Method and system for selecting input signals of a synchronous condenser damping controller

Abstract

The application provides a selection method and system for input signals of a synchronous phase modifier damping controller, comprising the following steps: establishing differential equations and algebraic equations of the whole system based on a dynamic model of a grid-connected system; linearizing the differential equations and algebraic equations of the whole system at a stable operating point to establish a small signal linearization model of the whole system; obtaining a system state matrix based on the small signal linearization model, calculating eigenvalues and left eigenvectors and right eigenvectors of the system state matrix, and determining different oscillation modes of the system according to the calculation results of the eigenvalues of the system state matrix; combining the left eigenvectors and the right eigenvectors of the system, calculating participation factors under different oscillation modes, and constructing a participation factor matrix; and combining the participation factor matrix, for a certain oscillation mode of the system, comparing and analyzing the participation factor sizes between the certain oscillation mode and different state variables, and taking a state variable with the largest participation factor as an input signal of a synchronous phase modifier damping controller.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of selection of input signals of a synchronous phase modifier damping controller, and particularly relates to a method and system for selecting input signals of a synchronous phase modifier damping controller. BACKGROUND

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

[0003] With the expansion of energy demand and the increasing requirements of environmental protection, new energy systems mainly based on wind power have developed rapidly, and the proportion of wind power in the power generation system is becoming larger and larger. Due to the characteristics of the "reverse distribution" between the wind energy-rich areas and the load centers in China, the technology of series compensation capacitor is usually used in large-scale wind power transmission in actual engineering. This technology improves the wind power transmission capacity, but also brings the risk of subsynchronous oscillation to the system.

[0004] Due to the different grid connection modes of wind turbines and traditional thermal power units, as well as the structural characteristics of "back-to-back" converters, the subsynchronous oscillation of wind turbines has its particularity, which is much more complex than that of traditional thermal power units, and seriously threatens the safe and stable operation of the system. 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] Currently, the subsynchronous oscillation suppression of wind turbines mainly includes optimizing control parameters, adding damping controllers, and adding flexible alternating current transmission system devices. 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, and economically and effectively suppresses the subsynchronous oscillation of the system.

[0006] Therefore, by analyzing the information of different oscillation modes contained in the feedback signal, the damping controller can be added in the control loop of the synchronous phase modifier to enhance its damping capacity, thereby suppressing the subsynchronous oscillation of the system. However, the selection of input signals of the synchronous phase modifier damping controller has a great impact on the damping enhancement effect. At present, most of the researches mainly rely on experience to select signals. Different power systems have different characteristics and parameters, and it may not be possible to accurately match the most suitable input signal only by experience. Moreover, the failure to select the best input signal may greatly reduce the effect of the additional damping controller, and may not achieve the expected control effect. In view of this problem, there is an urgent need for a method for determining the input signals of the synchronous phase modifier damping controller through quantitative calculation. SUMMARY

[0007] In order to overcome the above-mentioned deficiencies of the prior art, the present application provides a selection method of input signals of a synchronous phase modifier damping controller, which can select the input signal with the strongest correlation based on a quantitative calculation index, and exhibits the accuracy and scientific nature of signal selection.

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

[0009] In a first aspect, a selection method of input signals of a synchronous phase modifier damping controller is disclosed, comprising:

[0010] A dynamic model of a new energy station grid-connected system containing a synchronous phase modifier is constructed, and differential equations and algebraic equations of the entire system are established based on the dynamic model of the grid-connected system;

[0011] The differential equations and algebraic equations of the entire system are linearized at a stable operating point, and a small signal linearization model of the entire system is established;

[0012] Based on the small signal linearization model, a system state matrix is obtained, the eigenvalues and left eigenvectors and right eigenvectors of the system state matrix are calculated, and different oscillation modes of the system are determined according to the calculation results of the eigenvalues of the system state matrix;

[0013] The participation factors under different oscillation modes are calculated by combining the left eigenvectors and right eigenvectors of the system, and a participation factor matrix is constructed;

[0014] For a certain oscillation mode of the system, the participation factor matrix is combined, and by comparing and analyzing the participation factor sizes between the participation factor matrix and different state variables, the state variable with the largest participation factor is selected as the input signal of the synchronous phase modifier damping controller.

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

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

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

[0018] As a further technical solution, when the differential equations and algebraic equations of the synchronous phase modifier are established, the state variables and input variables of the synchronous phase modifier are selected, and the differential equations and algebraic equations of the synchronous phase modifier are established.

