阅读说明：本技术 阻尼控制方法、系统和可读存储介质 (Damping control method, system and readable storage medium ) 是由 赵玉娟 于 2021-09-29 设计创作，主要内容包括：本申请提供一种阻尼控制方法、系统和可读存储介质。阻尼控制方法包括根据卡尔曼滤波算法、风力发电机组的状态方程和输出方程,确定风力发电机组的塔顶前后位移,其中,状态方程和输出方程包括表示塔顶前后位移的状态向量；根据塔顶前后位移,确定风力发电机组的阻尼桨距角；及根据阻尼桨距角和风力发电机组的变桨桨距角,对风力发电机组进行变桨控制,以至少对塔架的阻尼进行控制。可以降低阻尼控制成本。(The application provides a damping control method, a damping control system and a readable storage medium. The damping control method comprises the steps of determining the front and rear displacement of the tower top of the wind generating set according to a Kalman filtering algorithm, a state equation and an output equation of the wind generating set, wherein the state equation and the output equation comprise state vectors expressing the front and rear displacement of the tower top; determining the damping pitch angle of the wind generating set according to the front and back displacement of the tower top; and carrying out variable pitch control on the wind generating set according to the damping pitch angle and the variable pitch angle of the wind generating set so as to control the damping of the tower at least. The damping control cost can be reduced.)

1. A damping control method, characterized by comprising:

determining the front and rear displacement of the tower top of the wind generating set according to a Kalman filtering algorithm, a state equation and an output equation of the wind generating set, wherein the state equation and the output equation comprise state vectors representing the front and rear displacement of the tower top;

determining the damping pitch angle of the wind generating set according to the front-back displacement of the tower top; and

and carrying out variable pitch control on the wind generating set according to the damping pitch angle and the variable pitch angle of the wind generating set so as to control the damping of the tower at least.

2. The damping control method of claim 1, wherein determining the tower top fore-aft displacement of the wind generating set according to a kalman filter algorithm, a state equation and an output equation of the wind generating set comprises:

and determining the front and rear displacement of the tower top of the wind generating set according to the Kalman filtering algorithm, the state equation, the output equation and the target initial state value of the state vector.

3. The damping control method according to claim 2, characterized in that the target initial state value is determined by a simulation method including:

determining the front and back simulated displacement of the tower top of the wind generating set according to a Kalman filtering algorithm, the state equation, the output equation and the alternative initial state value;

determining a damping simulation pitch angle of the wind generating set according to the tower top front and back simulation displacement;

simulating damping control of a tower of the wind generating set according to the damping simulated pitch angle, the variable-pitch simulated pitch angle of the wind generating set and a wind generating set model corresponding to the wind generating set so as to determine simulated load of the tower under the damping control;

simulating non-damping control of the tower according to the variable-pitch simulation pitch angle of the wind generating set and the wind generating set model to determine the simulation load of the tower under the non-damping control;

the target initial state value is the alternative initial state value when the following conditions are met:

and after the damping control of the wind generating set is simulated based on the alternative initial state value, the simulated load of the tower under the damping control is smaller than the simulated load of the tower under the non-damping control.

4. The damping control method according to claim 1, wherein said determining a damping pitch angle of said wind turbine generator set from said tower top fore-aft displacement comprises:

and determining the damping pitch angle of the wind generating set according to the fore-and-aft displacement of the tower top and the target gain coefficient.

5. The damping control method according to claim 4, wherein determining a damping pitch angle of the wind turbine generator set based on the tower top fore-aft displacement and a target gain coefficient comprises:

determining the front and rear speeds of the engine room according to the front and rear displacement of the tower top;

and determining the damping pitch angle of the wind generating set according to the front-back speed of the engine room and the target gain coefficient.

