Method and system for selecting input signals of damping controller of synchronous phase modifier

Abstract

The invention provides a method and a system for selecting an input signal of a damping controller of a synchronous phase modifier. The method comprises the following steps: establishing a differential equation and an algebraic equation of the whole system based on a dynamic model of a grid-connected system; linearizing a differential equation and an algebraic square of the whole system at a stable operation point, and establishing a small-signal linearization model of the whole system; solving a system state matrix based on the small signal linearization model, calculating a characteristic value, a left characteristic vector and a right characteristic vector of the system state matrix, and determining different oscillation modes of the system according to a characteristic value calculation result of the system state matrix; calculating participation factors in different oscillation modes by combining the left feature vector and the right feature vector of the system, and constructing a participation factor matrix; and in combination with the participation factor matrix, aiming at a certain oscillation mode of the system, the size of the participation factors between the oscillation mode and different state variables is compared and analyzed, and the state variable with the maximum participation factor is used as an input signal of the damping controller of the synchronous phase modifier.

Description

Technical Field

[0001] The present invention belongs to the technical field of synchronous phase condenser damping controller input signal selection, and in particular, relates to a synchronous phase condenser damping controller input signal selection method and system. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] With the expansion of energy demand and the increasing requirements for environmental protection, new energy systems based on wind power generation are developing rapidly, and wind power accounts for an increasing proportion of the power generation system. Due to the "reverse distribution" characteristics of wind energy-rich areas and load centers in my country, the technology of series compensation capacitors is usually used in actual projects for large-scale wind power transmission. While this technology improves the wind power transmission capacity, it also brings the risk of subsynchronous oscillation to the system.

[0004] Due to the different grid connection methods between wind turbines and traditional thermal power units, as well as the structural characteristics of the "back-to-back" converter, the subsynchronous oscillation of wind turbines has its own particularity, which is much more complicated than that of traditional thermal power units, and seriously threatens the safe and stable operation of the system. For example, in 2015, a subsynchronous oscillation accident occurred in a certain region of renewable energy power generation. The oscillation power spanned multiple voltage levels, causing severe torsional vibration of the shaft systems of multiple thermal power generators 300 kilometers away, and then the protection action was cut off, which further caused a system-level accident with a large power shortage and a sudden drop in frequency. Reducing the impact of subsynchronous oscillation on the system and selecting appropriate methods to propose effective oscillation suppression strategies are of great practical significance for expanding the safe operation range of wind power transmission systems and realizing large-scale development and utilization of wind power.

[0005] At present, there are several ways to suppress subsynchronous oscillation of wind turbines, such as optimizing control parameters, adding additional damping controllers, and adding flexible AC transmission system equipment. Among them, the additional damping controller selects the feedback signal containing oscillation information in the unit control loop, adjusts the converter control signal through the additional damping controller, and comprehensively utilizes the controllability and observability of the feedback signal to improve the damping capacity of the system, so as to suppress the subsynchronous oscillation of the system economically and effectively.

[0006] Therefore, by analyzing the information of different oscillation modes contained in the feedback signal, an additional damping controller can be added to the control loop of the synchronous condenser to enhance its damping capacity, thereby suppressing the subsynchronous oscillation of the system. However, the different selection of input signals for the damping controller of the synchronous condenser will have a great impact on the damping improvement effect. At present, most studies mainly select signals based on experience. Different power systems have different characteristics and parameters. Experience alone may not accurately match the most suitable input signal, and failure to select the best input signal may greatly reduce the effect of the additional damping controller and fail to achieve the expected control effect. To address this problem, there is an urgent need for a method to determine the input signal of the damping controller of the synchronous condenser through quantitative calculation. Summary of the invention

[0007] In order to overcome the deficiencies of the above-mentioned prior art, the present invention provides a method for selecting the input signal of the damping controller of a synchronous phase condenser, which can select the input signal with the strongest correlation based on quantitative calculation indicators, demonstrating the accuracy and scientificity of signal selection.

[0008] To achieve the above objectives, one or more embodiments of the present invention provide the following technical solutions:

[0009] In a first aspect, a method for selecting an input signal of a synchronous condenser damping controller is disclosed, comprising:

[0010] Construct a dynamic model of the grid-connected system of a new energy station containing a synchronous condenser, and establish differential equations and algebraic equations of the entire system based on the dynamic model of the grid-connected system;

[0011] Linearize the differential equations and algebraic squares of the entire system at the stable operating point and establish a small signal linearization model of the entire system;

[0012] Obtain the system state matrix based on the small signal linearization model, calculate the eigenvalues ​​and left eigenvectors and right eigenvectors of the system state matrix, and determine different oscillation modes of the system according to the eigenvalue calculation results of the system state matrix;

[0013] Combine the left eigenvector and the right eigenvector of the system to calculate the participation factors under different oscillation modes and construct the participation factor matrix;

[0014] Combined with the participation factor matrix, for a certain oscillation mode of the system, the participation factor between it and different state variables is compared and analyzed, and the state variable with the largest participation factor is used as the input signal of the synchronous condenser damping controller.

[0015] As a further technical solution, the dynamic model of the grid-connected system of the new energy station containing the synchronous condenser includes a dynamic model of the synchronous condenser and a dynamic model of the new energy station;

[0016] Based on the dynamic model of the synchronous condenser, the differential equation and algebraic equation of the synchronous condenser are established, which are set as the first equation group; based on the dynamic model of the new energy station, the differential equation and algebraic equation of the new energy station are established, which are set as the second equation group;

[0017] Based on the first set of equations and the second set of equations, the differential equations and algebraic equations of the entire system are obtained.