[0019] As a further technical solution, the differential equation and algebraic equation of the new energy station are established by selecting state variables and input variables of the new energy station.

[0020] As a further technical solution, when the differential equation and algebraic equation of the whole system are linearized, the differential equation and algebraic equation of the whole system are linearized at the 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] In the formula, is a small signal form of the state variable of the whole system; is a small signal form of the input variable of the whole system; is a system matrix; is an input matrix; is a control matrix; is a direct transfer matrix.

[0024] As a further technical solution, when the system state matrix is calculated, the system state matrix of the system is calculated based on the small signal linearization model of the whole system A .

[0025]

[0026] In the formula, is the state matrix of the whole system.

[0027] As a further technical solution, the process of calculating the eigenvalue and the left eigenvector and the right eigenvector of the system state matrix is as follows:

[0028] Based on the system state matrix, a characteristic equation about the right eigenvector of the system state matrix is established;

[0029]

[0030] In the formula, is the right eigenvector of the system state matrix A , is a matrix composed of the right eigenvector; is the eigenvalue corresponding to the right eigenvector A of the system state matrix ; the subscript "i" represents the arrangement of the system eigenvalue; the subscript "n" represents the total number of state variables;

[0031] Based on the system state matrix, a characteristic equation about the left eigenvector of the system state matrix is established;

[0032]

[0033] In the formula, is the left eigenvector of the system state matrix A , is a matrix composed of the left eigenvector; is the eigenvalue corresponding to the left eigenvector A of the system state matrix ;

[0034] The eigenvalue of the system and the left and right eigenvectors are obtained by solving the above characteristic equation.

[0035] As a further technical solution, different oscillation modes of the system are determined according to the eigenvalue calculation result of the system state matrix, specifically including:

[0036] If there is a pair of conjugate complex numbers in the system eigenvalue calculation result, the pair of eigenvalues corresponds to an oscillation mode of the system, that is:

[0037]

[0038] In the formula, is a pair of conjugate eigenvalues of the system, a is the real part of the conjugate eigenvalue of the system, b is the imaginary part of the eigenvalue of the system;

[0039] If a <0, then corresponds to a stable oscillation mode of the system, and the damping is positive;

[0040] If a> 0, then corresponds to an unstable oscillation mode of the system, and the damping is negative, and the oscillation frequency is .

[0041] As a further technical solution, the participation factor under different oscillation modes is calculated in combination with the left eigenvector and the right eigenvector of the system, specifically:

[0042] The left eigenvector and the right eigenvector of the system are multiplied by the corresponding elements inside to form a participation factor vector:

[0043]

[0044] In the formula, u indicates the element in the left eigenvector; vrepresents the right eigenvector inner element; represents the participation factor vector corresponding to the i-th eigenvalue; the subscript "j" represents the arrangement of the state variables;

[0045] The participation factor vector of each eigenvalue is then combined to form a participation matrix P :

[0046]

[0047] wherein, is the system participation matrix, referred to as the participation matrix P The element of the participation matrix is the participation factor, which measures the degree of correlation between the i-th mode and the j-th state variable .

[0048] As a further technical solution, the process of selecting the damping controller input signal includes: selecting the corresponding participation factor vector based on the determined system oscillation mode P i , obtaining the participation factor with the largest modulus under this oscillation mode by comparing and analyzing the sizes of the elements in the participation factor vector p ji , that is, , and positioning the j-th state variable accordingly, which is selected as the input signal of the synchronous phase modifier damping controller.

[0049] As a further technical solution, if the participation factors with the largest modulus under different oscillation modes correspond to different state variables, the respective input signals can be determined according to their respective corresponding relationships;

[0050] If the participation factors with the largest modulus under different oscillation modes correspond to the same state variable, the oscillation modes can be divided into frequency bands according to the oscillation frequency, if the oscillation modes corresponding to the same state variable are within the same frequency band, the same state variable can be selected as the input signal of the damping controller, if the oscillation modes corresponding to the same state variable are in different frequency bands, different state variables need to be selected as the input signals of the damping controller according to the modulus size decreasing principle, and the state variables are arranged in order.

[0051] In a second aspect, a system for selecting the input signal of a synchronous phase modifier damping controller is disclosed, comprising:

[0052] The differential equation and algebraic equation construction module of the system is configured to: construct a dynamic model of a new energy station grid-connected system containing a synchronous phase modifier, and establish the differential equation and algebraic equation of the entire system based on the dynamic model of the grid-connected system.

[0053] The small-signal linearization model construction module of the whole system is configured to linearize differential equations and algebraic equations of the whole system at a stable operating point, and establish a small-signal linearization model of the whole system.