6. The damping control method of claim 4, wherein the target gain factor is determined by an analog method comprising:

determining the front and back simulated displacement of the tower top of the wind generating set according to a Kalman filtering algorithm, the state equation and the output equation;

determining a damping simulation pitch angle of the wind generating set according to the tower top front and back simulation displacement and the alternative gain coefficient;

simulating damping control of a tower of the wind generating set according to the damping simulated pitch angle, the variable-pitch simulated pitch angle of the wind generating set and a wind generating set model corresponding to the wind generating set so as to determine simulated load of the tower under the damping control;

simulating non-damping control of the tower according to the variable-pitch simulation pitch angle of the wind generating set and the wind generating set model, and determining the simulation load of the tower under the non-damping control;

the target initial state value is the alternative gain coefficient when the following conditions are satisfied:

and after the damping control of the wind generating set is simulated based on the alternative gain coefficient, the simulated load of the tower under the damping control is smaller than the simulated load of the tower under the non-damping control.

7. The damping control method according to claim 3 or 6, characterized in that the simulation method includes:

generating the wind generating set model according to the characteristic parameters of the wind generating set;

and carrying out linearization processing on the wind generating set model according to a preset wind speed and the degree of freedom to obtain a state space equation corresponding to the wind generating set at the preset wind speed, wherein the state space equation comprises the state equation and the output equation of the wind generating set.

8. The damping control method of claim 7, wherein the degrees of freedom include first order blade tip flap displacement, generator rotational degrees of freedom, and first order tower top fore and aft displacement of the wind turbine generator set.

9. The damping control method of claim 1, wherein determining the tower top fore-aft displacement of the wind generating set according to a kalman filter algorithm, a state equation and an output equation of the wind generating set comprises:

and determining the front and rear displacement of the tower top of the wind generating set according to a Kalman filtering algorithm, a state equation corresponding to the actual wind speed of the environment where the wind generating set is located and an output equation.

10. A controller for a wind park comprising one or more processors for implementing a damping control method according to any of claims 1-9.

11. A readable storage medium, characterized in that a program is stored thereon, which, when being executed by a processor, carries out the damping control method according to any one of claims 1-9.

Technical Field

The invention relates to the field of wind power, in particular to a damping control method, a damping control system and a readable storage medium.

Background

The tower is one of the key components of the wind turbine. At present, the tower of a large-scale wind generating set is mostly a flexible tower, the front and back damping of the tower is small, and when the wind generating set operates, the tower can generate serious vibration, so that large load is caused to the tower, and the reliability and the service life of the wind generating set are influenced. In some technologies, the front and rear damping of the tower is controlled, so that the purposes of increasing the front and rear damping of the tower and reducing the vibration of the tower can be achieved. However, the tower damping control in these techniques is costly.

Disclosure of Invention

The application provides a damping control method, a damping control system and a readable storage medium, which can reduce the cost of tower damping control.

The application provides a damping control method, which comprises the following steps:

determining the front and rear displacement of the tower top of the wind generating set according to a Kalman filtering algorithm, a state equation and an output equation of the wind generating set, wherein the state equation and the output equation comprise state vectors representing the front and rear displacement of the tower top;

determining the damping pitch angle of the wind generating set according to the front-back displacement of the tower top;

and carrying out variable pitch control on the wind generating set according to the damping pitch angle and the variable pitch angle of the wind generating set so as to control the damping of the tower at least.

The application provides a controller of a wind generating set, which comprises one or more processors and is used for realizing the damping control method.

The present application provides a readable storage medium having stored thereon a program which, when executed by a processor, implements a simulation method as described above.

In some embodiments, the damping control method determines the tower top front-back displacement of the wind generating set according to a Kalman filtering algorithm, a state equation and an output equation of the wind generating set, determines the damping pitch angle of the wind generating set according to the tower top front-back displacement, and controls the damping of a tower of the wind generating set according to the damping pitch angle. According to the method and the device, the front and rear displacement of the tower top of the wind generating set is estimated through the Kalman filtering algorithm, and the acceleration sensor is not required to be arranged to detect the front and rear acceleration of the tower top, so that the tower damping control cost is reduced.

Drawings

FIG. 1 is a schematic block diagram of a control principle of a wind turbine generator set in the related art;

FIG. 2 is a flow chart of a damping control method provided by an embodiment of the present application;

FIG. 3 is a schematic block diagram of a control principle of a wind turbine generator set provided by an embodiment of the present application;

fig. 4 is a block diagram of a controller according to an embodiment of the present application.