[0018] As a further technical solution, when establishing the differential equation and algebraic equation of the synchronous condenser, the state variables and input variables of the synchronous condenser are selected to establish the differential equation and algebraic equation of the synchronous condenser.

[0019] As a further technical solution, when formulating the differential equation and algebraic equation of the new energy station, the state variables and input variables of the new energy station are selected to establish the differential equation and algebraic equation of the new energy station.

[0020] As a further technical solution, when linearizing the differential equations and algebraic equations of the whole system, the differential equations and algebraic equations of the whole system are linearized at a stable operating point in combination with the Lyapunov linearization principle.

[0021] As a further technical solution, a small signal linearization model of the whole system is established, specifically:

[0022]

[0023] Where Δx is the small signal form of the state variable of the entire system; Δu is the small signal form of the input variable of the entire system; is the system matrix; is the input matrix; is the control matrix;

[0024] is a direct transfer matrix.

[0025] As a further technical solution, when obtaining the system state matrix, the system state matrix A of the system is calculated based on the small signal linearization model of the whole system:

[0026]

[0027] In the formula, is the state matrix of the whole system.

[0028] As a further technical solution, the process of calculating the eigenvalues ​​and left eigenvectors and right eigenvectors of the system state matrix is:

[0029] Based on the system state matrix, the characteristic equation about the right eigenvector of the system state matrix is ​​established:

[0030] Axri =λ i x ri

[0031] In the formula, is the right eigenvector of the system state matrix A, is the matrix composed of right eigenvectors; i is the right eigenvector x corresponding to the system state matrix A ri The subscript “i” indicates the arrangement of the system’s eigenvalues; the subscript “n” indicates the total number of state variables;

[0032] Based on the system state matrix, the characteristic equation about the left eigenvector of the system state matrix is ​​established:

[0033] x li A=λ i x li

[0034] In the formula, is the left eigenvector of the system state matrix A, is a matrix composed of left eigenvectors; i is the left eigenvector x corresponding to the system state matrix A li The characteristic value of

[0035] By solving the above characteristic equation, we can obtain the eigenvalue and left and right eigenvectors of the system.

[0036] As a further technical solution, different oscillation modes of the system are determined according to the eigenvalue calculation results of the system state matrix, specifically including:

[0037] If the system eigenvalue calculation result has a pair of conjugate complex numbers, then this pair of eigenvalues ​​corresponds to an oscillation mode of the system, that is:

[0038] λ i,i+1 =a±jb

[0039] In the formula, λ i,i+1 is a pair of conjugate eigenvalues ​​of the system, a is the real part of the conjugate eigenvalue of the system, and b is the imaginary part of the eigenvalue of the system;

[0040] If a<0, then λ i,i+1 Corresponding to a stable oscillation mode of the system, the damping is positive;

[0041] If a>0, then λ i,i+1 Corresponding to an unstable oscillation mode of the system, the damping is negative and the oscillation frequency is f = |b| / (2π).

[0042] As a further technical solution, the participation factors under different oscillation modes are calculated by combining the left eigenvector and the right eigenvector of the system, specifically:

[0043] The left eigenvector x of the system li =[u 1i …u ji …u ni ] and the right eigenvector x ri =[v 1i …v ji …v ni ] T The corresponding elements are multiplied internally to form a participation factor vector:

[0044] P i =[u 1i v 1i u 2i v 2i …u ji v ji ] T

[0045] In the formula, u represents the element in the left eigenvector; v represents the element in the right eigenvector; represents the participation factor vector corresponding to the i-th eigenvalue; the subscript “j” represents the permutation of the state variables;

[0046] The participation factor vectors of each eigenvalue are then combined to form the participation matrix P:

[0047]

[0048] In the formula, is the system participation matrix, and the element p of the participation matrix P is called ji =u ji v ji is the participation factor, which measures the i-th mode λ i and the jth state variable Δx j The degree of mutual correlation between them.

[0049] As a further technical solution, the process of selecting the input signal of the damping controller includes: according to the determined system oscillation mode λ i,i+1 , select the corresponding participation factor vector P i By comparing and analyzing the size of each element in the participation factor vector, the participation factor p with the largest modulus value in this oscillation mode is obtained. ji , that is, max{|p ji |}, the jth state variable can be located accordingly and selected as the input signal of the synchronous condenser damping controller.

[0050] As a further technical solution, if the participation factors with the largest modulus values ​​in different oscillation modes correspond to different state variables, the respective input signals can be determined according to their respective corresponding relationships;

[0051] If the participation factor with the largest modulus value in different oscillation modes corresponds to the same state variable, the oscillation mode can be divided into frequency bands according to the oscillation frequency. If the oscillation modes with the same corresponding state variables are in the same frequency band, the same state variable can be selected as the input signal of the damping controller. If the oscillation modes with the same corresponding state variables are in different frequency bands, it is necessary to avoid selecting the same state variable. For this purpose, it is necessary to arrange the state variables in descending order according to the principle of decreasing modulus value for the participation factors of different oscillation modes, and select different state variables in descending order as the input signal of the damping controller.

[0052] In a second aspect, a system for selecting an input signal of a synchronous condenser damping controller is disclosed, comprising:

[0053] The differential equation and algebraic equation building module of the system is configured to: build a dynamic model of the grid-connected system of the new energy station including the synchronous condenser, and establish the differential equation and algebraic equation of the whole system based on the dynamic model of the grid-connected system;

[0054] The small signal linearization model building module of the whole system is configured to: linearize the differential equations and algebraic squares of the whole system at the stable operation point to establish the small signal linearization model of the whole system;

[0055] The oscillation mode determination module is configured to: obtain a system state matrix based on a small signal linearization model, calculate the eigenvalues ​​and left eigenvectors and right eigenvectors of the system state matrix, and determine different oscillation modes of the system according to the eigenvalue calculation results of the system state matrix;

[0056] The participation factor matrix construction module is configured to: combine the left eigenvector and the right eigenvector of the system, calculate the participation factors under different oscillation modes, and construct the participation factor matrix;

[0057] The input signal determination module is configured as follows: combining the participation factor matrix, for a certain oscillation mode of the system, by comparing and analyzing the size of the participation factor between it and different state variables, the state variable with the largest participation factor is used as the input signal of the synchronous condenser damping controller.

[0058] One or more of the above technical solutions have the following beneficial effects:

[0059] The technical solution of the present invention is based on the method for selecting the input signal of the synchronous phase condenser damping controller, establishes a small signal linearization model of the grid-connected system of the new energy station containing the synchronous phase condenser, and analyzes the oscillation mode of the new energy station by calculating the system eigenvalues. The design of the additional damping controller mainly includes three parts: input signal selection, control structure design and parameter optimization, and controller placement selection. The selection of the input signal is the beginning of the entire design process, and the subsequent control structure design and parameter optimization depend on the selection of the input signal. The technical solution of the present invention selects the input signal with the greatest correlation with the oscillation mode through this method, laying the foundation for the subsequent design of a damping controller with better performance.

[0060] The technical solution of the present invention is based on a method for selecting input signals of a damping controller of a synchronous phase condenser. It quantitatively calculates indicators such as controllability and observability of different signals according to participation factors, and can sort the correlations of different signals to the same oscillation mode, thereby evaluating the effectiveness of the selection of damping controller signals.

[0061] The technical solution of the present invention is based on a signal selection method for a damping controller of a synchronous phase regulator. For oscillations caused by different structural parameters, the input signal with the strongest correlation can be selected based on quantitative calculation indicators, demonstrating the accuracy and scientificity of signal selection.

[0062] Advantages of additional aspects of the present invention will be given in part in the following description, and in part will become obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0064] Figure 1 A flow chart of a method for selecting an input signal of a synchronous condenser damping controller;

[0065] Figure 2 This is the topology diagram of the grid-connected system of the new energy station including synchronous condenser;

[0066] Figure 3 is the modal diagram of participation factor of oscillation mode 1;

[0067] Figure 4 is the modal diagram of participation factor of oscillation mode 2;

[0068] Figure 5 Modal diagram of participation factor for oscillation mode 3. DETAILED DESCRIPTION

[0069] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0070] It should be noted that the terms used herein are for describing specific embodiments only and are not intended to be limiting of exemplary embodiments according to the present invention.

[0071] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0072] Embodiment 1

[0073] like Figure 1 As shown, this embodiment discloses a method for selecting an input signal of a synchronous condenser damping controller, comprising:

[0074] S1: Construct a dynamic model of the grid-connected system of a new energy station with a synchronous condenser in the DQ rotating coordinate system, and establish differential equations and algebraic equations of the whole system;

[0075] S2: Combined with Lyapunov linearization principle, the differential equations and algebraic equations of the whole system are linearized at the stable operation point, and a small signal linearization model of the whole system is established;

[0076] S3: Based on the small signal linearization model, the system state matrix A is obtained. The eigenvalue and left and right eigenvectors of the system state matrix are calculated by combining the eigenvalue analysis method. Different oscillation modes of the system are determined according to the calculation results of the system eigenvalue.

[0077] S4: Combine the left eigenvector and the right eigenvector of the system to calculate the participation factors of the system under different oscillation modes and construct the participation factor matrix;

[0078] S5: Combined with the participation factor matrix, for a certain oscillation mode of the system, by comparing and analyzing the size of the participation factor between it and different state variables, the input signal of the synchronous condenser damping controller is optimized.

[0079] So far, the input signal of the synchronous condenser damping controller has been successfully selected based on the stability analysis of the new energy station grid-connected system containing synchronous condensers.

[0080] The sub-technical scheme of this embodiment determines the different oscillation modes of the system by calculating the system eigenvalues, obtains the participation factor that measures the degree of correlation between different modes and state variables of the system based on the left and right eigenvectors of the system, and optimizes the input signal of the synchronous phase regulator damping controller by comparing and analyzing the system participation factors, which facilitates the design of the damping controller.

[0081] In step S1 of the sub-technical solution of this embodiment, when constructing the dynamic model of the grid-connected system of the new energy station containing the synchronous phase condenser in the DQ rotating coordinate system, the dynamic model of the synchronous phase condenser includes the asynchronous motor, the machine-side converter and its control structure, the DC link, the grid-side converter and its control structure, the filtering link, the transmission line and the phase-locked loop and other parts; the equivalent direct-drive wind turbine system is used to replace the new energy station for analysis, and the dynamic model of the new energy station includes the converter and its control structure, the filtering link and the transmission line and other parts. For the specific structure, see the attached Figure 2 The topology diagram of the grid-connected system of a new energy station including a synchronous phase regulator is shown.

[0082] In step S1 of the sub-technical solution of this embodiment, the dynamic model is established in the DQ rotating coordinate system. This is because the control structure of the converter is established in the DQ rotating coordinate system, and the control accuracy of the control structure in this coordinate system is more accurate than that in the three-phase static abc coordinate system; secondly, the Lyapunov linearization principle is also carried out based on this coordinate system.

[0083] In step S1 of the sub-technical solution of this embodiment, the process of establishing differential equations and algebraic equations for the entire system includes: after constructing the dynamic models of the synchronous phase regulator and the new energy station respectively, selecting their respective state variables and input variables, establishing their respective differential equations and algebraic equations, and then integrating the models of the synchronous phase regulator and the new energy station, and establishing their differential equations and algebraic equations based on determining the state variables and input variables of the entire system.

[0084] The dynamic models of each module of the synchronous condenser are as follows:

[0085] The stator voltage and rotor voltage equations of the asynchronous motor satisfy:

[0086]

[0087] In the formula, the variable subscript "pu" indicates the per-unit value form of the variable; sd,pu 、u sq,pu are the d-axis and q-axis components of the stator voltage respectively; u rd,pu 、u rq,pu are the d-axis and q-axis components of the rotor voltage respectively; i sd,pu 、i sq,pu are the d-axis and q-axis components of the stator current respectively; i rd,pu 、i rq,pu are the d-axis and q-axis components of the rotor current respectively; R s,pu is the stator winding resistance in the dq coordinate system; R r,pu is the rotor winding resistance in the dq coordinate system; L s,pu is the stator equivalent two-phase winding self-inductance in the dq coordinate system; L r,pu is the equivalent two-phase winding self-inductance of the rotor in the dq coordinate system; Lm,pu is the mutual inductance between the stator and rotor coaxial equivalent windings in the dq coordinate system; ω sc The angular velocity is obtained by the phase-locked loop tracking the synchronous angular velocity of the power grid; ω r,pu is the rotor angular velocity; ω b is the angular velocity reference value.

[0088] The rotor motion equation of the asynchronous motor satisfies:

[0089]

[0090] Where, H is the moment of inertia of the asynchronous motor; F is the friction coefficient of the asynchronous motor; T m,pu is the driving torque, which is a constant; θ r,pu is the rotor angle.

[0091] The dynamic model of the machine-side converter control structure satisfies:

[0092] Slip link control equation:

[0093]

[0094] In the formula, K wr,p , K wr,i is the proportional coefficient and integral coefficient of the PI controller in the slip control link; ω r,ref,pu is the rotor angular velocity reference value; P s,ref,pu , Q s,ref,pu The reference value of active power and reactive power output on the stator side; x rw,d Defined as the variable at the exit of the slip integral link.

[0095] Power outer loop control equation:

[0096]

[0097] In the formula, K rp,p , K rp,i is the proportional coefficient and integral coefficient of the power outer loop PI controller; P s,pu , Q s,pu Output active power and reactive power for the stator side; i rd,ref,pu 、i rq,ref,pu are the reference values ​​of rotor d and q axis currents respectively; rp,d 、x rp,q They are defined as the variables at the exit of active power and reactive power integration links respectively.

[0098] Current inner loop control equation:

[0099]

[0100] In the formula, K ri,p , Kri,i is the proportional coefficient and integral coefficient of the current inner loop PI controller; x rp,d 、x rp,q They are defined as the variables at the exit of the rotor d and q axis current integration links respectively.

[0101] The dynamic model of the DC link satisfies:

[0102]

[0103] In the formula, C sc,pu is the DC link capacitance value; u dc,pu is the voltage across the capacitor; u fd,pu 、u fq,pu are the d-axis and q-axis components of the voltage at the grid-side converter outlet; i fd,pu 、i fq,pu are the d-axis and q-axis components of the current at the grid-side converter outlet.

[0104] The dynamic model of the grid-side converter control structure satisfies:

[0105] The control equation of the voltage outer loop is:

[0106]

[0107] In the formula, K gu,p , K gu,i is the proportional coefficient and integral coefficient of the power outer loop PI controller; u dc,ref,pu is the voltage reference value across the capacitor; i fd,ref,pu 、i fq,ref,pu is the reference value of the d-axis and q-axis components of the current at the grid-side converter outlet; gu,d Defined as the variable at the exit of the voltage outer loop integration link.

[0108]

[0109] In the formula, K gi,p , K gi,i is the proportional coefficient and integral coefficient of the current inner loop PI controller; u dc,ref,pu is the voltage reference value across the capacitor; u odsc,pu 、u oqsc,pu is the d-axis and q-axis components of the voltage across the transmission line capacitor; gi,d 、x gi,q are defined as the exit variables of the d-axis and q-axis current integration links at the exit of the grid-side converter respectively; L f,pu , R f,pu They are the inductance and resistance of the filtering link respectively.

[0110] The dynamic model of the filtering link is:

[0111]

[0112] The dynamic model of the transmission line is:

[0113]

[0114] In the formula, C esc,pu , L esc,pu , R esc,pu are the capacitance, inductance and resistance on the transmission line respectively; i odsc,pu 、i oqsc,pu are the d-axis and q-axis components of the current flowing through the inductance of the transmission line; u bdsc,pu 、u bqsc,pu are the d-axis and q-axis components of the voltage at the grid-connected point of the synchronous condenser.

[0115] Dynamic model of phase-locked loop:

[0116]

[0117] In the formula, K P,PLL , K I,PLL is the proportional coefficient and integral coefficient of the phase-locked loop PI controller; δ sc The angle obtained by the phase-locked loop tracking the power grid.

[0118] The construction method of the dynamic model of the new energy station can refer to the construction method of the grid-side converter of the synchronous condenser, so it will not be repeated here. So far, the dynamic models of the synchronous condenser and the new energy station in the DQ rotating coordinate system have been obtained respectively.

[0119] The dynamic models of synchronous condensers and new energy stations are rearranged and transformed to obtain their respective differential equations and algebraic equations. The differential equations and algebraic equations of synchronous condensers are:

[0120]

[0121] In the formula, is the state variable of the synchronous condenser; is the input variable of the synchronous condenser; f SC and g SC They represent the nonlinear functions of the differential equation and algebraic equation of the synchronous condenser, respectively. The state variable intrinsic elements refer to the differential terms in the differential equation, while the input variables refer to the variables such as power, torque and node voltage that have explicit or implicit relationships with the state variables.

[0122] The differential equations and algebraic equations of the new energy station are:

[0123]

[0124] In the formula, is the state variable of the new energy station; is the input variable of the new energy station; f RES and g RES They represent the nonlinear functions of differential equations and algebraic equations of new energy stations respectively.

[0125] Combining the differential and algebraic equations of synchronous condensers and renewable energy stations, the differential and algebraic equations of the entire system can be obtained:

[0126]

[0127] In the formula, is the state variable of the whole system; is the input variable of the whole system; f and g represent the nonlinear functions of the differential equation and algebraic equation of the whole system respectively.

[0128] In step S2 of the sub-technical solution of this embodiment, when linearizing the differential equations and algebraic equations of the whole system, the differential equations and algebraic equations of the whole system are linearized at the stable operating point in combination with the Lyapunov linearization principle, and a small signal linearization model of the whole system is established.

[0129] To illustrate the basic principle of Lyapunov linearization, consider the nonlinear system described by the following differential equation:

[0130]

[0131] In the formula, x n is the state variable of the example nonlinear system; f n Nonlinear function representing the example nonlinear system.

[0132] Taylor expansion of the above equation at the origin:

[0133]

[0134] In the formula, Δx n is the small signal form of the state scalar of the example nonlinear system, The values ​​of the state variables of the nonlinear system when it is running stably are shown in h(Δx n ) represents Δx n Expressions of second order and above. If h(Δx n ) in Δx n =0 is Δx n The linear system described by the following formula can often be used to analyze the nonlinear system at the system equilibrium point. Stability:

[0135]

[0136] Combined with Lyapunov linearization theory, the differential equations and algebraic equations of the grid-connected system of the renewable energy station containing synchronous condenser are solved at the stable operation point. Linearize at the point to obtain the small signal linear model of the entire system:

[0137]

[0138] Where Δx is the small signal form of the state variable of the entire system; Δu is the small signal form of the input variable of the entire system; is the system matrix; is the input matrix; is the control matrix;

[0139] is a direct transfer matrix.

[0140] The selection of state variables is related to the nonlinear elements of the system. Each nonlinear element corresponds to a state variable, for example, the inductor L corresponds to the current flowing through the inductor, and the capacitor corresponds to the voltage across the capacitor. The selection of input variables depends on the number of algebraic equations, that is, the number of variables that need to be represented by state variables. For example, the calculation of power requires voltage and current. Voltage and current are state variables, while power is an input variable.

[0141] Using the above Lyapunov linearization principle, we can get Four matrices, that is, using differential equations and algebraic equations to find partial derivatives of state variables and input variables respectively, and constructing four matrices with corresponding coefficients. Thus, a small signal linearization model of the entire system can be established.

[0142] In step S3 of the sub-technical solution of this embodiment, when obtaining the system state matrix, based on the small signal linearization model of the whole system, the system state matrix A of the system is calculated by the following formula:

[0143]

[0144] In the formula, is the state matrix of the whole system.

[0145] In step S3 of the sub-technical solution of this embodiment, the process of calculating the eigenvalues ​​and left and right eigenvectors of the system state matrix includes: establishing characteristic equations about the left eigenvector and right eigenvector of the system state matrix respectively, and obtaining the eigenvalues ​​and left and right eigenvectors of the system by solving the characteristic equations.

[0146] Based on the system state matrix, the characteristic equation about the right eigenvector of the system state matrix is ​​established:

[0147] Ax ri =λ i xri

[0148] In the formula, is the right eigenvector of the system state matrix A, is the matrix composed of right eigenvectors; i is the right eigenvector x corresponding to the system state matrix A ri The subscript “i” represents the arrangement of the system eigenvalues; the subscript “n” represents the total number of state variables, n=38.

[0149] Similarly, based on the system state matrix, the characteristic equation about the left eigenvector of the system state matrix is ​​established:

[0150] x li A=λ i x li

[0151] In the formula, is the left eigenvector of the system state matrix A, is a matrix composed of left eigenvectors; i is the left eigenvector x corresponding to the system state matrix A li The characteristic value of .