[0054] The oscillation mode determination module is configured to obtain a system state matrix based on the small-signal linearization model, calculate eigenvalues and left and right eigenvectors of the system state matrix, and determine different oscillation modes of the system according to the calculation results of the eigenvalues of the system state matrix.

[0055] The participation factor matrix construction module is configured to calculate participation factors in different oscillation modes by combining the left and right eigenvectors of the system, and construct a participation factor matrix.

[0056] The input signal determination module is configured to combine the participation factor matrix, and for a certain oscillation mode of the system, compare and analyze the participation factors between the oscillation mode and different state variables, and the state variable with the largest participation factor is taken as the input signal of the synchronous condenser damping controller.

[0057] The above one or more technical solutions have the following beneficial effects:

[0058] The technical scheme of the present application is based on the selection method of the input signal of the synchronous condenser damping controller, establishes a small-signal linearization model of the new energy station grid-connected system containing a synchronous condenser, analyzes the oscillation mode of the new energy station by calculating the eigenvalues of the system. The design of the additional damping controller mainly includes three parts: input signal, control structure and parameters, and controller placement position. 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 scheme of the present application selects the input signal with the strongest correlation with the oscillation mode through this method, and lays a foundation for the subsequent design of a damping controller with good performance.

[0059] The technical scheme of the present application is based on the selection method of the input signal of the synchronous condenser damping controller, and according to the quantitative calculation of the controllability and observability of different signals, the correlation degree of different signals to the same oscillation mode can be sorted, and the effectiveness of the selection of the damping controller signal can be evaluated.

[0060] The technical scheme of the present application is based on the selection method of the input signal of the synchronous condenser damping controller, and according to the quantitative calculation of the controllability and observability of different signals, the correlation degree of different signals to the same oscillation mode can be sorted, and the effectiveness of the selection of the damping controller signal can be evaluated.

[0061] The advantages of the additional aspects of the present application will be partially given in the following description, partially will become obvious from the following description, or will be understood by the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] The accompanying drawings, 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.

[0063] Figure 1 The present invention is a flow chart of a method for selecting an input signal of a synchronous condenser damping controller;

[0064] Figure 2 This is the topology diagram of the grid-connected system of a new energy station including synchronous condensers;

[0065] Figure 3 is the modal diagram of participation factor of oscillation mode 1;

[0066] Figure 4 is the modal diagram of participation factor of oscillation mode 2;

[0067] Figure 5 Modal diagram of participation factor of oscillation mode 3. DETAILED DESCRIPTION

[0068] It should be noted that the following detailed descriptions are exemplary and intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which the present invention belongs.

[0069] It should be noted that the terms used herein are for describing particular embodiments only and are not intended to limit the exemplary embodiments according to the present invention.

[0070] In the absence of conflict, the embodiments of the present invention and the features thereof may be combined with each other.

[0071] Example 1

[0072] like Figure 1 As shown, this embodiment discloses a method for selecting an input signal of a synchronous condenser damping controller, comprising:

[0073] S1: In D - Q Construct a dynamic model of the grid-connected system of a new energy station containing a synchronous condenser in a rotating coordinate system, and establish differential equations and algebraic equations for the entire system;

[0074] The dynamic model is built on D - Q In the rotating coordinate system, the control structure of the converter is based on D - QIn the rotating coordinate system, the control accuracy of the control structure is more accurate than that in the three-phase static abc coordinate system; secondly, the Lyapunov linearization principle is also based on this coordinate system.

[0075] S2: According to the Lyapunov linearization principle, the differential equation and the algebraic equation of the whole system are linearized at the stable operating point, and a small signal linearization model of the whole system is established;

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

[0077] S4: According to the left and right eigenvectors of the system, the participation factors of the system in different oscillation modes are calculated, and a participation factor matrix is constructed;

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

[0079] At this point, the input signal of the synchronous compensator damping controller has been successfully selected on the basis of the stability analysis of the grid-connected system of the new energy station containing the synchronous compensator.

[0080] The technical scheme of the embodiment determines different oscillation modes of the system by calculating the eigenvalues of the system, obtains the participation factors for measuring the 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 compensator damping controller by comparing and analyzing the participation factors of the system, which is convenient for the design of the damping controller.