Detailed Description

Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with one or more embodiments of the present specification. Rather, they are merely examples of apparatus and methods consistent with certain aspects of one or more embodiments of the specification, as detailed in the claims which follow.

It should be noted that: in other embodiments, the steps of the corresponding methods are not necessarily performed in the order shown and described herein. In some other embodiments, the method may include more or fewer steps than those described herein. Moreover, a single step described in this specification may be broken down into multiple steps for description in other embodiments; multiple steps described in this specification may be combined into a single step in other embodiments.

The following description will first explain the principle of tower front-rear damping control in the related art.

In some embodiments, the dynamic characteristic equation before and after the tower top of the wind generating set is expressed by the expression (1):

wherein, F_ARepresenting the axial thrust of a wind wheel of the wind generating set;

x represents the fore-and-aft displacement of the tower top of the wind generating set;

representing the tower top back-and-forth movement speed of the wind generating set;

representing tower top fore-and-aft movement acceleration of wind generating setsDegree;

m_trepresenting the tower mass of the wind generating set;

k_trepresenting the tower stiffness of the wind generating set;

B_trepresenting tower fore and aft damping of the wind turbine.

For a large-scale wind generating set, tower front and rear damping B in expression (1)_tThe wind generating set is small, belongs to a weak damping system, and can cause large load to the tower in the operation process. In the related technology, extra pitch angle control is added on the basis of the original pitch angle control of the wind generating set to damp the front and back of the tower B_tAnd (5) controlling. Namely, on the basis of the original pitch angle of the wind generating set, the damping pitch angle delta beta is newly added, so that the wind wheel of the wind generating set generates extra axial thrust delta F on the basis of the original axial thrust_AThus increasing the front and rear damping B of the tower_t. The dynamic characteristic equation before and after the tower top of the wind generating set is as the expression (2):

if Δ F_AAndin direct proportion, then Δ F_AAndis shown in expression (3):

substituting expression (3) into expression (2) may result in expression (4):

comparing the expression (1) and the expression (4), it can be seen that the front and rear tower damping of the wind generating set is from B_tIncrease to B_t+B_pThus, by adding the damping pitch angle Δ β, the additional axial thrust Δ F is added_ABy the method, the purpose of increasing the front and rear damping of the tower can be achieved.

Further, the damping pitch angle Δ β may be determined by:

in some embodiments, rotor axial thrust F_ACan be expressed as expression (5):

F_A＝f(v,β,w) (5)

wherein v represents wind speed;

beta represents the pitch angle of the wind generating set;

w represents the rotor speed of the wind turbine.

By linearizing the above expression (5) at the operation balance point and keeping the wind speed v and the wind wheel rotation speed w fixed, expression (6) can be obtained:

substituting expression (6) into expression (3), expression (7) of damping pitch angle Δ β can be obtained:

according to expression (7), the damping pitch angle Δ β may be determined, such that additional control of the pitch angle of the wind park may be performed. But the tower top back-and-forth movement speed of the wind generating setGenerally, the acceleration sensor is difficult to obtain, so that in practical application, the acceleration sensor is used for measuring the front and rear acceleration of the tower top of the wind generating setAcceleration of tower topIntegrating to obtain the front-back movement speed of the tower top

Fig. 1 is a schematic block diagram of a part of a control principle of a wind turbine generator system in the related art. Referring to fig. 1, a control system connected to a wind turbine includes a variable speed control loop, a pitch control loop, and a damping control loop, wherein:

the variable speed control loop is used for controlling the actual rotating speed w of the generator of the wind driven generator unit_gOutput generator torque T_eThe torque of the generator is controlled.

The variable pitch control ring is used for controlling the actual rotating speed w of the generator_gAnd a generator reference speed w_refThe rotational speed deviation delta w of (rated power generation rotational speed) outputs a variable pitch angle beta_rCarrying out variable pitch control on the wind generating set so as to enable the actual rotating speed w of the generator_gMaintained at the generator reference speed w_refAnd the actual power of the wind generating set is maintained near the rated power.

The damping control ring is used for controlling the front and rear acceleration of the tower top of the wind generating setIntegrating to obtain the front-back movement speed of the tower topThen the tower top is moved back and forth at a speedMultiplying the preset gain coefficient, outputting a corresponding damping control pitch angle delta beta, and performing additional pitch control on the wind generating set so as to control the front and rear damping of the tower.

In the actual control, the pitch angle beta can be changed firstly_rAdding the damping control pitch angle delta beta to obtain a main control pitch angle beta_dThen the main control pitch angle beta_dAs the input of the variable pitch system of the wind generating set, the variable pitch system is used for controlling the pitch angle beta according to the main control_dOutputting corresponding pitch angle beta, carrying out pitch control on the wind generating set, and further simultaneously carrying out actual rotating speed w of the generator_gAnd tower fore and aft damping.

In some embodiments, the generator torque T output based on the variable speed control loop_eAnd the pitch angle beta output by the pitch system controls the wind generating set, and simultaneously, the wind generating set outputs the actual rotating speed w of the generator_gAs control feedback, the variable speed control loop and the variable pitch control loop are enabled to be in accordance with the real-time actual rotating speed w of the generator_gAnd controlling the wind generating set.

In fig. 1, control logics corresponding to the variable speed control loop, the variable pitch control loop and the damping control loop may be arranged in a main controller of the wind generating set; the control logic corresponding to the variable pitch system can be arranged in a variable pitch controller of the wind generating set.

In the above-mentioned related art, it is necessary to provide an acceleration sensor for measuring the front-rear acceleration of the tower top on the wind turbine generator systemThe acceleration sensor needs to have low-frequency characteristics, has high requirements on precision and reliability, and is expensive, so that the tower damping control cost in the related art is high.

Fig. 2 is a flowchart of a damping control method according to an embodiment of the present application. The damping control method shown in fig. 2 is applied to a controller of a wind turbine generator set, and includes steps S21 to S23.

And step S21, determining the front and back displacement of the tower top of the wind generating set according to a Kalman filtering algorithm, a state equation and an output equation of the wind generating set, wherein the state equation and the output equation comprise state vectors representing the front and back displacement of the tower top.

The Kalman filtering algorithm is an algorithm for performing optimal estimation on the system state by using a linear system state equation and outputting observation data through the system input. According to the method and the device, through a Kalman filtering algorithm, the state equation and the output equation of the wind generating set are utilized, and the front displacement and the rear displacement of the tower top are optimally estimated.

In some embodiments, step 21 comprises: and determining the front and rear displacement of the tower top of the wind generating set according to a Kalman filtering algorithm, a state equation corresponding to the actual wind speed of the environment where the wind generating set is located and an output equation. The actual wind speed associated with the environment in which the wind turbine generator system is located may be the current wind speed. The actual wind speeds are different, the corresponding state equations and the corresponding output equations are different, and the front and rear displacement of the tower top is calculated by using the different state equations and the different output equations under different wind speeds, so that the damping control method has better adaptability, and the accuracy of the calculated front and rear displacement of the tower top is higher.

In some embodiments, the state equations and output equations of the wind turbine generator set may be determined by simulation methods. The simulation method may be applied to an electronic device (e.g., a computer). A wind generating set model may be established, and a state equation and an output equation of the wind generating set may be determined based on the wind generating set model. In some embodiments, the corresponding state equation and output equation of the wind turbine generator set at different wind speeds may be determined by a simulation method. And determining a state equation and an output equation of the wind generating set at different wind speeds based on the wind generating set model.

In some embodiments, the simulation method comprises:

1) and generating a wind generating set model according to the characteristic parameters of the wind generating set.

In some embodiments, the wind power generation group model may be generated by running FAST software. The FAST software is self-contained with various wind power generation unit models. And taking the characteristic parameters of the wind generating set as input parameters of FAST software, and operating the FAST software after parameter setting to generate a corresponding wind generating set model. The characteristic parameters of the wind generating set include, but are not limited to, output capacity of the wind generating set, blade parameters, tower parameters, a turbulent wind model for simulating an actual wind speed of an environment where the wind generating set is located, and the like. For example, the output capacity of the wind generating set is 1.5MW, the parameter representing the output capacity of the wind generating set model is set to 1.5MW in the FAST software, and the FAST software generates the wind generating set model with the output capacity of 1.5 MW.

