a processor 302 and a computer program stored on the memory 301 and executable on the processor 302.

In one example, the processor 302 may include a Central Processing Unit (CPU), or an Application Specific Integrated Circuit (ASIC), or may be configured to implement one or more Integrated circuits of the embodiments of the present Application.

The Memory may include Read-Only Memory (ROM), Random Access Memory (RAM), magnetic disk storage media devices, optical storage media devices, flash Memory devices, electrical, optical, or other physical/tangible Memory storage devices. Thus, in general, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., a memory device) encoded with software comprising computer-executable instructions and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the wind-misalignment correction method for a wind-generating set according to the present application.

The processor 302 runs a computer program corresponding to the executable program code by reading the executable program code stored in the memory 301, for implementing the wind-power generation group wind misalignment correction method in the above-described embodiment.

In one example, the wind park controller 300 may also include a communication interface 303 and a bus 304. As shown in fig. 9, the memory 301, the processor 302, and the communication interface 303 are connected via a bus 304 to complete communication therebetween.

The communication interface 303 is mainly used for implementing communication between modules, apparatuses, units and/or devices in the embodiment of the present application. Input devices and/or output devices may also be accessed through communication interface 303.

The bus 304 includes hardware, software, or both that couple the components of the aerogenerator group controller 300 to each other. By way of example, and not limitation, Bus 304 may include an Accelerated Graphics Port (AGP) or other Graphics Bus, an Enhanced Industry Standard Architecture (EISA) Bus, a Front-Side Bus (FSB), a HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) Bus, an InfiniBand interconnect, a Low Pin Count (LPC) Bus, a memory Bus, a Micro Channel Architecture (MCA) Bus, a Peripheral Component Interconnect (PCI) Bus, a PCI-Express (PCI-X) Bus, a Serial Advanced Technology Attachment (SATA) Bus, a Video Electronics Standards Association Local Bus (VLB) Bus, or other suitable Bus, or a combination of two or more of these. Bus 304 may include one or more buses, where appropriate. Although specific buses are described and shown in the embodiments of the application, any suitable buses or interconnects are contemplated by the application.

The embodiment of the present application further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the wind misalignment correction method for a wind turbine generator set in the foregoing embodiment can be implemented, and the same technical effect can be achieved, and in order to avoid repetition, details are not repeated here. The computer-readable storage medium may include a non-transitory computer-readable storage medium, such as a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and the like, which is not limited herein.

It should be clear that the embodiments in this specification are described in a progressive manner, and the same or similar parts in the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. For the device embodiment, the aerogenerator group controller embodiment, the computer-readable storage medium embodiment, reference may be made to the description of the method embodiments for their relevance. The present application is not limited to the particular steps and structures described above and shown in the drawings. Those skilled in the art may make various changes, modifications and additions or change the order between the steps after appreciating the spirit of the present application. Also, a detailed description of known process techniques is omitted herein for the sake of brevity.

Aspects of the present application are described above with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions/acts specified in the flowchart and/or block diagram block or blocks. Such a processor may be, but is not limited to, a general purpose processor, a special purpose processor, an application specific processor, or a field programmable logic circuit. It will also be understood that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware for performing the specified functions or acts, or combinations of special purpose hardware and computer instructions.

It will be appreciated by persons skilled in the art that the above embodiments are illustrative and not restrictive. Different features which are present in different embodiments may be combined to advantage. Other variations to the disclosed embodiments can be understood and effected by those skilled in the art upon studying the drawings, the specification, and the claims. In the claims, the term "comprising" does not exclude other means or steps; the word "a" or "an" does not exclude a plurality; the terms "first" and "second" are used to denote a name and not to denote any particular order. Any reference signs in the claims shall not be construed as limiting the scope. The functions of the various parts appearing in the claims may be implemented by a single hardware or software module. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage.