Wind power grid-connected low-frequency oscillation analysis method and system based on inverse characteristic trajectory method

Abstract

The application discloses a wind power grid-connected low-frequency oscillation analysis method and system based on an inverse characteristic trajectory method, and relates to the technical field of power grid safety. The technical scheme points of the application are as follows: the following steps are included: constructing a Heffron-Phillips model considering wind turbine grid connection; simplifying the Heffron-Phillips model considering wind turbine grid connection into a feedback connection model which can realize application of the characteristic trajectory method; based on the feedback connection model, applying the inverse characteristic trajectory method to solve the stability margin; analyzing the influence of wind power grid connection on the open-loop transfer function matrix of the system; and analyzing the influence of wind power grid connection on the low-frequency oscillation of the system. The application improves the accuracy of the stability margin approximation value on the basis of the characteristic trajectory method, obtains an inverse similarity matrix and a stability margin expression which are simple in mathematical relationship, and obtains a clear explanation of the influence mechanism of wind turbine access on the low-frequency oscillation.

Description

Technical Field

[0001] This invention relates to the field of power grid safety technology, and more specifically, to a method and system for analyzing low-frequency oscillations in wind power grid connection based on the inverse characteristic trajectory method. Background Technology

[0002] The impact of wind turbine grid connection on low-frequency oscillations has received widespread attention in the field of modern power system stability analysis. The effects of wind turbine grid connection on the power system include the dynamic connection of wind turbines and changes in the original system's power flow distribution.

[0003] Currently, research methods used in these areas mainly include sensitivity analysis, mode analysis, damped torque method, and time-domain simulation. Sensitivity analysis can assess the impact of wind turbines on low-frequency oscillations by measuring the sensitivity of the damping ratio to the unit's inertia; mode analysis can compare the impact of constant-speed and variable-speed wind turbines on power system oscillations; the damped torque method can effectively decompose the impact of wind turbine grid connection dynamics and power flow changes on electromechanical oscillation modes; and time-domain simulation can perform time-domain analysis of the impact of wind turbine grid connection. However, while these four analysis methods have been widely applied to the stability analysis of low-frequency oscillations caused by wind turbine grid connection, they still cannot fully explain the impact of wind turbine dynamics and power flow distribution changes introduced by grid connection on system stability margins. Therefore, they cannot provide a clearer explanation of the mechanism by which wind turbine connection affects low-frequency oscillations. Furthermore, facing increasingly complex power grids, small-disturbance stability analysis requires a more precise study of the impact of changes in system operating conditions (such as continuous changes in unit output) on system stability.

[0004] Therefore, how to research and design a method and system for analyzing low-frequency oscillations in wind power grid connection that can overcome the above-mentioned defects is an urgent problem that we need to solve. Summary of the Invention

[0005] To address the shortcomings of existing technologies, the purpose of this invention is to provide a method and system for analyzing low-frequency oscillations in wind power grid connection based on the inverse characteristic trajectory method. This method improves the accuracy of the stability margin approximation based on the characteristic trajectory method, yields a mathematically simple inverse similarity matrix and stability margin expression, and provides a clear explanation of the mechanism by which wind turbine access affects low-frequency oscillations.

[0006] The above-mentioned technical objective of the present invention is achieved through the following technical solution:

[0007] Firstly, a method for analyzing low-frequency oscillations in wind power grid connection based on the inverse characteristic trajectory method is provided, including the following steps:

[0008] Construct a Heffron-Phillips model that considers wind turbine grid connection;

[0009] The Heffron-Phillips model considering wind turbine grid connection is simplified into a feedback connection model that enables the application of the characteristic trajectory method;

[0010] Based on the feedback connection model, the inverse characteristic trajectory method is applied to solve the stability margin.

[0011] Analyze the impact of wind power grid connection on the system's open-loop transfer function matrix;

[0012] Analyze the impact of wind power grid connection on low-frequency oscillations in the system.

[0013] Furthermore, the process of constructing the Heffron-Phillips model considering wind turbine grid connection is as follows:

[0014] Based on the traditional Heffron-Phillips model, the injected power of the wind turbine is used as the input signal of the system, and the voltage amplitude of the wind turbine connected to the bus is used as the output signal of the system.

[0015] The small-signal model of the wind turbine is:

[0016] ;

[0017] in, This indicates the increment of active power injected into the wind turbine; This indicates the increment of reactive power injected into the wind turbine; This indicates the increment of the voltage amplitude injected into the bus by the fan; express right The transfer function; express right The transfer function;

[0018] The linearized model of the wind turbine after it is connected to the power system is as follows:

[0019] ;

[0020] in, Represents generalized frequency; This represents the angular displacement of each generator rotor relative to the synchronous reference shaft, i.e., the power angle; Indicates the rotational speed of each generator; This represents the quadrature-axis transient electromotive force of each generator; This indicates the output voltage of the automatic voltage regulator; This represents the system matrix in the classic Heffron-Phillips model; This represents the intermediate matrix determined by the input matrix, output matrix, and direct transition matrix in the classic Heffron-Phillips model; This represents the system matrix after the wind turbine is connected;

[0021] The system matrix after connecting the wind turbine is as follows:

[0022] ;

[0023] in, Represents a diagonal matrix containing the inertial constant of the generator rotor; Represents a diagonal matrix containing the rotor motion damping coefficients; This represents the transfer function matrix of the governor-prime mover system; Represents a diagonal matrix containing the d-axis transient time constants of each generator; Represents the time constant; Indicates excitation gain; Represents the PSS transfer function matrix; This represents the coefficient matrix of the linearized model after the wind turbine is connected, and is similar to that in the classic Heffron-Phillips model. The difference is that a fan is connected to the system.

