CN115514004A - An Adaptive Control Method for Subsynchronous Oscillation of Direct-Drive Wind Power Gentle Delivery System - Google Patents

Abstract

The invention discloses a sub-synchronous oscillation control method of a self-adaptive direct-drive wind power soft and direct delivery system, which comprises the steps of establishing a model of the direct-drive wind power soft and direct delivery system, analyzing a control link strongly related to a sub-synchronous oscillation mode, and providing an additional position scheme of self-adaptive control of sub-synchronous oscillation; designing an adaptive control method for inhibiting subsynchronous oscillation of a direct-drive wind power soft and direct delivery system; respectively establishing an optimization model of parameters of the self-adaptive control method by adopting different additional position schemes, and determining optimal control parameters of a control strategy at each additional position; and comparing the subsynchronous oscillation control effects of the additional position schemes, establishing an evaluation index, determining the optimal additional position of the controller, and realizing subsynchronous oscillation suppression.

Description

An Adaptive Control Method for Subsynchronous Oscillation of Direct-Drive Wind Power Gentle Delivery System

technical field

The invention relates to the technical field of power system stability and control, in particular to an adaptive subsynchronous oscillation control method for a direct-drive wind power soft direct delivery system.

Background technique

The wind power system has the risk of sub-synchronous oscillation through flexible DC transmission, which endangers the stable and safe operation of the power system. It has gradually become a hot spot in recent research. Complex interactions between power electronics in DC transmission systems. However, there are few studies on subsynchronous oscillation control methods for direct-drive wind power soft direct delivery systems, and usually focus on subsynchronous oscillation control under a single operating point, lacking analysis and comparison of suppression effects under multiple operating conditions. Considering that the operating state of wind turbines changes greatly and the working conditions are complex, how to realize the subsynchronous oscillation control of the direct-drive wind power soft direct delivery system under complex working conditions still needs to be further explored.

Contents of the invention

In order to solve the above-mentioned deficiencies mentioned in the background technology, the object of the present invention is to provide an adaptive direct-drive wind power soft direct delivery system subsynchronous oscillation control method,

The purpose of the present invention can be achieved through the following technical solutions: an adaptive direct-drive wind power soft direct delivery system subsynchronous oscillation control method, the method includes the following steps:

Establish a direct-drive wind power soft direct delivery system model to analyze the control link strongly related to the subsynchronous oscillation mode, and propose an additional location scheme for the subsynchronous oscillation adaptive control;

Design an adaptive control method to suppress the subsynchronous oscillation of the direct drive wind power soft direct delivery system;

Different additional position schemes are used to establish optimization models of parameters of different adaptive control methods, and the optimal control parameters of the control methods under each additional position scheme are determined through the optimization models of parameters of different adaptive control methods;

Using the obtained optimal control parameters, the subsynchronous oscillation control effect of each additional position scheme is compared, the evaluation index is established, the optimal additional position of the controller is determined, and the subsynchronous oscillation suppression is realized.

Preferably, the process of establishing a direct-drive wind power soft direct delivery system model includes the following steps:

Direct drive wind power flexible direct delivery system includes: permanent magnet direct drive wind farm, AC line, flexible DC transmission system and infinite power supply; among them, permanent magnet direct drive wind farm consists of permanent magnet direct drive fan, fan side converter, back-to-back The DC link of the converter is composed of the wind turbine grid-side converter; the flexible DC transmission system is composed of a flexible DC fan-side converter station, a DC transmission cable and a flexible DC grid-side converter station;

The voltage equation, flux linkage equation, torque equation and motion equation formula of the permanent magnet direct drive fan are as follows:

T _e = ψ _f i _qs (3)

Among them, ψ _ds and ψ _qs represent the stator dq-axis flux linkage respectively, u _ds , u _qs , i _ds , i _qs are the dq-axis components of the stator voltage and stator current of the direct drive fan, respectively, R _s , L _s are the direct drive fan The stator resistance and stator inductance of the drive fan, J represents the inertia of the direct drive fan shaft, D is the damping of the direct drive fan rotor, ω _s , ω _r are the angular velocity of the synchronous magnetic field and the rotational angular velocity of the double-fed fan rotor per unit, T _m , T _e are the mechanical torque and electromagnetic torque of the direct drive fan, respectively;

The fan-side converter adopts double closed-loop vector control with zero d-axis, the outer ring q-axis controls the actual active output P of the direct drive fan with PI, and the inner ring dq-axis controls i _ds and i _qs respectively with PI, as follows:

分别表示变量i_ds,i_qs的参考值，上标*表示对应变量的参考值；K_pa和K_ia分别表示PI_a控制器的比例系数和积分系数，下标a＝1,2,3…表示第a个PI控制器的比例系数和积分系数；u_d1,u_q1分别表示风机机侧变流器交流侧的dq轴电压；in,

respectively represent the reference values of the variables i _ds and i _qs , the superscript * represents the reference value of the corresponding variable; K _pa and K _ia represent the proportional coefficient and integral coefficient of the PI _a controller respectively, and the subscript a=1,2,3... Indicates the proportional coefficient and integral coefficient of the a-th PI controller; u _d1 , u _q1 respectively indicate the dq axis voltage of the AC side of the converter on the fan side;

The grid-side converter of the wind turbine adopts the control strategy of constant DC voltage and constant reactive power. The dq axis of the outer ring controls the DC link voltage and the reactive power Q _g of the grid side by PI, and the dq axis of the inner ring controls the grid-side current by PI respectively. The dq axis components i _dg , i _qg are as follows:

Among them, u _dc is the back-to-back DC link voltage, u _d2 and u _q2 respectively represent the dq axis voltage of the AC side of the fan grid side converter; PI ₄ ~ PI ₇ are used for the control of the fan grid side converter;

The converter station at the sending end of the soft direct wind turbine adopts a constant AC voltage control strategy. The dq axes of the outer ring control the dq axes voltage u _wfd0 , u _wfq0 of the converter station with PI, and the dq axes of the inner ring control the dq axes of the AC side respectively with PI The current i _wfd , i _wfq is as follows:

Among them, u _wfd and u _wfq respectively represent the dq axis voltage of the AC measurement point of the converter station; PI ₈ ~ PI ₁₁ are used for the control of the converter station at the side sending end of the soft direct wind turbine;

Preferably, the additional position scheme of the adaptive control of subsynchronous oscillation is determined by key variables and main control parameters affecting subsynchronous oscillation:

The state space equation is established based on the model of the direct-drive fan flexible direct delivery system, the key variables affecting the subsynchronous oscillation of the direct-drive wind power flexible direct delivery system are analyzed, and the controllability index m _ci of formula (8) is used to compare the control position of the additional position of the subsynchronous oscillation Pros and cons:

Among them, i and k represent the number of the state variable and the number of the eigenvalue respectively, b _i represents the column vector corresponding to the control variable u _i in the control matrix, and β _k represents the left eigenvector corresponding to the kth eigenvalue;

Using the observability index m _oi of formula (9) to compare the advantages and disadvantages of the subsynchronous oscillation control measurement position:

Among them, j represents the serial number of the control variable, c _j represents the row vector corresponding to the output variable y _j in the output matrix, and α _k represents the right eigenvector corresponding to the kth eigenvalue;

According to the eigenvalue analysis and modeling simulation of the subsynchronous oscillation of the direct-drive wind power soft direct delivery system, the control parameters that have a great influence on the subsynchronous oscillation mode are obtained.

Preferably, the adaptive control method is as follows:

Set the input signal and output signal of the additional controller of the direct drive wind power soft direct delivery system as y and u, then the input signal and output signal of the controller under discrete time are y(k) and u(k) respectively;

Based on the input signal and output signal of the adaptive control method, the dynamic linearization of the direct-drive wind power soft direct delivery system is realized, as shown in formula (10):

y(k+1)=y(k)+Φ(k)Δu(k) (10)

Φ(k) represents the pseudo partial derivative of the system, Δu(k)=u(k)-u(k-1);

Establish the partial derivative estimation criterion function of the input and output data of the subsynchronous oscillation controller, as shown in formula (11).

表示风电送出系统的伪偏导数的估计值；μ is the penalty coefficient representing the amount of change in the pseudo partial derivative,

Represents the estimated value of the pseudo partial derivative of the wind power delivery system;

Calculate the partial derivative of formula (11), and obtain the pseudo partial derivative estimation formula of the direct-drive wind power soft direct delivery system, as shown in formula (12):

为输出的估计误差，F＝1-γ，η为表示伪偏导数估计算法的步长因子，γ为估计误差e₀(k)误差增益；in,

For the estimated error of the output, F=1-γ, η is the step factor representing the pseudo partial derivative estimation algorithm, and γ is the estimated error e ₀ (k) error gain;

The criterion function of the established controller output is shown in formula (13):

The control law of the adaptive control method is shown in formula (14):

Among them, ρ ₀ , ρ ₁ are the step size factors for adjusting the control rate; λ represents the penalty coefficient of the system input signal.

Preferably, the partial derivative estimation criterion function takes the minimization of the dynamic linearization output and the real output as a target, and meanwhile adds a partial derivative variation with a penalty term.

Preferably, the optimization model of the parameters of the adaptive control method includes:

objective function

The sum of the square of the dq-axis error signal of the outer ring of the wind turbine grid-side converter and the dq-axis error signal of the outer ring of the soft direct-feeding end converter station in time is used as the performance index, and the objective function is established as shown in formula (15):

Among them, J is the optimization objective function, t is the time, e _wd (t), e _wq (t), e _vd (t), e _vq (t) are respectively the d-axis outer ring DC voltage control The error signal of the wind turbine grid-side converter q-axis outer ring reactive power control error signal, the error signal of the d-axis outer ring AC voltage control of the soft straight fan side send-end converter station and the soft straight fan side send-end converter station The error signal of the q-axis outer ring AC voltage control;

optimization parameters

The controller parameters to be optimized include: penalty coefficient μ of pseudo partial derivative variation, step factors ρ ₀ and ρ ₁ for adjusting control rate, penalty coefficient λ of system input signal, step factor η of pseudo partial derivative estimation, estimated error gain γ;

Restrictions

According to the design principle of the adaptive control method of subsynchronous oscillation, the feasible range of controller parameters has the following constraints, as shown in equation (16):

为伪偏导数估计值

的上界。in,

Estimated values for the pseudo partial derivatives

upper bound.

Preferably, the optimization model of the parameters of the adaptive control method adopts the particle swarm optimization algorithm to optimize the model parameters, including:

First, initialize the particle swarm and calculate the fitness of each particle; second, update the speed and position of the particle and recalculate the fitness to find the globally optimal particle; finally, judge whether the particle swarm algorithm converges, if not, return to the previous step , continue to update the particle velocity and position, if it has converged, it means that the optimization of the controller parameters is completed, and the optimal parameters of the controller under the additional position are successfully obtained.

Preferably, the process of realizing subsynchronous oscillation suppression is as follows:

Determine additional location schemes for adaptive control of subsynchronous oscillations;

Determine the optimal control parameters for each additional position;

Establish n direct-drive wind power soft direct delivery system subsynchronous oscillation complex working conditions scenarios;

For the subsynchronous oscillation controllers at each additional position, the verification of subsynchronous oscillation suppression under complex working conditions is carried out respectively, and the objective function J _l,s of each additional position and each working condition scene is obtained, where the subscripts l and s are respectively Indicates the additional location and working condition scene number;

Obtain the comprehensive evaluation index of subsynchronous oscillation control at each additional position, expressed as

The additional position with the minimum comprehensive evaluation index of subsynchronous oscillation control is selected as the selected position to realize subsynchronous oscillation suppression.

Preferably, a device comprising:

one or more processors;

memory for storing one or more programs;

When one or more of the programs are executed by one or more of the processors, one or more of the processors implement the above-mentioned adaptive direct-drive wind power soft output system subsynchronous oscillation control method .

Preferably, when the computer executable instructions are executed by a computer processor, they are used to implement the above-mentioned adaptive direct-drive wind power soft output system subsynchronous oscillation control method.

Beneficial effects of the present invention:

Based on the input and output data of the strategy, the adaptive control method of the present invention realizes dynamic linearization of the direct-drive wind power flexible straight system, requires less system information, and has low dependence on system modeling. Under various working conditions where the number of fans changes, the subsynchronous oscillation can be effectively suppressed, and it has strong adaptability.

Description of drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings that need to be used in the description of the embodiments or the prior art. Obviously, for those of ordinary skill in the art, In other words, on the premise of not paying creative work, other drawings can also be obtained based on these drawings;

Fig. 1 is method flowchart of the present invention;

Fig. 2 is a schematic diagram of a case of the direct-drive wind power flexible straight grid-connected system of the present invention;

Fig. 3 is a schematic diagram of the subsynchronous oscillation adaptive control structure of the present invention;

Fig. 4 is the flow chart of particle swarm control parameter optimization method of the present invention;

Fig. 5 is a schematic diagram of the application of the adaptive control additional position of the present invention;

Fig. 6 is the effect diagram of the adaptive control application of the present invention;

Fig. 7 is a change diagram of estimated values of pseudo partial derivatives in the adaptive control process of the present invention.

detailed description

The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

As shown in Fig. 1, an adaptive subsynchronous oscillation control method for direct-drive wind power soft direct delivery system includes the following steps:

Step 1: Establish the mathematical model of the direct-drive wind power soft direct delivery system

As shown in Figure 1, the direct drive wind power transmission system includes: permanent magnet direct drive wind farm, AC line, flexible DC transmission system and infinite power supply. Among them, the permanent magnet direct drive wind farm is composed of the permanent magnet direct drive fan, the fan side converter, the DC link of the back-to-back converter, and the fan grid side converter; the flexible DC transmission system consists of the flexible DC fan side converter station , DC transmission cables, and flexible direct grid side converter stations.

