A safety risk suppression control method for equipment speed fluctuation during low voltage ride-through period

Abstract

The present invention discloses a safety risk suppression control method for equipment speed fluctuation during low voltage ride-through period, which relates to the technical field of wind turbine stability research, and includes the following steps: S1, temporarily locking the integral link of pitch angle control during the low voltage ride-through fault of the wind turbine, and establishing the system state space equation of the wind turbine rotor after the integral link is locked; S2, modifying the system state space equation using the system state feedback matrix. The present invention starts from two aspects respectively. One is to lock the integral link of pitch angle control during the fault to eliminate the hysteresis of pitch angle control, and solve the problem of excessive speed drop caused by the continuous action of pitch angle when the speed returns to the rated value. The second is to introduce the system state feedback matrix during the fault to obtain the desired system response performance, improve the overall damping ratio of the system, and at the same time enhance the low-frequency and high-frequency fluctuation suppression capability of the speed, and improve the speed response characteristics of the wind turbine.

Description

Technical Field

[0001] The present invention relates to the technical field of wind turbine stability research, and more specifically to a safety risk suppression control method for equipment speed fluctuation during a low voltage ride-through period. Background Art

[0002] In order to maintain the safety and stability of the power system, wind turbines need to have the ability to ride through faults. However, the active power of wind turbines will change significantly during fault ride-through, causing large fluctuations in the rotor speed and long-term oscillations.

[0003] The low voltage ride-through capability of wind turbines is an important evaluation indicator for evaluating the safe and stable operation of power systems with high wind power penetration. During low voltage ride-through, wind turbines need to maintain operation and provide reactive power support to the power grid until the fault is cleared. However, when maintaining operation, wind turbines need to reduce mechanical load stress by delaying the active power recovery time. Therefore, during low voltage ride-through, the energy accumulated in the rotor due to the inability to be transmitted to the power grid will cause speed fluctuations, affecting the safe and stable operation of wind turbines. The existing wind turbine pitch angle control strategy has a poor transient control effect on this fluctuation. The sharp fluctuations in the pitch angle position caused by speed fluctuations will affect the mechanical load. With the long-term accumulation of load and fatigue damage, it may even cause malicious events such as tower collapse, seriously affecting the safe operation of wind farms.

[0004] Therefore, a safety risk suppression control method for equipment speed fluctuation during low voltage ride-through period is urgently needed to improve the speed fluctuation characteristics of wind turbines during faults. Summary of the invention

[0005] In order to overcome the defects existing in the above-mentioned prior art, the present invention discloses a safety risk suppression control method for equipment speed fluctuation during low voltage ride-through period, so as to improve the speed fluctuation characteristics of wind turbines during faults. The present invention starts from two aspects respectively. One is to lock the integral link of pitch angle control during faults to eliminate the hysteresis of pitch angle control, and solve the problem of excessive speed drop caused by the continuous action of pitch angle when the speed returns to the rated value. The second is to introduce the system state feedback matrix during faults to obtain the desired system response performance, improve the damping ratio of the system as a whole, and at the same time enhance the low-frequency and high-frequency fluctuation suppression capability of the speed, and improve the speed response characteristics of the wind turbine.

[0006] In order to achieve the above objectives, the technical solution adopted by the present invention is:

[0007] A safety risk suppression control method for equipment speed fluctuation during low voltage ride-through period, comprising the following steps:

[0008] 1. Establishment of state space equation

[0009] S1. Temporarily lock the integral link of the pitch angle control during the low voltage ride-through fault of the wind turbine, and after the integral link is locked, establish the system state space equation of the wind turbine rotor;

[0010] In the present invention, the integral link of the pitch angle control refers to the time integration of the difference between the target rotational speed and the actual rotational speed, which is used to eliminate the static error of the pitch angle control on a long time scale.

[0011] During the low voltage ride-through of wind turbines, the goal of wind turbine pitch angle control is to make mechanical power quickly track the change of electromagnetic power to alleviate the low-frequency fluctuation of speed, but due to the delay of the integral link, the tracking change of mechanical power has a large lag. In addition, during low voltage ride-through, due to the short time and relatively small wind speed fluctuation, the integral link can be temporarily locked during the fault period to eliminate the lag of pitch angle control and solve the problem of excessive speed drop caused by the continuous action of the pitch angle when the speed returns to the rated value.

[0012] Preferably, the system state space equation in step S1 is:

[0013] ;

[0014] Among them, the top of the variable represents the differential of the dependent variable, is the state variable, is the system matrix, is the control matrix, To control the amount.

[0015] Preferably, the state variables in the state space equation of the S1 step system are , system matrix , control matrix It is expressed as:

[0016] ;

[0017] ;

[0018] ;

[0019] ;

[0020] ;

[0021] ;

[0022] in, Indicates the increment of the relevant variable, subscript represents the initial value of the relevant variable, Indicates the partial differential symbol, superscript represents the transpose of a matrix, and are the inertia constants of the wind wheel and the generator, is the generator speed, is the wind rotor rotation angular velocity, , are the torques of the wind wheel and the transmission chain respectively, is the equivalent damping constant of the transmission chain, is the equivalent stiffness of the transmission chain, is the gearbox transmission ratio, is the blade pitch angle, is the ratio of the pitch angle controller, is the time constant of the pitch mechanism, is the electromagnetic power, , , They are the intermediate variables of the system matrix with 4 rows and 1 column, 4 rows and 2 columns, and 4 rows and 4 columns respectively.

[0023] 2. Modification of system state space equations

[0024] S2. Modify the system state space equation using the system state feedback matrix, and set the linear system corresponding to the modified system state space equation;

[0025] In step S2, the system state feedback matrix is ​​introduced to improve the overall transmission chain torque (the ), speed (in the system state space equation ) The damping ratio of the system state space equation of the variable is adjusted, taking into account the suppression of transmission chain torque and speed fluctuations, and modifying the system state space equation.

[0026] Preferably, step S2 includes: introducing a system state feedback matrix, making the control quantity in the system state space equation , and bring it into the system state space equation to modify the system state space equation. The modified system state space equation is:

[0027] ;

[0028] Among them, the top of the variable represents the differential of the dependent variable, is the system state feedback matrix, is the closed-loop system matrix, is the state variable, is the system matrix, is the control matrix.

[0029] In step S2, the system state feedback matrix is ​​introduced, and the control quantity in the system state space equation is , enhance the overall damping ratio of the system, and overall improve the damping ratio of the system state space equation containing the transmission chain torque and speed changes, while taking into account the suppression of transmission chain torque and speed fluctuations.

[0030] In the present invention, by introducing the system state feedback matrix, the system state equation can be reconstructed, and the characteristic value of the system state equation can be adjusted as desired, thereby improving the damping ratio and stability of the system.

[0031] 3. Establishment of characteristic root distribution map

[0032] S3. Set the system state feedback matrix to obtain the desired dynamic performance of the linear system, and establish the characteristic root distribution diagram under the desired dynamic performance of the linear system, and analyze the fluctuation of the state variables of the wind turbine after the integral link is locked and the system state feedback matrix is ​​introduced.

[0033] Preferably, step S3 comprises the following steps:

[0034] S31, for the linear system corresponding to the modified system state space equation, by setting the system state feedback matrix Parameters to configure the closed-loop system matrix The eigenvalues ​​of are used to obtain the desired dynamic performance of the linear system;

[0035] In the present invention, the above-mentioned linear system refers to a linearized wind turbine generator set, which can simultaneously satisfy superposition and uniformity, and its function is to describe the linear change of the rotation speed of the wind turbine generator set during the low-speed penetration process.