[0081] In step S1 of the technical scheme of the embodiment, D - Q When constructing the dynamic model of the grid-connected system of the new energy station containing the synchronous compensator in the rotating coordinate system, the dynamic model of the synchronous compensator includes asynchronous motor, machine-side converter and its control structure, DC link, grid-side converter and its control structure, filter link, transmission line and phase-locked loop; the equivalent direct-driven wind turbine system is used to replace the new energy station for analysis, and the dynamic model of the new energy station includes converter and its control structure, filter link and transmission line, and the specific structure is shown in the topological graph of the grid-connected system of the new energy station containing the synchronous compensator shown in the accompanying drawings. Figure 2

[0082] ​In step S1 of the embodiment, the process of establishing the differential equations and algebraic equations of the whole system comprises: after constructing the dynamic models of the synchronous phase modifier and the new energy station respectively, selecting the state variables and input variables of each, establishing the differential equations and algebraic equations of each, and then integrating the models of the synchronous phase modifier and the new energy station, establishing the differential equations and algebraic equations of the whole system on the basis of the state variables and input variables of the whole system.

[0083] The dynamic model of each module of the synchronous phase modifier is as follows:

[0084] The stator voltage and rotor voltage equations of the asynchronous motor satisfy:

[0085]

[0086] In the formula, the subscript of the variable " indicates the per-unit form of the variable; pu u sd,pu 、u sq,pu are respectively the d-axis and q-axis components of the stator voltage; u rd,pu 、u rq,pu are respectively the d-axis and q-axis components of the rotor voltage; i sd,pu 、i sq,pu are respectively the d-axis and q-axis components of the stator current; i rd,pu 、i rq,pu are respectively the d-axis and q-axis components of the rotor current; 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 equivalent two-phase winding self-inductance of the stator in the dq coordinate system; L r,pu is the equivalent two-phase winding self-inductance of the rotor in the dq coordinate system; L m,pu is the mutual inductance between the equivalent windings of the stator and rotor in the dq coordinate system; is the angular velocity obtained by the phase-locked loop tracking the grid synchronous angular velocity; is the rotor angular velocity; is the angular velocity reference value.

[0087] The rotor motion equation of the asynchronous motor satisfies:

[0088]

[0089] In the formula,​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; is the rotor angle.

[0090] The dynamic model of the machine-side converter control structure satisfies:

[0091] The slip-link control equation is:

[0092]

[0093] wherein, K wr,p , K wr,i is the proportional coefficient and integral coefficient of the slip control link PI controller; is the rotor angular velocity reference value; P s,ref,pu , Q s,ref,pu is the stator-side output active power and reactive power reference value; x rw,d is defined as the variable at the outlet of the slip integral link.

[0094] The power outer loop control equation is:

[0095]

[0096]

[0097] wherein, 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 is the stator-side output active power and reactive power; i rd,ref,pu , i rq,ref,pu is the rotor d-axis and q-axis current reference value, respectively; x rp,d , x rp,q is defined as the active power and reactive power integral link outlet variable, respectively.

[0098] The current inner loop control equation is:

[0099]

[0100]

[0101] wherein, K ri,p 、 K ri,i are the proportional and integral coefficients of the inner current loop PI controller; x rp,d 、 x rp,q are defined as the variables at the outlet of the integral term of the rotor d, q-axis current, respectively.

[0102] The dynamic model of the DC link satisfies:

[0103]

[0104] wherein, C sc,pu is the capacitance value of the DC link; u dc,pu is the voltage across the capacitance; u fd,pu 、 u fq,pu are the d, q-axis components of the voltage at the outlet of the grid-side converter; i fd,pu 、 i fq,pu are the d, q-axis components of the current at the outlet of the grid-side converter.

[0105] The dynamic model of the grid-side converter control structure satisfies:

[0106] The control equation of the outer voltage loop is:

[0107]

[0108] wherein, K gu,p 、 K gu,i are the proportional and integral coefficients of the outer power loop PI controller; u dc,ref,pu is the reference value of the voltage across the capacitance; i fd,ref,pu 、 i fq,ref,pu are the reference values of the d, q-axis components of the current at the outlet of the grid-side converter; x gu,d is defined as the variable at the outlet of the integral term of the outer voltage loop.

[0109]

[0110]

[0111] wherein, Kgi,p 、 K gi,i Kp, Ki are the proportional and integral coefficients of the inner current loop PI controller; u dc,ref,pu Vc is the reference value of the capacitor voltage; u odsc,pu 、 u oqsc,pu id, iq are the d, q axis components of the capacitor voltage across the transmission line; x gi,d 、 x gi,q id0, iq0 are defined as the output variables of the d, q axis current integrators at the output of the grid side converter; L f,pu 、 R f,pu L, R are the inductance and resistance of the filter respectively.