The voltage equation, flux equation, torque equation and motion equation of the permanent magnet direct drive fan are shown in equations (1)-(4):

T _e = ψ _f i _qs (3)

Among them, ψ _ds and ψ _qs represent the stator dq-axis flux linkage respectively, u _ds , u _qs , i _ds , i _qs are the dq-axis components of the stator voltage and stator current of the direct drive fan, respectively, R _s , L _s are the direct drive fan The stator resistance and stator inductance of the drive fan, J represents the inertia of the direct drive fan shaft, D is the damping of the direct drive fan rotor, ω _s , ω _r are the angular velocity of the synchronous magnetic field and the rotational angular velocity of the double-fed fan rotor per unit, T _m , T _e are the mechanical torque and electromagnetic torque of the direct drive fan, respectively.

The converter on the fan side adopts a double-closed-loop vector control strategy with zero d-axis. The outer ring q-axis uses PI to control the actual active output P of the direct-drive fan, and the inner ring dq-axis uses PI to control i _ds , i _qs , respectively, that is, the formula ( 5):

分别表示变量i_ds,i_qs的参考值，上标*表示对应变量的参考值，该表示方法下文相同；K_pa和K_ia分别表示PI_a控制器的比例系数和积分系数，其下标a＝1,2,3…表示第a个PI控制器的比例系数和积分系数，该表示方法下文相同；u_d1,u_q1分别表示风机机侧变流器交流侧的dq轴电压；in,

represent the reference values of the variables i _ds and i _qs respectively, the superscript * represents the reference value of the corresponding variable, and the expression method is the same below; K _pa and K _ia represent the proportional coefficient and integral coefficient of the PI _a controller respectively, and the subscript a = 1, 2, 3... represents the proportional coefficient and integral coefficient of the a-th PI controller, and the expression method is the same below; u _d1 , u _q1 represent the dq axis voltages of the AC side of the converter on the fan side respectively;

The grid-side converter of the wind turbine adopts the control strategy of constant DC voltage and constant reactive power. The dq axis of the outer ring controls the DC link voltage and the reactive power Q _g of the grid side by PI, and the dq axis of the inner ring controls the grid-side current by PI respectively. dq-axis components i _dg , i _qg , namely formula (6):

Among them, u _dc is the back-to-back DC link voltage, u _d2 and u _q2 respectively represent the dq axis voltage of the AC side of the fan grid side converter; PI ₄ ~ PI ₇ are used for the control of the fan grid side converter;

The converter station at the sending end of the soft direct wind turbine adopts a constant AC voltage control strategy. The dq axes of the outer ring control the dq axes voltage u _wfd0 , u _wfq0 of the converter station with PI, and the dq axes of the inner ring control the dq axes of the AC side respectively with PI Current i _wfd , i _wfq , namely formula (7):

Among them, u _wfd and u _wfq respectively represent the dq axis voltage of the AC measurement point of the converter station; PI ₈ ~ PI ₁₁ are used for the control of the converter station at the side sending end of the soft direct wind turbine;

The control strategy of the receiving-end converter station on the soft DC grid side is the same as that of the grid-side converter of the direct-drive wind farm, both of which are constant DC voltage and constant reactive power, and will not be repeated here.

Step 2: Obtain the key variables and main control parameters that affect the subsynchronous oscillation, and determine the additional location scheme for the adaptive control of the subsynchronous oscillation

Firstly, the state space equation is established based on the mathematical model of the direct drive wind turbine direct delivery system, and the key variables affecting the subsynchronous oscillation of the direct drive wind power direct delivery system are analyzed. Using the controllability index m _ci of formula (8) to compare the advantages and disadvantages of the additional position of subsynchronous oscillation control:

Among them, i and k represent the number of the state variable and the number of the eigenvalue respectively, b _i represents the column vector corresponding to the control variable u _i in the control matrix, and β _k represents the left eigenvector corresponding to the kth eigenvalue.

Using the observability index m _oi of formula (9) to compare the advantages and disadvantages of the subsynchronous oscillation control measurement position:

Among them, j represents the number of the control variable, c _j represents the row vector corresponding to the output variable y _j in the output matrix, and α _k represents the right eigenvector corresponding to the kth eigenvalue.

本实施方案中所获得的次同步振荡较优量测位置有：

It should be noted that the optimal additional positions of the subsynchronous oscillation obtained in this embodiment are: u

The preferred measurement positions of the subsynchronous oscillation obtained in this embodiment are:

Secondly, based on the eigenvalue analysis and modeling simulation of the subsynchronous oscillation of the direct-drive wind power soft direct delivery system, the controller parameters that have a greater impact on the subsynchronous oscillation mode are obtained.