In some embodiments, with reference to fig. 1 in combination, the wind park model generated in step 1) is a non-linear aerodynamic model of a wind park for simulating the wind park in fig. 1. The input variables of the wind generating set model comprise a simulated wind speed V 'of the environment where the wind generating set is positioned, a simulated pitch angle beta' of the wind generating set and a generator simulated torque T_e'. The output variable of the wind generating set model comprises the generator simulation rotating speed w of the wind generating set_g′。

2) And carrying out linearization processing on the wind generating set model according to the preset wind speed and the degree of freedom to obtain a corresponding state space equation of the wind generating set at the preset wind speed, wherein the state space equation comprises a state equation and an output equation of the wind generating set. In some embodiments, the wind generating set model may be linearized by running the FAST software due to the ability of the FAST software to derive a linear wind generating set model from a non-linear wind generating set model.

In some embodiments, a plurality of preset wind speeds may be set. The preset wind speed is different, the corresponding turbulent wind models are different, the obtained state space equations are different, and further the corresponding state equations are different from the output equations. Therefore, the state equation and the output equation corresponding to different wind speeds can be obtained, and therefore in step S21, the fore-and-aft displacement of the tower top of the wind generating set can be determined according to the state equation and the output equation corresponding to the actual wind speed.

In some embodiments, the degrees of freedom include a first order tower top fore-aft displacement (TwFADOF1) of the wind turbine generator set to ensure that the generated state equations and output equations include state vectors representing the tower top fore-aft displacement. The degrees of freedom may also include first order blade tip flap displacement (flap dof1) and generator rotational degree of freedom (GenDOF) of the wind turbine generator set. The first-order blade tip flapping displacement and the generator rotation freedom degree are used for enabling the wind generating set model after linearization processing to have rich functions. It can be understood that, for different model design considerations, the degrees of freedom may be adjusted according to the actual situation, for example, on the basis of the above three degrees of freedom, other degrees of freedom are added, so that the linearized wind turbine generator system model has more functions.

In some embodiments, after the FAST software linearizes the wind turbine generator system model based on the degrees of freedom including the first-order blade tip flap displacement, the generator rotational degree of freedom, and the first-order tower top back and forth displacement, the output state equation is as shown in expression (8), and the corresponding output equation is as shown in expression (9):

y＝Cx+Du (9)

wherein the content of the first and second substances,

a state vector representing the wind park, wherein "x 1: the tower top fore-and-aft displacement (m) "is the tower top fore-and-aft displacement of the wind generating set to be determined. For determining the value of the state vector, please refer to the following related description, which is not repeated herein;

representing an input variable of a wind turbine;

y represents an output variable of the wind generating set;

represents the derivative of the state vector x;

a denotes a system matrix, B denotes a control matrix, C denotes an output matrix, and D denotes a direct transition matrix. The A, B, C, D above is a known value in the equation of state and the equation of output for the FAST software output. The above A, B, C, D may be at least partially different for equations of state and output at different wind speeds.

The above expressions (8) and (9) are converted into discretization equations, so that the value of the state vector at the discrete moment (including the value of "x 1: the front-back displacement (m) of the tower top)" can be determined by using a kalman filter algorithm. Discretizing the discretized state equation such as expression (10), and corresponding discretized output equation such as expression (11):

x_k＝F_k-1x_k-1+G_k-1u_k-1+w_k-1 (10)

z_k＝H_k-1x_k+v_k (11)

wherein, in the expression (10), x_kA value representing a state vector of the wind generating set at the moment k; x is the number of_k-1Representing the value of the state vector of the wind generating set at the moment k-1; u. of_k-1Representing the value of the input variable of the wind generating set at the moment k-1; w is a_k-1Is the noise signal at the moment k-1; f_k-1And G_k-1Is a state transition matrix of the state equation. For discrete equations of state at different wind speeds, F_k-1、G_k-1And w_k-1May be at least partially different.

In the expression (11), z_kThe value of the output variable of the wind turbine at time k, in this case the generator speed w at time k_g，x_kValue, v, representing the state vector of the wind turbine at time k_kRepresenting the noise signal of the wind turbine at time k, H_k-1For the state transition matrix of the output equation, H_k-1Are known values. For discrete output equations at different wind speeds, H_k-1And v_kMay be at least partially different.

After the state equation and the output equation of the wind generating set are obtained through the simulation method, the discrete state equation and the discrete output equation corresponding to different wind speeds can be burnt into the main controller of the wind generating set, so that in step S21, the main controller of the wind generating set determines the front and back displacement of the tower top of the wind generating set according to the state equation and the output equation of the wind generating set.

According to a Kalman filtering algorithm, based on the value of the state vector x at the k-1 moment and a discrete state equation, the estimation value of the state vector x at the k moment can be obtained; based on the output value of the discrete output equation at the moment k, the observed value of the state vector x at the moment k can be obtained; according to the estimation value and the observation value of the state vector x at the time k, the optimal estimation value of the state vector x at the time k can be obtained. In some embodiments, the tower top fore-aft displacement of the wind generating set may be determined according to a kalman filter algorithm, a state equation, an output equation, and a target initial state value of the state vector. The target initial state value is the target initial value of the state vector at time 0. According to the target initial state value, the value of the state vector at the next moment can be obtained by using a Kalman filtering algorithm, and then the value of the state vector at the next moment is obtained, so that the value of the state vector at each discrete moment can be obtained. In some embodiments, different wind speeds correspond to different target initial state values.

In some embodiments of the present application, the target initial state values of the state vector at different wind speeds may be burned into a controller of the wind turbine generator system, and the controller determines the front-rear displacement of the tower top of the wind turbine generator system according to the kalman filter algorithm, the state equation, the output equation, and the target initial state value of the state vector. In some embodiments, the target initial state values of the state vector at different wind speeds may be burned into a controller of the wind turbine generator system, and the controller determines the tower top front-rear displacement of the wind turbine generator system according to a kalman filter algorithm, a state equation corresponding to an actual wind speed, an output equation corresponding to the actual wind speed, and the target initial state value corresponding to the actual wind speed. For the determination of the target initial state value, reference may be made to the following related description, which is not repeated herein.

In other embodiments, all or a plurality of wind speeds may correspond to the same state equation, output equation, and target initial state value. Thus, the control logic is simplified.

And step S22, determining the damping pitch angle of the wind generating set according to the fore-and-aft displacement of the tower top.

In some embodiments, determining a damping pitch angle of the wind turbine generator set from the tower top fore-aft displacement comprises:

and determining the damping pitch angle of the wind generating set according to the fore-and-aft displacement of the tower top and the target gain coefficient. In some embodiments, the nacelle fore-aft velocity may be determined from the tower top fore-aft displacement; and determining the damping pitch angle of the wind generating set according to the front and rear speeds of the engine room and the target gain coefficient. In some embodiments, the nacelle fore-aft speed and the target gain coefficient are multiplied to obtain the damped pitch angle of the wind turbine generator set. For determining the target gain factor, reference may be made to the following related description, which is not repeated herein.

And step S23, carrying out pitch control on the wind generating set according to the damping pitch angle and the pitch angle of the wind generating set so as to control the damping of the tower at least.

In some embodiments, as described in relation to fig. 1, the damping pitch angle may be added to the pitch angle to obtain an overall pitch angle, which is input to the wind park to simultaneously control the generator power of the wind park and the tower fore-aft damping.

In other embodiments, the damped pitch angle may be input to the wind turbine generator set, and the damped pitch angle and the pitch angle may be added by the wind turbine generator set to simultaneously control the generator power of the wind turbine generator set and the tower fore-aft damping according to the total pitch angle obtained by the addition.

How to determine the target initial state value and the target gain factor is explained below.

In some embodiments, the established wind generating set model is a pneumatic model of the wind generating set, and a controller model corresponding to a controller of the wind generating set may be established through Matlab software. And then simulating damping control and non-damping control of the wind generating set based on the controller model and the wind generating set model to determine a target initial state value and a target gain coefficient. The controller model may be used to run the simulation method.

In some embodiments, the target initial state value may be determined by a simulation method as follows:

1) and determining the front and back simulated displacement of the tower top of the wind generating set according to the Kalman filtering algorithm, the state equation, the output equation and the alternative initial state value. The alternative initial state value is an alternative value of the target initial state value, and may be determined based on manual experience.