[0112] The dynamic model of the filter is:

[0113]

[0114] The dynamic model of the transmission line is:

[0115]

[0116] where, C esc,pu 、 L esc,pu 、 R esc,pu C, L, R are the capacitance, inductance and resistance of the transmission line respectively; i odsc,pu 、 i oqsc,pu idL, iqL are the d, q axis components of the current flowing through the inductance of the transmission line; u bdsc,pu 、 u bqsc,pu id0, iq0 are the d, q axis components of the grid connected point voltage of the synchronous condenser.

[0117] The dynamic model of the phase-locked loop is:

[0118]

[0119] where, K P,PLL 、 K I,PLL Kp, Ki are the proportional and integral coefficients of the phase-locked loop PI controller; is the angle obtained by the phase-locked loop tracking the grid.

[0120] The dynamic model construction method of the new energy station can refer to the construction method of the grid-side converter of the synchronous compensator, and thus will not be described herein. Thus, the dynamic models of the synchronous compensator and the new energy station are obtained respectively D Q Dynamic models in the rotating coordinate system.

[0121] The dynamic models of the synchronous compensator and the new energy station are sorted and transformed, and the differential equations and algebraic equations of the synchronous compensator and the new energy station are obtained respectively. The differential equations and algebraic equations of the synchronous compensator are as follows:

[0122]

[0123] In the formula, is the state variable of the synchronous compensator; is the input variable of the synchronous compensator; f SC and g SC and respectively represent the nonlinear functions of the differential equations and the algebraic equations of the synchronous compensator. The state variable contains the differential term in the differential equation, and the input variable refers to the power, torque, node voltage and other variables that have an explicit or implicit relationship with the state variable.

[0124] The differential equations and the algebraic equations of the new energy station are as follows:

[0125]

[0126] 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 and respectively represent the nonlinear functions of the differential equations and the algebraic equations of the new energy station.

[0127] By combining the differential equations and the algebraic equations of the synchronous compensator and the new energy station, the differential equations and the algebraic equations of the entire system are obtained as follows:

[0128]

[0129] In the formula, is the state variable of the entire system; is the input variable of the entire system; f and g respectively represent the nonlinear functions of the differential equations and the algebraic equations of the entire system.

[0130] ​In step S2 of the sub-technical solution of this embodiment, when linearizing the differential equations and algebraic equations of the entire system, the differential equations and algebraic equations of the entire system are linearized at the stable operating point in combination with the Lyapunov linearization principle, and a small signal linearization model of the entire system is established.

[0131] To illustrate the basic principle of Lyapunov linearization, consider the following nonlinear system described by differential equations:

[0132]

[0133] Where, x n are the state variables of the example nonlinear system; f n Nonlinear function representing the example nonlinear system

[0134] Taylor expansion of the above equation at the origin:

[0135]

[0136] Where, is the small signal form of the state scalar of the example nonlinear system, is the value of each state variable when the nonlinear system is running stably, express Expressions of second order and above. If exist The neighborhood of The linear system described by the following formula can often be used to analyze the nonlinear system at the equilibrium point of the system. Stability:

[0137]

[0138] Combined with Lyapunov linearization theory, the differential equations and algebraic equations of the grid-connected system of the new 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:

[0139]

[0140] Where, is the small signal form of the state variable of the entire system; Small signal form of input variables for the entire system; is the system matrix; is the input matrix; is the control matrix; is a direct transfer matrix.

[0141] The selection of state variables is related to the nonlinear elements of the system. Each nonlinear element corresponds to a state variable, such as the current flowing through the inductor, and 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, power calculations require voltage and current, which are state variables, but power is not. Therefore, power is the input variable.

[0142] 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, are constructed from the corresponding coefficients. This allows the establishment of a small-signal linear model of the entire system.

[0143] 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 of the system is calculated by the following formula: A :

[0144]

[0145] Where, is the state matrix of the entire system.

[0146] 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.

[0147] Based on the system state matrix, the characteristic equation about the right eigenvector of the system state matrix is ​​established:

[0148]

[0149] Where, is the system state matrix A The right eigenvector of is a matrix consisting of right eigenvectors; is the system state matrix A The corresponding right eigenvector x ri The subscript “i” represents the arrangement of the system’s eigenvalues; the subscript “n” represents the total number of state variables, n=38.