The main control parameters affecting subsynchronous oscillation obtained in this embodiment include: K _p4 , K _i4 , K _p5 , K _i5 , K _p8 , K _i8 , K _p9 , and K _i9 .

等多种配对方案。Furthermore, the additional control scheme can be represented by (A, B), where A is the signal input to the controller, and B is the signal output from the controller. Combinations in which the additional signal and the measurement signal do not exist in the same converter or converter station are excluded, thus:

and other matching schemes.

Step 3: Design an adaptive control method for the subsynchronous oscillation of the direct-drive wind power soft direct delivery system

Assuming that the input signal and output signal of the additional controller of the direct-drive wind power transmission system are y and u, then the input signal and output signal of the controller in discrete time are y(k) and u(k) respectively.

Based on the control strategy is the input signal and output signal, the dynamic linearization of the direct-drive wind power soft direct delivery system is realized, as shown in formula (10):

y(k+1)=y(k)+Φ(k)Δu(k) (10)

Φ(k) represents the pseudo partial derivative of the system, Δu(k)=u(k)-u(k-1).

Further, the partial derivative estimation criterion function of the input and output data of the subsynchronous oscillation controller is established, as shown in formula (11).

表示风电送出系统的伪偏导数的估计值。The objective of this criterion function is to minimize the dynamic linearization output and the real output, and at the same time add the partial derivative variation with a penalty item to reduce the influence of disturbance on the control strategy. μ is the penalty coefficient representing the amount of change in the pseudo partial derivative,

Represents the estimated value of the pseudo partial derivative of the wind power sending system.

Calculate the partial derivative of formula (11), and obtain the pseudo partial derivative estimation formula of the direct-drive wind power soft direct delivery system, as shown in formula (12):

为输出的估计误差，F＝1-γ。η为表示伪偏导数估计的步长因子，γ为估计误差e₀(k)误差增益。where Γ(k)=η/(Δu(k) ² +μ),

is the estimation error of the output, F=1-γ. η is the step size factor representing the estimation of the pseudo partial derivative, and γ is the error gain of the estimation error e ₀ (k).

The ultimate goal of the subsynchronous oscillation control of the direct-drive wind power output system is to stabilize the system, and for a certain control link of the system converter, it means that the input error of the PI controller approaches zero. The criterion function of the established controller output is shown in formula (13):

The control law of the control strategy is further deduced as shown in formula (14):

Among them, ρ ₀ , ρ ₁ are the step size factors for adjusting the control rate; λ represents the penalty coefficient of the system input signal.

The block diagram of the adaptive control method is shown in Figure 2.

Step 4: Establish control parameter optimization model

1) Objective function

Taking the sum of the dq-axis error signal of the outer ring of the wind turbine grid-side converter and the square of the dq-axis error signal of the outer ring of the soft direct-feeding converter station as the performance index, the objective function is established as shown in formula (15) :

Among them, J is the optimization objective function, t is the time, e _wd (t), e _wq (t), e _vd (t), e _vq (t) are respectively the d-axis outer ring DC voltage control The error signal of the wind turbine grid-side converter q-axis outer ring reactive power control error signal, the error signal of the d-axis outer ring AC voltage control of the soft straight fan side send-end converter station and the soft straight fan side send-end converter station The error signal of the q-axis outer ring AC voltage control.

2) Optimize parameters

The controller parameters to be optimized include: penalty coefficient μ of pseudo partial derivative variation, step factors ρ ₀ and ρ ₁ for adjusting control rate, penalty coefficient λ of system input signal, step factor η of pseudo partial derivative estimation, estimated Error gain γ.

3) Constraints

According to the design principle of the adaptive control method of subsynchronous oscillation, the feasible range of controller parameters has the following constraints, as shown in equation (16):

为伪偏导数

的上界。in,

is the pseudo partial derivative

upper bound.

Step 5: Use particle swarm optimization algorithm to optimize model parameters

First, initialize the particle swarm and calculate the fitness of each particle; second, update the speed and position of the particle and recalculate the fitness to find the globally optimal particle; finally, judge whether the particle swarm algorithm converges, if not, return to the previous step , continue to update the particle velocity and position, if it has converged, it means that the optimization of the controller parameters is completed, and the optimal parameters of the controller at this additional position are successfully obtained. The flow chart of particle swarm control parameter optimization method is shown in Fig.3.