[0036] Preferably, S31 comprises the following steps:

[0037] S311, set system status feedback matrix The cost function of

[0038] Preferably, the cost function in step S311 is:

[0039] ;

[0040] in, is the cost function, is the state variable, is the control quantity, the superscript represents the transpose of a matrix, is the weight matrix of the state variables, is the comprehensive weight matrix of state variables and control quantities, is the weight matrix of the control quantity, , and Together they determine the system state variables and control volume The proportion between is the integration variable.

[0041] S312, transforming the cost function to obtain a standard quadratic cost function;

[0042] Preferably, the quadratic cost function in step S312 is:

[0043] ;

[0044] in, is a quadratic cost function, with the superscript Indicates the transpose of a matrix, the superscript represents the inverse of the matrix, is the intermediate variable, , is the state variable, To control the amount, is the weight matrix of the state variables, is the comprehensive weight matrix of state variables and control quantities, is the weight matrix of the control quantity, is the integration variable.

[0045] S313, set system status feedback matrix The calculation equation of minimizes the quadratic cost function.

[0046] In the present invention, the purpose of minimizing the quadratic cost function is to: , and Under this condition, the feedback matrix obtained by solving The parameters make the state variables of the system converge faster, the control cost is smaller, and the desired dynamic performance of the linear system is obtained.

[0047] Preferably, in step S313, the system state feedback matrix The calculation equation is:

[0048] ;

[0049] Among them, the superscript Indicates the transpose of a matrix, the superscript represents the inverse of the matrix, is the control matrix, is the comprehensive weight matrix of state variables and control quantities, is the weight matrix of the control quantity, is the intermediate matrix.

[0050] Preferably, in step S313, the intermediate matrix The calculation equation is:

[0051] ;

[0052] Among them, the superscript Indicates the transpose of a matrix, the superscript represents the inverse of the matrix, is the system matrix, is the control matrix, is the weight matrix of the state variables, is the comprehensive weight matrix of state variables and control quantities, is the weight matrix of the control quantity.

[0053] S32. Establish a characteristic root distribution diagram under the expected linear system dynamic performance, and use the characteristic root distribution diagram to analyze the fluctuation of the state variables of the wind turbine after the integral link is locked and the system state feedback matrix is ​​introduced.

[0054] Beneficial effects of the present invention:

[0055] The present invention starts from two aspects. One is to lock the integral link of the pitch angle control during a fault to eliminate the lag of the pitch angle control, and solve the problem of excessive speed drop caused by the continuous action of the pitch angle when the speed recovers to the rated value. The second is to introduce a system state feedback matrix during a fault to obtain the desired system response performance, improve the overall damping ratio of the system, and at the same time enhance the ability to suppress low-frequency and high-frequency fluctuations in the speed, thereby improving the speed response characteristics of the wind turbine. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 It is a flow chart of a safety risk suppression control method for equipment speed fluctuation during low voltage ride-through period of the present invention;

[0057] Figure 2 It is a characteristic root distribution diagram under the method proposed in the present invention;

[0058] Figure 3 For the present invention Figure 2 A magnified view of area A in FIG.

[0059] Figure 4 For the present invention Figure 2 Magnified view of area B in FIG. DETAILED DESCRIPTION

[0060] The concept, specific structure and technical effects of the present invention will be clearly and completely described below in conjunction with the embodiments and drawings to fully understand the purpose, characteristics and effects of the present invention.

[0061] Example 1

[0062] A safety risk suppression control method for equipment speed fluctuation during low voltage ride-through period, such as Figure 1 As shown, the following steps are included:

[0063] S1. Temporarily lock the integral link of the pitch angle control during the low voltage ride-through fault of the wind turbine, and after the integral link is locked, establish the system state space equation of the wind turbine rotor;

[0064] S2. Modify the system state space equation using the system state feedback matrix, and set the linear system corresponding to the modified system state space equation;

[0065] S3. Set the system state feedback matrix to obtain the desired dynamic performance of the linear system, and establish the characteristic root distribution diagram under the desired dynamic performance of the linear system, and analyze the fluctuation of the state variables of the wind turbine after the integral link is locked and the system state feedback matrix is ​​introduced.