[0150] Similarly, based on the system state matrix, the characteristic equation of the left eigenvector of the system state matrix is ​​established:

[0151]

[0152] Where, is a left eigenvector of the system state matrix A , is a matrix composed of the left eigenvectors; is a corresponding eigenvalue of the system state matrix A , x li .

[0153] In step S3 of the embodiment, the process of determining different oscillation modes of the system by using the eigenvalue analysis method includes: combining the eigenvalue analysis method, that is, if all the eigenvalues are located in the left half of the complex plane (i.e., the real part is less than zero), the system is stable; if there is any one or more eigenvalues located in the right half of the complex plane or on the imaginary axis, the system is unstable.

[0154] If there is a pair of conjugate complex numbers in the calculation result of the eigenvalue of the system, the pair of eigenvalues corresponds to an oscillation mode of the system. That is:

[0155]

[0156] In the formula, is a pair of conjugate eigenvalues of the system, a is the real part of the conjugate eigenvalue of the system, b is the imaginary part of the conjugate eigenvalue of the system.

[0157] If a <0, then corresponds to a stable oscillation mode of the system, and the damping is positive; if a> 0, then corresponds to an unstable oscillation mode of the system, and the damping is negative. The oscillation frequency is .

[0158] In step S4 of the embodiment, the process of calculating the participation factor of the system by combining the left and right eigenvectors of the system includes: multiplying the corresponding part elements in the left eigenvector x li [ u 1i … u ji … u ni ] and the right eigenvector x ri [ v 1i … v ji … v ni ] T to form a participation factor vector:

[0159]

[0160] Where, u Represents the elements in the left eigenvector; v Represents the elements in the right eigenvector; P i 38×1 represents the participation factor vector corresponding to the i-th eigenvalue; the subscript “j” denotes the permutation of the state variables.

[0161] The participation factor vectors of each eigenvalue are then combined to form the participation matrix P :

[0162]

[0163] Where, is the system participation matrix. P Elements p ji = u ji v ji is the participation factor, which measures the i-th mode and the jth state variable The degree of mutual correlation between them.

[0164] 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 determined in step S4, , 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 with the largest modulus value in this oscillation mode is obtained. p ji , i.e. max{| p ji |}, the jth state variable can be located accordingly and selected as the input signal of the synchronous condenser damping controller.

[0165] In step S5 of the embodiment, if the participation factors with the maximum modulus in different oscillation modes correspond to different state variables, the respective input signals can be determined according to the respective corresponding relationship; if the participation factors with the maximum modulus in different oscillation modes correspond to the same state variable, the oscillation modes can be divided into frequency bands according to the oscillation frequencies, if the oscillation modes corresponding to the same state variable 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 corresponding to the same state variable are in different frequency bands, different state variables need to be selected as the input signal of the damping controller by arranging the state variables in order according to the principle of decreasing modulus value.

[0166] The state variables are arranged in order according to the principle of decreasing modulus value, and different state variables are selected as the input signal of the damping controller, because:

[0167] Firstly, if the same input signal is used to control the oscillation of all frequency bands, it may not be possible to accurately adjust the characteristics of each frequency band, thereby limiting the control effect; secondly, using the same input signal may produce adverse control effects on some frequency bands, and even may excite new oscillation modes, thereby further reducing the stability of the system.

[0168] A new energy station grid-connected system containing a synchronous phase modifier is used to verify the effectiveness of the input signal selection method of the synchronous phase modifier damping controller proposed in the application. All analyses are performed in Matlab on an Inter 1.60GHz 16GB notebook computer.

[0169] The new energy station grid-connected system containing a synchronous phase modifier is shown in FIG. 1. Figure 2 The new energy station grid-connected system containing a synchronous phase modifier contains a synchronous phase modifier and a new energy station grid connection, wherein the synchronous phase modifier is a double-fed structure, containing an asynchronous motor, a machine-side converter and a control structure thereof, a direct current link, a grid-side converter and a control structure thereof, a filter link, a power transmission line and a phase-locked loop; the new energy station grid connection is analyzed by using an equivalent direct-drive wind turbine instead of a new energy station, including a converter and a control structure thereof, a filter link, a power transmission line, an alternating current line and an infinite grid.

[0170] The embodiment constructs a dynamic model of the new energy station grid-connected system containing a synchronous phase modifier, linearizes it at a stable operating point, establishes a state space model of the system, calculates the system eigenvalues and left and right eigenvectors based on the state space model of the system, and determines different oscillation modes of the system in combination with the calculation results of the eigenvalues. Part of the oscillation modes of the system are shown in Table 1.