Step 6: Evaluate the subsynchronous oscillation control effect of the controller for each additional position scheme

The evaluation method of subsynchronous oscillation control effect of each additional location scheme mainly has the following steps:

1) Based on the analysis method of the direct drive wind power soft direct delivery system described in S1, determine the additional position scheme of the subsynchronous oscillation adaptive control;

2) Based on the parameter optimization method described in S3, determine the optimal control parameters under each additional position;

3) Establish n direct-drive wind power soft direct delivery system subsynchronous oscillation complex working conditions scenarios;

4) For the subsynchronous oscillation controllers at each additional position, the verification of subsynchronous oscillation suppression under complex working conditions is carried out respectively, and the objective function J _l,s of each additional position and each working condition scene is obtained, and the subscripts l and s are respectively Indicates the additional location and working condition scene number;

5) Obtain the comprehensive evaluation index of subsynchronous oscillation control at each additional position, expressed as

6) The additional position with the smallest comprehensive evaluation index of subsynchronous oscillation control is selected as the selected position to realize subsynchronous oscillation suppression.

After evaluating the subsynchronous oscillation control effect of the controller under complex working conditions, the additional position of the adaptive control is selected as shown in Figure 4. The additional position is located in the q-axis control loop of the converter station at the sending end of the soft straight fan side.

What needs to be further explained is that in the specific implementation process, a 100MW direct-drive wind farm is established and simulated through the grid connection of the flexible DC system, and the self-adaptive subsynchronous oscillation controller proposed by the present invention is applied, and the oscillation suppression effect is shown in Figure 5 . In this scene, v=7m/s, P=0.1933p.u. in 4~6s, v=8m/s, P=0.2885p.u. in 6~8s, v=10m/s, P=0.5635p.u., 10~10s 12s has v=11m/s, P=0.75p.u. It can be seen that if there is no subsynchronous oscillation control, the active output waveform of the system will start to oscillate when switching between high wind speed and high active output at t=8s, and the oscillation will be more severe at 10-12s. The self-adaptive control method of the present invention does not generate subsynchronous oscillation phenomenon in the system under each working condition, which illustrates the effectiveness of the self-adaptive control method of the present invention in suppressing subsynchronous oscillation. The change value of the pseudo partial derivative in the subsynchronous oscillation control process of the present invention is shown in FIG. 6 .

Based on the same inventive concept, the present invention also provides a computer device, which includes: one or more processors, and a memory for storing one or more computer programs; the program includes program instructions, and the processor is used to execute Program instructions stored in memory. The processor may be a central processing unit (Central Processing Unit, CPU), or other general-purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), field programmable gate arrays (Field-Programmable GateArray, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc., which are the computing core and control core of the terminal, which are used to implement one or more instructions, specifically for Load and execute one or more instructions in the computer storage medium to realize the above method.

It should be further explained that, based on the same inventive concept, the present invention also provides a computer storage medium, on which a computer program is stored, and when the computer program is run by a processor, the above method is executed. The storage medium may be any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electrical, magnetic, infrared, or semiconductor system, device, or device, or any combination thereof. More specific examples (non-exhaustive list) of computer readable storage media include: electrical connections with one or more leads, portable computer disks, hard disks, random access memory (RAM), read only memory (ROM), Erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination of the above. In the present invention, a computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

In the description of this specification, descriptions referring to the terms "one embodiment", "example", "specific example" and the like mean that specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one of the present disclosure. In an embodiment or example. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

The basic principles, main features and advantages of the present disclosure have been shown and described above. Those skilled in the industry should understand that the present disclosure is not limited by the above-mentioned embodiments. The above-mentioned embodiments and descriptions only illustrate the principle of the present disclosure. Variations and improvements all fall within the scope of the claimed disclosure.

Claims (10)

1. An adaptive direct-drive wind power soft direct delivery system subsynchronous oscillation control method is characterized in that the method comprises the following steps: Establish a direct-drive wind power soft direct delivery system model to analyze the control link strongly related to the subsynchronous oscillation mode, and propose an additional location scheme for the subsynchronous oscillation adaptive control; Design an adaptive control method to suppress the subsynchronous oscillation of the direct drive wind power soft direct delivery system; Different additional position schemes are used to establish optimization models of parameters of different adaptive control methods, and the optimal control parameters of the control methods under each additional position scheme are determined through the optimization models of parameters of different adaptive control methods; Using the obtained optimal control parameters, the subsynchronous oscillation control effect of each additional position scheme is compared, the evaluation index is established, the optimal additional position of the controller is determined, and the subsynchronous oscillation suppression is realized. 2. The subsynchronous oscillation control method of an adaptive direct-drive wind power flexible direct delivery system according to claim 1, wherein the process of establishing a direct-drive wind power flexible direct delivery system model comprises the following steps: Direct drive wind power flexible direct delivery system includes: permanent magnet direct drive wind farm, AC line, flexible DC transmission system and infinite power supply; among them, permanent magnet direct drive wind farm consists of permanent magnet direct drive fan, fan side converter, back-to-back The DC link of the converter is composed of the wind turbine grid-side converter; the flexible DC transmission system is composed of a flexible DC fan-side converter station, a DC transmission cable and a flexible DC grid-side converter station; The voltage equation, flux linkage equation, torque equation and motion equation formula of the permanent magnet direct drive fan are as follows:

T _e = ψ _f i _qs (3)

Among them, ψ _ds and ψ _qs represent the stator dq-axis flux linkage respectively, u _ds , u _qs , i _ds , i _qs are the dq-axis components of the stator voltage and stator current of the direct drive fan, respectively, R _s , L _s are the direct drive fan The stator resistance and stator inductance of the drive fan, J represents the inertia of the direct drive fan shaft, D is the damping of the direct drive fan rotor, ω _s , ω _r are the angular velocity of the synchronous magnetic field and the rotational angular velocity of the double-fed fan rotor per unit, T _m , T _e are the mechanical torque and electromagnetic torque of the direct drive fan, respectively; The fan-side converter adopts double closed-loop vector control with zero d-axis, the outer ring q-axis controls the actual active output P of the direct drive fan with PI, and the inner ring dq-axis controls i _ds and i _qs respectively with PI, as follows:

in,

respectively represent the reference values of the variables i _ds and i _qs , the superscript * represents the reference value of the corresponding variable; K _pa and K _ia represent the proportional coefficient and integral coefficient of the PI _a controller respectively, and the subscript a=1,2,3... Indicates the proportional coefficient and integral coefficient of the a-th PI controller; u _d1 , u _q1 respectively indicate the dq axis voltage of the AC side of the converter on the fan side; The grid-side converter of the wind turbine adopts the control strategy of constant DC voltage and constant reactive power. The dq axis of the outer ring controls the DC link voltage and the reactive power Q _g of the grid side by PI, and the dq axis of the inner ring controls the grid-side current by PI respectively. The dq axis components i _dg , i _qg are as follows:

Among them, u _dc is the back-to-back DC link voltage, u _d2 and u _q2 respectively represent the dq axis voltage of the AC side of the fan grid side converter; PI ₄ ~ PI ₇ are used for the control of the fan grid side converter; The converter station at the sending end of the soft direct wind turbine adopts a constant AC voltage control strategy. The dq axes of the outer ring control the dq axes voltage u _wfd0 , u _wfq0 of the converter station with PI, and the dq axes of the inner ring control the dq axes of the AC side respectively with PI The current i _wfd , i _wfq is as follows:

Among them, u _wfd and u _wfq represent the dq axis voltages of the AC measurement points of the converter station respectively; PI ₈ ~ PI ₁₁ are used for the control of the converter station at the sending end of the flexible direct wind turbine. 3. A method for subsynchronous oscillation control of an adaptive direct-drive wind power soft direct delivery system according to claim 1, characterized in that the additional position scheme of the adaptive control of subsynchronous oscillation consists of a key that affects subsynchronous oscillation Variables and main control parameters determined: The state space equation is established based on the model of the direct-drive fan flexible direct delivery system, the key variables affecting the subsynchronous oscillation of the direct-drive wind power flexible direct delivery system are analyzed, and the controllability index m _ci of formula (8) is used to compare the control position of the additional position of the subsynchronous oscillation Pros and cons:

Among them, i and k represent the number of the state variable and the number of the eigenvalue respectively, b _i represents the column vector corresponding to the control variable u _i in the control matrix, and β _k represents the left eigenvector corresponding to the kth eigenvalue; Using the observability index m _oi of formula (9) to compare the advantages and disadvantages of the subsynchronous oscillation control measurement position:

Among them, j represents the serial number of the control variable, c _j represents the row vector corresponding to the output variable y _j in the output matrix, and α _k represents the right eigenvector corresponding to the kth eigenvalue; According to the eigenvalue analysis and modeling simulation of the subsynchronous oscillation of the direct-drive wind power soft direct delivery system, the control parameters that have a great influence on the subsynchronous oscillation mode are obtained. 4. The subsynchronous oscillation control method of an adaptive direct-drive wind power soft direct delivery system according to claim 1, wherein the adaptive control method is as follows: Set the input signal and output signal of the additional controller of the direct drive wind power soft direct delivery system as y and u, then the input signal and output signal of the controller under discrete time are y(k) and u(k) respectively; Based on the input signal and output signal of the adaptive control method, the dynamic linearization of the direct-drive wind power soft direct delivery system is realized, as shown in formula (10): y(k+1)=y(k)+Φ(k)Δu(k) (10) Φ(k) represents the pseudo partial derivative of the system, Δu(k)=u(k)-u(k-1); Establish the partial derivative estimation criterion function of the input and output data of the subsynchronous oscillation controller, as shown in formula (11),