[0066] Example 2

[0067] This embodiment further elaborates step S1 on the basis of embodiment 1. In step S1, the integral link is temporarily locked during the low voltage ride-through fault of the wind turbine generator set. After the integral link is locked, the system state space equation of the rotor is established:

[0068] ;

[0069] Among them, the top of the variable represents the differential of the dependent variable, is the state variable, is the system matrix, is the control matrix, is the control quantity, which can be expressed as:

[0070] ;

[0071] ;

[0072] ;

[0073] ;

[0074] ;

[0075] ;

[0076] in, Indicates the increment of the relevant variable, subscript represents the initial value of the relevant variable, Indicates the partial differential symbol, superscript represents the transpose of a matrix, and are the inertia constants of the wind wheel and the generator, is the generator speed, is the wind rotor rotation angular velocity, , are the torques of the wind wheel and the transmission chain respectively, is the equivalent damping constant of the transmission chain, is the equivalent stiffness of the transmission chain, is the gearbox transmission ratio, is the blade pitch angle, is the ratio of the pitch angle controller, is the time constant of the pitch mechanism, is the electromagnetic power, , , They are the intermediate variables of the system matrix with 4 rows and 1 column, 4 rows and 2 columns, and 4 rows and 4 columns respectively.

[0077] During low voltage ride-through, the goal of pitch angle control is to make mechanical power quickly track the change of electromagnetic power to alleviate the low-frequency fluctuation of speed, but due to the delay of the integral link, the tracking change of mechanical power has a large lag. In addition, during low voltage ride-through, since the time is short and the wind speed fluctuation is relatively small, the integral link can be temporarily locked during the fault period.

[0078] Example 3

[0079] This embodiment further explains step S2 based on embodiment 2. In step S2, the system state feedback matrix is ​​introduced to make the control quantity in the system state space equation , enhance the overall damping ratio of the system, improve the damping ratio of the system state space equation containing the transmission chain torque and speed variation, and take into account the suppression of transmission chain torque and speed fluctuations. The modified system state space equation is:

[0080] ;

[0081] Among them, the top of the variable represents the differential of the dependent variable, is the system state feedback matrix, is the closed-loop system matrix, is the state variable, is the system matrix, is the control matrix.

[0082] Example 4

[0083] This embodiment further describes step S3 based on embodiment 3. In step S3, the system state feedback matrix is ​​designed. , obtain the desired dynamic performance of the linear system, and establish the characteristic root distribution diagram under the desired system performance, and analyze the fluctuation of the state variables of the wind turbine after the integral link is locked and the system state feedback matrix is ​​introduced, which specifically includes the following steps:

[0084] S31, for the linear system corresponding to the modified system state space equation, by setting the system state feedback matrix Parameters to configure the closed-loop system matrix The eigenvalues ​​of are used to obtain the desired dynamic performance of the linear system;

[0085] S31 includes the following steps:

[0086] S311, set system status feedback matrix The cost function is:

[0087] ;

[0088] in, is the cost function, is the state variable, is the control quantity, the superscript represents the transpose of a matrix, is the weight matrix of the state variables, is the comprehensive weight matrix of state variables and control quantities, is the weight matrix of the control quantity, , and Together they determine the system state variables and control volume The proportion between is the integration variable.

[0089] S312, transform the cost function to obtain a standard quadratic cost function:

[0090] ;

[0091] in, is a quadratic cost function, with the superscript Indicates the transpose of a matrix, the superscript represents the inverse of the matrix, is the intermediate variable, , is the state variable, To control the amount, is the weight matrix of the state variables, is the comprehensive weight matrix of state variables and control quantities, is the weight matrix of the control quantity, is the integration variable.

[0092] S313, set system status feedback matrix The calculation equation of minimizes the quadratic cost function.