[0171] Table 1 Oscillation modes of the new energy station grid-connected system containing a synchronous phase modifier

[0172]

[0173] The participation factors of the three oscillation modes of the system are calculated in combination with the left and right eigenvectors of the system, and the calculation results are plotted into a participation factor mode diagram, as shown in Figure 3 , Figure 4 and Figure 5 .

[0174] For the selection of the input signal of the damping controller of the oscillation mode 1, in combination with the participation factor mode Figure 3 , it can be found that the state variable with the largest correlation degree with this oscillation mode is the power angle of the direct-drive wind turbine , and thus can be selected as the input signal of the damping controller of the synchronous condenser; for the selection of the input signal of the damping controller of the oscillation mode 2, in combination with the participation factor mode Figure 4 , it can be found that the state variable with the largest correlation degree with this oscillation mode is the power angle of the direct-drive wind turbine , and thus can be selected as the input signal of the damping controller of the synchronous condenser; for the selection of the input signal of the damping controller of the oscillation mode 3, in combination with the participation factor mode Figure 5 , it can be found that the state variable with the largest correlation degree with this oscillation mode is the d-axis component of the rotor current of the synchronous condenser D i rd,pu , and thus i rd,pu can be selected as the input signal of the damping controller of the synchronous condenser.

[0175] It can be found from the above signal selection results that the input signals selected for the first two oscillation modes are the same, because the oscillation frequencies of the two oscillation modes are close, and the two oscillation modes can be divided into the same frequency band. For the oscillation in the same frequency band, the input signal of the damping controller can be selected as the same state variable. The oscillation frequency of the third oscillation mode is quite different from those of the first two oscillation modes, and thus the third oscillation mode can be divided into another frequency band, and the input signal selected for the third oscillation mode is also different from those of the other frequency bands.

[0176] For the oscillation modes in different frequency bands, if the state variables calculated through the participation factors are different, the respective state variables can be selected as the input signals of the damping controllers; if the state variables calculated through the participation factors are the same, the state variables should be arranged in descending order according to the magnitude of the participation factor mode value, and different state variables can be selected as the input signals of the damping controllers in turn.

[0177] Embodiment Two

[0178] ​The embodiment aims to provide a computer device, comprising 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.

[0179] Embodiment three

[0180] The embodiment aims to provide a computer readable storage medium.

[0181] A computer readable storage medium, having a computer program stored thereon, wherein the program is executable by a processor to implement the steps of the above method.

[0182] Embodiment four

[0183] The embodiment aims to provide a selection system of input signals of a synchronous phase modifier damping controller, comprising:

[0184] The differential equation and algebraic equation construction module of the system is configured to: construct a dynamic model of a new energy station grid-connected system containing a synchronous phase modifier, and establish differential equations and algebraic equations of the entire system based on the dynamic model of the grid-connected system;

[0185] The small signal linearization model construction module of the entire system is configured to: linearize the differential equations and algebraic equations of the entire system at a stable operating point, and establish a small signal linearization model of the entire system;

[0186] The oscillation mode determination module is configured to: obtain a system state matrix based on the small signal linearization model, calculate eigenvalues and left eigenvectors and right eigenvectors of the system state matrix, and determine different oscillation modes of the system according to the calculation results of the eigenvalues of the system state matrix;

[0187] The participation factor matrix construction module is configured to: combine the left eigenvectors and the right eigenvectors of the system, calculate participation factors under different oscillation modes, and construct a participation factor matrix;

[0188] The input signal determination module is configured to: combine the participation factor matrix, for a certain oscillation mode of the system, compare and analyze the participation factor sizes between the oscillation mode and different state variables, and take the state variable with the largest participation factor as the input signal of the synchronous phase modifier damping controller.

[0189] Embodiment five

[0190] The embodiment aims to provide a computer program product containing instructions, which, when executed on a computer, causes the computer to perform the method and functions involved in any one of the above embodiments.

[0191] The steps involved in the apparatus of the above embodiments correspond to the method embodiment one, and the specific implementation can refer to the relevant description part of embodiment one. The term "computer readable storage medium" should be understood as including a single medium or multiple media of one or more instruction sets; it should also be understood as including any medium capable of storing, encoding, or carrying a set of instructions for execution by a processor and causing the processor to perform any of the methods in the present application.

[0192] Those skilled in the art should understand that each module or step of the present application described above can be realized by a general computer device, alternatively, they can be realized by program codes executable by a computing device, so that they can be stored in a storage device for execution by a computing device, or they can be respectively made into each integrated circuit module, or a plurality of modules or steps among them can be made into a single integrated circuit module to realize. The present application is not limited to any specific combination of hardware and software.