μ is the penalty coefficient representing the variation of the pseudo partial derivative,

Represents the estimated value of the pseudo partial derivative of the wind power delivery system; Calculate the partial derivative of formula (11), and obtain the pseudo partial derivative estimation formula of the direct-drive wind power soft direct delivery system, as shown in formula (12):

where Γ(k)=η/(Δu(k) ² +μ),

For the estimated error of the output, F=1-γ, η is the step factor representing the pseudo partial derivative estimation algorithm, and γ is the estimated error e ₀ (k) error gain; The criterion function of the established controller output is shown in formula (13):

The control law of the adaptive control method is shown in formula (14):

Among them, ρ ₀ , ρ ₁ are the step size factors for adjusting the control rate; λ represents the penalty coefficient of the system input signal. 5. The subsynchronous oscillation control method of an adaptive direct-drive wind power output system according to claim 4, wherein the partial derivative estimation criterion function uses the minimized dynamic linearization output and the real output as objective, while adding the amount of partial derivative change with a penalty term. 6. The subsynchronous oscillation control method of an adaptive direct-drive wind power output system according to claim 1, wherein the optimization model of parameters of the adaptive control method comprises: objective function The sum of the square of the dq-axis error signal of the outer ring of the wind turbine grid-side converter and the dq-axis error signal of the outer ring of the soft direct-feeding end converter station in time is used as the performance index, and the objective function is established as shown in formula (15):

Among them, J is the optimization objective function, t is the time, e _wd (t), e _wq (t), e _vd (t), e _vq (t) are respectively the d-axis outer ring DC voltage control The error signal of the wind turbine grid-side converter q-axis outer ring reactive power control error signal, the error signal of the d-axis outer ring AC voltage control of the soft straight fan side send-end converter station and the soft straight fan side send-end converter station The error signal of the q-axis outer ring AC voltage control; optimization parameters The controller parameters to be optimized include: penalty coefficient μ of pseudo partial derivative variation, step factors ρ ₀ and ρ ₁ for adjusting control rate, penalty coefficient λ of system input signal, step factor η of pseudo partial derivative estimation, estimated error gain γ; Restrictions According to the design principle of the adaptive control method of subsynchronous oscillation, the feasible range of controller parameters has the following constraints, as shown in equation (16):

in,

Estimated values for the pseudo partial derivatives

upper bound. 7. The subsynchronous oscillation control method of a kind of self-adaptive direct drive wind power soft direct delivery system according to claim 6, characterized in that, the optimization model of the parameters of the self-adaptive control method adopts the particle swarm optimization algorithm to optimize the model parameters, including : First, initialize the particle swarm and calculate the fitness of each particle; second, update the speed and position of the particle and recalculate the fitness to find the globally optimal particle; finally, judge whether the particle swarm algorithm converges, if not, return to the previous step , continue to update the particle velocity and position, if it has converged, it means that the optimization of the controller parameters is completed, and the optimal parameters of the controller under the additional position are successfully obtained. 8. A method for controlling subsynchronous oscillation of an adaptive direct-drive wind power soft direct delivery system according to claim 1, wherein the process for realizing subsynchronous oscillation suppression is as follows: Determine additional location schemes for adaptive control of subsynchronous oscillations; Determine the optimal control parameters for each additional position; Establish n direct-drive wind power soft direct delivery system subsynchronous oscillation complex working conditions scenarios; For the subsynchronous oscillation controllers at each additional position, the verification of subsynchronous oscillation suppression under complex working conditions is carried out respectively, and the objective function J _l,s of each additional position and each working condition scene is obtained, where the subscripts l and s are respectively Indicates the additional location and working condition scene number; Obtain the comprehensive evaluation index of subsynchronous oscillation control at each additional position, expressed as

The additional position with the minimum comprehensive evaluation index of subsynchronous oscillation control is selected as the selected position to realize subsynchronous oscillation suppression. 9. A device, characterized in that it comprises: one or more processors; memory for storing one or more programs; When one or more of the programs are executed by one or more of the processors, the one or more of the processors realizes an adaptive direct-drive wind power flexible device according to any one of claims 1-8. Straight out of the system subsynchronous oscillation control method. 10. A storage medium comprising computer-executable instructions, wherein the computer-executable instructions are used to perform an adaptive method according to any one of claims 1-8 when executed by a computer processor. Subsynchronous oscillation control method for direct drive wind power soft direct output system.

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