[0093] System state feedback matrix The calculation equation is:

[0094] ;

[0095] Among them, the superscript Indicates the transpose of a matrix, the superscript represents the inverse of the matrix, is the control matrix, is the comprehensive weight matrix of state variables and control quantities, is the weight matrix of the control quantity, is the intermediate matrix, and the calculation equation is:

[0096] ;

[0097] Among them, the superscript Indicates the transpose of a matrix, the superscript represents the inverse of the matrix, is the system matrix, is the control matrix, is the weight matrix of the state variables, is the comprehensive weight matrix of state variables and control quantities, is the weight matrix of the control quantity.

[0098] S32. Establish a characteristic root distribution diagram under the expected linear system dynamic performance, and use the characteristic root distribution diagram to analyze the fluctuation of the state variables of the wind turbine after the integral link is locked and the system state feedback matrix is ​​introduced.

[0099] like Figure 2 , Figure 3 and Figure 4 As shown, the characteristic root distribution diagram under the expected system performance of the present invention is analyzed. Figure 3 In the figure, the two Xs on the left are the proposed control (integral link + system state feedback matrix), the two Xs in the middle are integral locking, and the two Xs on the right are traditional control. Figure 4 In the figure, the X on the left is the proposed control (integral link + system state feedback matrix), the two Xs on the right are traditional control, and the X between the two Xs on the right is the integral lock.

[0100] from Figure 2 , Figure 3 and Figure 4 It can be found that when only the integral link is locked, the original 5 characteristic roots become 4, and the characteristic root λ 1. λ 2 moves away from the real axis and reaches -0.268±j2.666. Although the system damping ratio is increased, the oscillation frequency is enhanced, and the characteristic root λ 3. λ 4 changes from a pair of conjugate complex roots to a smaller real root of -0.937, which means that the low-frequency fluctuation of the speed decays faster, and because the imaginary part is 0, the oscillation form becomes monotonic decay, and the speed will not be excessively reduced, which improves the low-frequency fluctuation of state variables such as speed and transmission chain torque.

[0101] When the system state feedback matrix is ​​added, the characteristic root λ 1. λ 2 moves toward the real axis and reaches -0.611±j0.814, which greatly improves the system damping ratio and reduces the oscillation frequency. It can effectively improve the high-frequency fluctuations of state variables such as speed and transmission chain torque, and improve the suppression effect of speed fluctuations. The characteristic root λ 3. λ 4 Move away from the imaginary axis, the real root is smaller at -9.1, which is improved by nearly 10 times, which can greatly improve the low-frequency fluctuations.

[0102] The present invention starts from two aspects. One is to lock the integral link of the pitch angle control during a fault to eliminate the lag of the pitch angle control, and solve the problem of excessive speed drop caused by the continuous action of the pitch angle when the speed recovers to the rated value. The second is to introduce a system state feedback matrix during a fault to obtain the desired system response performance, improve the overall damping ratio of the system, and at the same time enhance the ability to suppress low-frequency and high-frequency fluctuations in the speed, thereby improving the speed response characteristics of the wind turbine.

[0103] The above is a specific description of the implementation mode of the present invention, but the present invention is not limited to the described embodiments. Those skilled in the art may make various equivalent modifications or substitutions without violating the spirit of the present invention, and these equivalents or substitutions are all included in the scope defined by the claims of the present invention.