[0152] In step S3 of the sub-technical solution of this embodiment, the process of using the eigenvalue analysis method to determine the different oscillation modes of the system includes: combining the eigenvalue analysis method, that is: if all the eigenvalues ​​are located in the left half of the complex plane (that is, the real part is less than zero), then the system is stable; if there are any one or more eigenvalues ​​located in the right half of the complex plane or on the imaginary axis, then the system is unstable.

[0153] If the result of calculating the eigenvalue of the system contains a pair of conjugate complex numbers, then this pair of eigenvalues ​​corresponds to an oscillation mode of the system. That is:

[0154] λ i,i+1 =a±jb

[0155] In the formula, λ i,i+1 is a pair of conjugate eigenvalues ​​of the system, a is the real part of the conjugate eigenvalue of the system, and b is the imaginary part of the conjugate eigenvalue of the system.

[0156] If a<0, then λ i,i+1 Corresponding to a stable oscillation mode of the system, the damping is positive; if a>0, then λ i,i+1 Corresponding to an unstable oscillation mode of the system, the damping is negative and the oscillation frequency is f = |b| / (2π).

[0157] In step S4 of the sub-technical solution of this embodiment, the process of calculating the system participation factor by combining the left and right eigenvectors of the system includes: li =[u1i …u ji …u ni ] and the right eigenvector x ri =[v 1i …v ji …v ni ] T The corresponding elements are multiplied internally to form a participation factor vector:

[0158] P i =[u 1i v 1i u 2i v 2i … u ji v ji ] T

[0159] Where u represents the element in the left eigenvector; v represents the element in the right eigenvector; P i 38×1 denotes the participation factor vector corresponding to the i-th eigenvalue; the subscript “j” denotes the permutation of the state variables.

[0160] The participation factor vectors of each eigenvalue are then combined to form the participation matrix P:

[0161]

[0162] In the formula, is the system participation matrix. The element p of the participation matrix P is called ji =u ji v ji is the participation factor, which measures the i-th mode λ i and the jth state variable Δx j The degree of mutual correlation between them.

[0163] In step S5 of the sub-technical solution of this embodiment, the process of selecting the input signal of the damping controller includes: according to the system oscillation mode λ determined in step S4, i,i+1 , select the corresponding participation factor vector P i By comparing and analyzing the size of each element in the participation factor vector, the participation factor p with the largest modulus value in this oscillation mode is obtained. ji , that is, max{|p ji |}, the jth state variable can be located accordingly and selected as the input signal of the synchronous condenser damping controller.

[0164] In step S5 of the sub-technical solution of this embodiment, if the participation factor with the largest modulus value in different oscillation modes corresponds to different state variables, the respective input signals can be determined according to their respective corresponding relationships; if the participation factor with the largest modulus value in different oscillation modes corresponds to the same state variable, the oscillation mode can be divided into frequency bands according to the oscillation frequency, and if the oscillation modes with the same corresponding state variables are in the same frequency band, the same state variable can be selected as the input signal of the damping controller; if the oscillation modes with the same corresponding state variables are in different frequency bands, it is necessary to avoid selecting the same state variable, and for this purpose, it is necessary to arrange the order of the state variables according to the principle of descending modulus value for the participation factors of different oscillation modes, and select different state variables in descending order as the input signals of the damping controller.

[0165] The state variables are arranged in descending order according to the principle of modulus value, and different state variables are selected as the input signals of the damping controller because:

[0166] First, if the same input signal is used to control the oscillations of all frequency bands, it may not be possible to accurately adjust according to the characteristics of each frequency band, resulting in limited control effect; second, using the same input signal may produce poor control effects on certain frequency bands and may even stimulate new oscillation modes, further reducing the stability of the system.

[0167] The effectiveness of the synchronous condenser damping controller input signal selection method proposed in the present invention is verified by using a new energy station grid-connected system containing synchronous condensers. All analyses are performed in Matlab and on an Intel 1.60GHz 16GB laptop.

[0168] New energy station grid-connected system including synchronous condenser Figure 2 The grid-connected system of the new energy station with synchronous condenser includes two parts: synchronous condenser and new energy station grid-connected system. The synchronous condenser is a double-fed structure, including asynchronous motor, machine-side converter and its control structure, DC link, grid-side converter and its control structure, filtering link, transmission line and phase-locked loop; the grid-connected new energy station is analyzed by replacing the new energy station with an equivalent direct-drive wind turbine, including converter and its control structure, filtering link, transmission line, AC line and infinite power grid.

[0169] The sub-technical solution of this embodiment constructs a dynamic model of the grid-connected system of a new energy station containing a synchronous condenser, linearizes it at the stable operation point, establishes a state space model of the system, calculates the system eigenvalues ​​and left and right eigenvectors based on the system state space model, and determines different oscillation modes of the system in combination with the eigenvalue calculation results. The partial oscillation modes of the system are shown in Table 1.

[0170] Table 1 Oscillation modes of the grid-connected system of the new energy station with synchronous condenser

[0171]

[0172] Combined with the left and right eigenvectors of the system, the participation factors of the three oscillation modes of the system are calculated, and the calculation results are plotted into participation factor modal diagrams, as shown in Figure 3 , Figure 4 and Figure 5 shown.