2) And determining the damping simulation pitch angle of the wind generating set according to the front and back simulation displacement of the tower top.

3) And simulating the damping control of the tower of the wind generating set according to the damping simulated pitch angle, the variable pitch simulated pitch angle of the wind generating set and the wind generating set model corresponding to the wind generating set so as to determine the simulated load of the tower under the damping control. Similar to step S23, the controller model may add the damping simulated pitch angle and the pitch simulated pitch angle to obtain a simulated total pitch angle, and input the simulated total pitch angle to the wind turbine generator system model to simulate the damping control of the tower of the wind turbine generator system.

In some embodiments, during damping control simulation, the FAST software may determine the simulated load of the tower under damping control based on tower load simulation data of the wind turbine generator set model.

4) And simulating the non-damping control of the tower according to the variable-pitch simulation pitch angle of the wind generating set and the wind generating set model to determine the simulation load of the tower under the non-damping control.

In some embodiments, at step 4), the pitch angle input to the wind power plant model does not include a pitch angle for damping control, simulating non-damping control of the tower. During the simulation, the FAST software can determine the tower load simulation data under the non-damping control according to the tower load simulation data of the wind generating set model. Non-damping control refers to no damping control of the tower.

The target initial state value is an alternative initial state value when the following conditions are met:

and after the damping control of the wind generating set is simulated based on the alternative initial state value, the simulated load of the tower under the damping control is smaller than the simulated load of the tower under the non-damping control.

The aim of reducing the front and rear loads of the tower can be achieved when the wind generating set is subjected to damping control based on the alternative initial state value.

If the simulated load of the tower under the damping control is determined to be larger than or equal to the simulated load of the tower under the non-damping control based on the alternative initial state value, the alternative initial state value is not a target value, so the alternative initial state value is adjusted, and then the simulation methods of the steps 1) to 4) are executed again based on the adjusted alternative initial state value, wherein the simulated load of the tower under the damping control is smaller than the simulated load of the tower under the non-damping control.

In some embodiments, different wind speeds may correspond to different target initial state values. For different wind speeds, the simulation methods of steps 1) to 4) above may be respectively performed based on different candidate initial state values to determine corresponding target initial state values at different wind speeds.

In some embodiments, the target gain factor may be determined by an analog method as follows:

and determining the front and back simulated displacement of the tower top of the wind generating set according to a Kalman filtering algorithm, a state equation and an output equation.

And determining the damping simulation pitch angle of the wind generating set according to the front and back simulation displacement of the tower top and the alternative gain coefficient. The alternative gain factor is an alternative value of the target gain factor, and may be determined based on manual experience.

And simulating the damping control of the tower of the wind generating set according to the damping simulated pitch angle, the variable pitch simulated pitch angle of the wind generating set and the wind generating set model corresponding to the wind generating set so as to determine the simulated load of the tower under the damping control.

And simulating the non-damping control of the tower according to the variable-pitch simulation pitch angle of the wind generating set and the wind generating set model, and determining the simulation load of the tower under the non-damping control.

The target gain coefficient is an alternative gain coefficient when the following conditions are met:

after the damping control of the wind generating set is simulated based on the alternative gain coefficient, the simulated load of the tower under the damping control is smaller than the simulated load of the tower under the non-damping control.

The damped analog load is less than the alternative gain factor for the un-damped analog load condition.

The principle of determining the target gain coefficient is similar to that of determining the target initial state value, and is not described herein again.

In some embodiments, the target gain factor and the target initial state value may be adjusted in combination, and the simulation method includes:

1) and determining the front and back simulated displacement of the tower top of the wind generating set according to the Kalman filtering algorithm, the state equation, the output equation and the alternative initial state value.

2) And determining the damping simulation pitch angle of the wind generating set according to the front and back simulation displacement of the tower top and the alternative gain coefficient.

3) And simulating the damping control of the tower of the wind generating set according to the damping simulated pitch angle, the variable pitch simulated pitch angle of the wind generating set and the wind generating set model corresponding to the wind generating set so as to determine the simulated load of the tower under the damping control.