Claims

1. A safety risk suppression control method for equipment speed fluctuation during low voltage ride-through period, characterized in that: The following steps are involved: S1. Temporarily lock the integral link of the pitch angle control during the low voltage ride-through fault of the wind turbine, and after the integral link is locked, establish the system state space equation of the wind turbine rotor; S2. Modify the system state space equation using the system state feedback matrix, and set the linear system corresponding to the modified system state space equation; S3. Setting the system state feedback matrix to obtain the desired dynamic performance of the linear system, and establishing the characteristic root distribution diagram under the desired dynamic performance of the linear system, and analyzing the fluctuation of the state variables of the wind turbine after the integral link is locked and the system state feedback matrix is ​​introduced; The system state space equation in step S1 is: ； Among them, the top of the variable represents the differential of the dependent variable, is the state variable, is the system matrix, is the control matrix, To control the amount; State variables in the state space equations of the S1 step system , system matrix , control matrix It is expressed as: ； ； ； ； ； ； in, Indicates the increment of the relevant variable, subscript represents the initial value of the relevant variable, Indicates the partial differential symbol, superscript represents the transpose of a matrix, and are the inertia constants of the wind wheel and the generator, is the generator speed, is the wind rotor rotation angular velocity, , are the torques of the wind wheel and the transmission chain respectively, is the equivalent damping constant of the transmission chain, is the equivalent stiffness of the transmission chain, is the gearbox transmission ratio, is the blade pitch angle, is the ratio of the pitch angle controller, is the time constant of the pitch mechanism, is the electromagnetic power, , , They are the intermediate variables of the system matrix with 4 rows and 1 column, 4 rows and 2 columns, and 4 rows and 4 columns respectively; Step S2 includes: introducing the system state feedback matrix, making the control quantity in the system state space equation , and bring it into the system state space equation to modify the system state space equation. The modified system state space equation is: ； Among them, the top of the variable represents the differential of the dependent variable, is the system state feedback matrix, is the closed-loop system matrix, is the state variable, is the system matrix, is the control matrix.

2. A method for controlling the safety risk of equipment speed fluctuation during low voltage ride-through period as claimed in claim 1, characterized in that: The S3 step includes the following steps: S31, for the linear system corresponding to the modified system state space equation, by setting the system state feedback matrix Parameters to configure the closed-loop system matrix The eigenvalues ​​of are used to obtain the desired dynamic performance of the linear system; S32. Establish a characteristic root distribution diagram under the expected linear system dynamic performance, and use the characteristic root distribution diagram to analyze the fluctuation of the state variables of the wind turbine after the integral link is locked and the system state feedback matrix is ​​introduced.

3. A method for controlling the safety risk of equipment speed fluctuation during low voltage ride-through period as claimed in claim 2, characterized in that: S31 includes the following steps: S311, set system status feedback matrix The cost function of S312, transforming the cost function to obtain a standard quadratic cost function; S313, set system status feedback matrix The calculation equation of minimizes the quadratic cost function.

4. A method for controlling the safety risk of equipment speed fluctuation during low voltage ride-through period as claimed in claim 3, characterized in that: The cost function in step S311 is: ； in, is the cost function, is the state variable, is the control quantity, the superscript represents the transpose of a matrix, is the weight matrix of the state variables, is the comprehensive weight matrix of state variables and control quantities, is the weight matrix of the control quantity, , and Together they determine the system state variables and control volume The proportion between is the integration variable.

5. A method for controlling the safety risk of equipment speed fluctuation during low voltage ride-through period as claimed in claim 3, characterized in that: The quadratic cost function in step S312 is: ； in, is a quadratic cost function, with the superscript Indicates the transpose of a matrix, the superscript represents the inverse of the matrix, is the intermediate variable, , is the state variable, To control the amount, is the weight matrix of the state variables, is the comprehensive weight matrix of state variables and control quantities, is the weight matrix of the control quantity, is the integration variable.

6. A method for controlling safety risks of equipment speed fluctuation during low voltage ride-through period as claimed in claim 3, characterized in that: In step S313, the system state feedback matrix The calculation equation is: ； Among them, the superscript Indicates the transpose of a matrix, the superscript represents the inverse of the matrix, is the control matrix, is the comprehensive weight matrix of state variables and control quantities, is the weight matrix of the control quantity, is the intermediate matrix.

7. A method for controlling the safety risk of equipment speed fluctuation during low voltage ride-through period as claimed in claim 6, characterized in that: In step S313, the intermediate matrix The calculation equation is: ； Among them, the superscript Indicates the transpose of a matrix, the superscript represents the inverse of the matrix, is the system matrix, is the control matrix, is the weight matrix of the state variables, is the comprehensive weight matrix of state variables and control quantities, is the weight matrix of the control quantity.

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