[0193] Although the specific embodiments of the present application are described above in combination with the drawings, it is not a limitation on the scope of protection of the present application, and those skilled in the art should understand that various modifications or changes made by those skilled in the art on the basis of the technical solutions of the present application without creative labor are still within the scope of protection of the present application.

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 linear model of the entire system; Obtain the system state matrix based on the small signal linearization model, calculate the eigenvalues, left eigenvectors, and right eigenvectors of the system state matrix, and determine the different oscillation modes of the system based on the eigenvalue calculation results of the system state matrix; Combining the left and right eigenvectors of the system, the participation factors under different oscillation modes are calculated and the participation factor matrix is ​​constructed. 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; The process of selecting the input signal of the damping controller includes: , select the corresponding participation factor vector By comparing and analyzing the size of each element in the participation factor vector, the participation factor with the largest modulus value in this oscillation mode is obtained. ,Right now , we can locate the jth state variable based on this and select it as the input signal of the synchronous condenser damping controller; If the participation factors with the largest modulus values ​​in different oscillation modes correspond to different state variables, then 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, the state variables need to be arranged in descending order according to the principle of decreasing modulus value for the participation factors of different oscillation modes, and different state variables are selected in descending order as the input signal of the damping controller.

2. The method for selecting an input signal of a synchronous condenser damping controller according to claim 1, wherein: 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; The differential equations and algebraic equations of the synchronous condenser are established based on the dynamic model of the synchronous condenser, which is set as the first equation group. The differential equations and algebraic equations of the new energy station are established based on the dynamic model of the new energy station, which is set as the second equation group. Based on the first and second equations, differential equations and algebraic equations of the entire system are obtained; 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; 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; When linearizing the differential equations and algebraic equations of the entire system, the Lyapunov linearization principle is combined to linearize the differential equations and algebraic equations of the entire system at the stable operating point.

3. The method for selecting an input signal of a synchronous condenser damping controller according to claim 1, wherein: The process of calculating the eigenvalues, left eigenvectors, and right eigenvectors of the system state matrix is: Based on the system state matrix, establish the characteristic equation about the right eigenvector of the system state matrix; Where, is the system state matrix A The right eigenvector of is a matrix consisting of right eigenvectors; is the system state matrix A The corresponding right eigenvector 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, establish the characteristic equation about the left eigenvector of the system state matrix; Where, is the system state matrix A The left eigenvector of is a matrix consisting of left eigenvectors; is the system state matrix A The corresponding left eigenvector The characteristic value of By solving the above characteristic equation, the eigenvalues ​​and left and right eigenvectors of the system are obtained.

4. The method for selecting an input signal of a synchronous condenser damping controller according to claim 1, wherein: Combining the left and right eigenvectors of the system, the participation factors under different oscillation modes are calculated, specifically: The left eigenvector of the system and the right eigenvector Multiply the corresponding elements internally to form a participation factor vector: Where, u Represents the elements in the left eigenvector; v Represents the elements 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 : Where, is the system participation matrix, called participation matrix P Elements p ji = u ji v ji is the participation factor, which measures the i-th mode and the jth state variable The degree of mutual correlation between them.

5. A system for selecting input signals of a synchronous condenser damping controller, characterized in that: include: The system's differential equation and algebraic equation building module is configured to: construct a dynamic model of the grid-connected system of a new energy station including 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; 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 operating point and establish the small signal linearization model of the whole system; an oscillation mode determination module configured to: obtain a system state matrix based on a small signal linearization model, calculate 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; 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 to: combine the participation factor matrix, analyze the participation factors of a certain oscillation mode of the system and different state variables by comparing them, and use the state variable with the largest participation factor as the input signal of the synchronous condenser damping controller; The process of selecting the input signal of the damping controller includes: , select the corresponding participation factor vector By comparing and analyzing the size of each element in the participation factor vector, the participation factor with the largest modulus value in this oscillation mode is obtained. ,Right now , we can locate the jth state variable based on this and select it as the input signal of the synchronous condenser damping controller; If the participation factors with the largest modulus values ​​in different oscillation modes correspond to different state variables, then 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, the state variables need to be arranged in descending order according to the principle of decreasing modulus value for the participation factors of different oscillation modes, and different state variables are selected in descending order as the input signal of the damping controller.

6. 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 4 is implemented.

7. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the steps of the method according to any one of claims 1 to 4 are implemented.

8. 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 according to any one of claims 1 to 4 are performed.

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