4) And simulating the non-damping control of the tower according to the variable-pitch simulation pitch angle of the wind generating set and the wind generating set model to determine the simulation load of the tower under the non-damping control.

The target initial state value and the target gain coefficient are alternative initial state values and alternative gain coefficients which meet the following conditions:

and after the damping control of the wind generating set is simulated based on the alternative initial state value and the alternative gain coefficient, the simulated load of the tower under the damping control is smaller than the simulated load of the tower under the non-damping control.

When the damping control is performed on the wind generating set based on the alternative initial state value and the alternative gain coefficient, the purpose of reducing the front and rear loads of the tower can be achieved.

If the simulated load of the tower under the damping control is determined to be larger than or equal to the simulated load of the tower under the non-damping control based on the candidate initial state value and the candidate gain coefficient, at least one of the candidate initial state value and the candidate gain coefficient is not a target value, so that the candidate initial state value and the candidate gain coefficient are respectively adjusted, or one of the candidate initial state value and the candidate gain coefficient is adjusted, and then the simulation methods of the steps 1) to 4) are executed again based on the adjusted candidate initial state value and the candidate gain coefficient until the simulated load of the tower under the damping control is smaller than the simulated load of the tower under the non-damping control.

In some embodiments, different wind speeds may correspond to different target initial state values and/or different target gain factors. For different wind speeds, the simulation methods of steps 1) to 4) above may be respectively performed based on different candidate initial state values and/or different candidate gain coefficients, so as to determine corresponding target initial state values and target gain coefficients at different wind speeds.

Fig. 3 is a schematic block diagram of a control principle of a wind turbine generator system according to an embodiment of the present application.

FIG. 3 is similar to FIG. 1, and the main difference is that the front and rear displacement of the tower top of the wind generating set is determined through a Kalman filtering algorithm, then the front and rear displacement of the tower top is used as the input of a damping control ring, and the front and rear displacement of the tower top is differentiated to obtain the front and rear speed of the tower topTo determine the damping pitch angle of the wind turbine.

According to the related description, in some embodiments, the damping control method determines the tower top front-rear displacement of the wind generating set according to the Kalman filtering algorithm, the state equation and the output equation of the wind generating set, determines the damping pitch angle of the wind generating set according to the tower top front-rear displacement, and controls the damping of the tower of the wind generating set according to the damping pitch angle. According to the method and the device, the front and rear displacement of the tower top of the wind generating set is estimated through the Kalman filtering algorithm, and the acceleration sensor is not required to be arranged to detect the front and rear acceleration of the tower top, so that the tower damping control cost is reduced. And the front and rear displacement of the tower top can be optimally estimated through a Kalman filtering algorithm, so that the accuracy of tower damping control is high.

Fig. 4 is a block diagram of a controller 500 of a wind turbine generator system according to an embodiment of the present disclosure.

The controller 500 includes one or more processors 501 for implementing the damping control method as described above. In some embodiments, the controller 500 may include a readable storage medium 509, and the readable storage medium 509 may store a program that may be called by the processor 501, and may include a non-volatile storage medium.

In some embodiments, the controller 500 may include a memory 508 and an interface 507.

In some embodiments, the controller 500 may also include other hardware depending on the application.

The readable storage medium 509 of the embodiment of the present application stores thereon a program for implementing the damping control method as described above when the program is executed by the processor 501.

This application may take the form of a computer program product embodied on one or more readable storage media 509 (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having program code embodied therein. Readable storage media 509 includes permanent and non-permanent, removable and non-removable media, and information storage may be accomplished by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of readable storage media 509 include, but are not limited to: phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technologies, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic tape storage or other magnetic storage devices, or any other non-transmission medium, may be used to store information that may be accessed by a computing device.

The above description is only a preferred embodiment of the present disclosure, and should not be taken as limiting the present disclosure, and any modifications, equivalents, improvements, etc. made within the spirit and principle of the present disclosure should be included in the scope of the present disclosure.

The above description is only a preferred embodiment of the present disclosure, and should not be taken as limiting the present disclosure, and any modifications, equivalents, improvements, etc. made within the spirit and principle of the present disclosure should be included in the scope of the present disclosure.

It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.