[0173] Selection of the damping controller input signal for oscillation mode 1, combined with the participation factor modal Figure 3 It can be found that the state variable most associated with this oscillation mode is the power angle δ of the direct-drive fan. m1 , so we can choose δ m1 As the input signal of the synchronous condenser damping controller; for the selection of the damping controller input signal of oscillation mode 2, combined with the participation factor mode Figure 4 It can be found that the state variable most associated with this oscillation mode is the power angle δ of the direct-drive fan. m1 , so we can choose δ m1 As the input signal of the synchronous condenser damping controller; for the selection of the damping controller input signal of oscillation mode 3, combined with the participation factor mode Figure 5 It can be found that the state variable most associated with this oscillation mode is the D-axis component i of the synchronous condenser rotor current. rd,pu , so we can choose i rd,pu As the input signal of the synchronous condenser damping controller.

[0174] From the above signal selection results, it can be found that the input signals finally selected by the first two oscillation modes are the same. This is because the oscillation frequencies of the two oscillation modes are similar and can be divided into the same frequency band. For oscillations in the same frequency band, the input signal of the damping controller can select the same state variable; the oscillation frequency of the third oscillation mode is quite different from that of the first two oscillation modes, so the third oscillation mode can be divided into another frequency band, and its selected input signal is also different from that of other frequency bands.

[0175] For oscillation modes in different frequency bands, if the state variables calculated by the participation factors are different, the corresponding state variables can be selected as the input signals of the damping controller respectively; if the state variables calculated by the participation factors are the same, the order of the state variables should be arranged in descending order according to the principle of decreasing magnitude of the participation factor modulus, and different state variables should be selected in descending order as the input signals of the damping controller.

[0176] Embodiment 2

[0177] The purpose of this embodiment is to provide a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above method when executing the program.

[0178] Embodiment 3

[0179] The purpose of this embodiment is to provide a computer-readable storage medium.

[0180] A computer-readable storage medium stores a computer program, which executes the steps of the above method when executed by a processor.

[0181] Embodiment 4

[0182] The purpose of this embodiment is to provide a system for selecting an input signal of a synchronous condenser damping controller, comprising:

[0183] The differential equation and algebraic equation building module of the system is configured to: build a dynamic model of the grid-connected system of the new energy station including the synchronous condenser, and establish the differential equation and algebraic equation of the whole system based on the dynamic model of the grid-connected system;

[0184] The small signal linearization model building module of the whole system is configured to: linearize the differential equations and algebraic squares of the whole system at the stable operation point to establish the small signal linearization model of the whole system;

[0185] The oscillation mode determination module is configured to: obtain a system state matrix based on a small signal linearization model, calculate the eigenvalues ​​and left eigenvectors and right eigenvectors of the system state matrix, and determine different oscillation modes of the system according to the eigenvalue calculation results of the system state matrix;

[0186] The participation factor matrix construction module is configured to: combine the left eigenvector and the right eigenvector of the system, calculate the participation factors under different oscillation modes, and construct the participation factor matrix;

[0187] The input signal determination module is configured as follows: combining the participation factor matrix, for a certain oscillation mode of the system, by comparing and analyzing the size of the participation factor between it and different state variables, the state variable with the largest participation factor is used as the input signal of the synchronous condenser damping controller.

[0188] Embodiment 5

[0189] The purpose of this embodiment is to provide a computer program product containing instructions, which, when running on a computer, enables the computer to execute the methods and functions involved in any of the above embodiments.

[0190] The steps involved in the apparatus of the above embodiment correspond to the method embodiment 1, and the specific implementation method can refer to the relevant description part of embodiment 1. The term "computer-readable storage medium" should be understood as a single medium or multiple media including one or more instruction sets; it should also be understood to include any medium that can store, encode or carry an instruction set for execution by a processor and enable the processor to execute any method in the present invention.

[0191] Those skilled in the art should understand that the modules or steps of the present invention described above can be implemented by a general-purpose computer device, or alternatively, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. The present invention is not limited to any specific combination of hardware and software.

[0192] Although the above describes the specific implementation mode of the present invention in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art on the basis of the technical solution of the present invention without creative work are still within the scope of protection of the present invention.

Claims

1. A method for selecting an input signal of a synchronous condenser damping controller, characterized in that: include: Construct a dynamic model of the grid-connected system of a new energy station containing a synchronous condenser, and establish the differential equations and algebraic equations of the entire system based on the dynamic model of the grid-connected system; Linearize the differential equations and algebraic squares of the entire system at the stable operating point and establish a small signal linearization model of the entire system; Obtain the system state matrix based on the small signal linearization model, calculate the eigenvalues ​​and left eigenvectors and right eigenvectors of the system state matrix, and determine different oscillation modes of the system according to the eigenvalue calculation results of the system state matrix; Combine the left eigenvector and the right eigenvector of the system to calculate the participation factors under different oscillation modes and construct the participation factor matrix; Combined with the participation factor matrix, for a certain oscillation mode of the system, the participation factor between it and different state variables is compared and analyzed, and the state variable with the largest participation factor is used as the input signal of the synchronous condenser damping controller.

2. A method for selecting input signals of a synchronous condenser damping controller as claimed in claim 1, characterized in that: The dynamic model of the new energy station grid-connected system containing a synchronous condenser includes a dynamic model of the synchronous condenser and a dynamic model of the new energy station; Based on the dynamic model of the synchronous condenser, the differential equation and algebraic equation of the synchronous condenser are established, which are set as the first equation group; based on the dynamic model of the new energy station, the differential equation and algebraic equation of the new energy station are established, which are set as the second equation group; Based on the first set of equations and the second set of equations, differential equations and algebraic equations of the entire system are obtained; Preferably, when establishing the differential equation and algebraic equation of the synchronous condenser, the state variables and input variables of the synchronous condenser are selected to establish the differential equation and algebraic equation of the synchronous condenser; Preferably, when the differential equation and algebraic equation of the new energy station are constructed, the state variables and input variables of the new energy station are selected to establish the differential equation and algebraic equation of the new energy station; Preferably, when linearizing the differential equations and algebraic equations of the whole system, the differential equations and algebraic equations of the whole system are linearized at a stable operating point in combination with the Lyapunov linearization principle.

3. A method for selecting input signals of a synchronous condenser damping controller as claimed in claim 1, characterized in that: The process of calculating the eigenvalues, left eigenvectors, and right eigenvectors of the system state matrix is: Based on the system state matrix, a characteristic equation about the right eigenvector of the system state matrix is ​​established; Ax ri =λ i x ri In the formula, is the right eigenvector of the system state matrix A, is a matrix consisting of right eigenvectors; λ i is the right eigenvector x corresponding to the system state matrix A ri The subscript "i" indicates the arrangement of the system's eigenvalues; the subscript "n" indicates the total number of state variables; Based on the system state matrix, a characteristic equation about the left eigenvector of the system state matrix is ​​established; x li A=λ i x li In the formula, is the left eigenvector of the system state matrix A, is a matrix consisting of left eigenvectors; λ i is the left eigenvector x corresponding to the system state matrix A li The characteristic value of By solving the above characteristic equation, we can obtain the eigenvalue and left and right eigenvectors of the system.

4. A method for selecting input signals of a synchronous condenser damping controller as claimed in claim 1, characterized in that: Combining the left eigenvector and the right eigenvector of the system, the participation factors under different oscillation modes are calculated, specifically: The left eigenvector x of the system li =[u 1i …u ji …u ni ] and the right eigenvector x ri =[v 1i …v ji …v ni ] T The corresponding elements are multiplied internally to form a participation factor vector: P i =[u 1i v 1i u 2i v 2i …u ji v ji ] T In the formula, u represents the element in the left eigenvector; v represents the element in the right eigenvector; represents the participation factor vector corresponding to the i-th eigenvalue; the subscript "j" represents the permutation of the state variables; The participation factor vectors of each eigenvalue are then combined to form the participation matrix P: In the formula, is the system participation matrix, and the element p of the participation matrix P is called ji =u ji v ji is the participation factor, which measures the i-th mode λ i and the jth state variable Δx j The degree of mutual correlation between them.

5. The method for selecting input signals of a synchronous condenser damping controller according to claim 1, characterized in that: The process of selecting the input signal of the damping controller includes: according to the determined system oscillation mode λ i,i+1 , select the corresponding participation factor vector P i By comparing and analyzing the size of each element in the participation factor vector, the participation factor p with the largest modulus value in this oscillation mode is obtained. ji , that is, max{|p ji |}, the jth state variable can be located accordingly and selected as the input signal of the synchronous condenser damping controller.

6. A method for selecting input signals of a synchronous condenser damping controller as claimed in claim 1, characterized in that: If the participation factors with the largest modulus values ​​in different oscillation modes correspond to different state variables, the respective input signals can be determined according to their respective corresponding relationships; If the participation factor with the largest modulus value in different oscillation modes corresponds to the same state variable, the oscillation mode can be divided into frequency bands according to the oscillation frequency. If the oscillation modes with the same corresponding state variables are in the same frequency band, the same state variable can be selected as the input signal of the damping controller. If the oscillation modes with the same corresponding state variables are in different frequency bands, it is necessary to avoid selecting the same state variable. For this purpose, it is necessary to arrange the state variables in descending order according to the principle of decreasing modulus value for the participation factors of different oscillation modes, and select different state variables in descending order as the input signal of the damping controller.

7. A system for selecting input signals of a synchronous condenser damping controller, characterized in that: include: The differential equation and algebraic equation building module of the system is configured to: build a dynamic model of the grid-connected system of the new energy station including the synchronous condenser, and establish the differential equation and algebraic equation of the whole system based on the dynamic model of the grid-connected system; The small signal linearization model building module of the whole system is configured to: linearize the differential equations and algebraic squares of the whole system at the stable operation point to establish the small signal linearization model of the whole system; The oscillation mode determination module is configured to: obtain a system state matrix based on a small signal linearization model, calculate an eigenvalue and a left eigenvector and a right eigenvector of the system state matrix, and determine different oscillation modes of the system according to the eigenvalue calculation results of the system state matrix; The participation factor matrix construction module is configured to: combine the left eigenvector and the right eigenvector of the system, calculate the participation factors under different oscillation modes, and construct the participation factor matrix; The input signal determination module is configured as follows: combining the participation factor matrix, for a certain oscillation mode of the system, by comparing and analyzing the size of the participation factor between it and different state variables, the state variable with the largest participation factor is used as the input signal of the synchronous condenser damping controller.

8. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps of the method described in any one of claims 1 to 6 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method described in any one of claims 1 to 6 are performed.

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