[0024] Furthermore, the two transfer functions of the excitation control loop in the feedback connection model are specifically as follows:

[0025] ;

[0026] in, This represents the first transfer function of the excitation control loop; This represents the second transfer function of the excitation control loop; Represents the transfer function matrix of the excitation system; This indicates the synchronous speed.

[0027] Furthermore, the open-loop transfer function matrix of the system in the feedback connection model is specifically as follows:

[0028] ;

[0029] in, Represents the open-loop transfer function matrix of the system; Indicates synchronous speed; This represents the first transfer function of the excitation control loop; This represents the second transfer function of the excitation control loop.

[0030] Furthermore, the process of applying the inverse characteristic trajectory method to solve for the stability margin is as follows:

[0031] (1) Substitution We can obtain:

[0032] ;

[0033] in, This represents the angular frequency of the generator; Represents the imaginary number symbol;

[0034] (2) Define the transfer function matrix and as follows:

[0035] ;

[0036] (3) The matrix obtained by multiplying K1 by a diagonal matrix is ​​then subjected to eigenvalue decomposition:

[0037] ;

[0038] in, Let be a real diagonal matrix, and its diagonal elements be... eigenvalues, U is The right eigenvector matrix;

[0039] (4) We can obtain:

[0040] ;

[0041] Among them, matrix Similar to ,use express Then we have:

[0042] ;

[0043] in, Represents the eigenvalues ​​of the matrix within the parentheses;

[0044] (5) Similarity matrix With stability margin It can be represented as:

[0045] ;

[0046] in, Indicates the stability margin of the matrix in parentheses; This represents the smallest eigenvalue of the matrix within the parentheses; This represents a simplified form of a similarity matrix after hiding the independent variables. This represents the simplified form of the open-loop transfer function matrix of the system after hiding the independent variables.

[0047] Furthermore, the process of analyzing the impact of wind power grid connection on the system's open-loop transfer function matrix is ​​as follows:

[0048] The difference in the open-loop transfer function matrix of the system before and after the wind turbine output is increased can be decomposed into two parts: one part is only related to the dynamic changes of the wind turbine, and the other part is only related to the dynamic changes of the synchronous machine whose output is being replaced.

[0049] Assume the frequencies of the system's low-frequency oscillations before and after the wind turbine's output increase are respectively and We can obtain:

[0050] ;

[0051] in, This represents the open-loop transfer function matrix of the system before the replacement; This represents the open-loop transfer function matrix of the system after the replacement; This represents the loop transfer function matrix that relates only to the dynamic changes of the wind turbine; The loop transfer function matrix represents the part of the synchronous machine whose output is being replaced and whose dynamic changes are related.

[0052] Furthermore, the process of analyzing the impact of wind power grid connection on system low-frequency oscillations is as follows:

[0053] By decomposing the open-loop transfer function matrix of the wind turbine connected to the system and altering the power flow into a part that depends only on the wind turbine dynamics and a part that depends only on the power flow changes, we can obtain:

[0054] ;

[0055] Then, the similarity matrix is ​​obtained. Inverse matrix The expression:

[0056] ;

[0057] in, express The loop transfer function matrix is ​​only related to the dynamic changes of the wind turbine. express The loop transfer function matrix of the part of the synchronous machine whose output is being replaced is related to the dynamic changes.

[0058] , , , The transition matrix in the derivation process is defined as follows:

[0059]

[0060]

[0061]

[0062] ;

[0063] This analysis examines the impact of increased turbine output on the stability margin due to dynamic changes in the turbine and the impact of changes in system power flow on the stability margin.

[0064] Secondly, a low-frequency oscillation analysis system for wind power grid connection based on the inverse characteristic trajectory method is provided, including:

[0065] The model reconstruction module is used to build a Heffron-Phillips model that takes into account wind turbine grid connection.

[0066] The model simplification module is used to simplify the Heffron-Phillips model that considers wind turbine grid connection into a feedback connection model that enables the application of the characteristic trajectory method.

[0067] The margin analysis module is used to solve the stability margin based on the feedback connection model and the inverse characteristic trajectory method.

[0068] The grid connection analysis module is used to analyze the impact of wind power grid connection on the system's open-loop transfer function matrix;

[0069] The oscillation analysis module is used to analyze the impact of wind power grid connection on low-frequency oscillations in the system.

[0070] Thirdly, a computer terminal is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the wind power grid-connected low-frequency oscillation analysis method based on the inverse characteristic trajectory method as described in any one of the first aspects.

[0071] Fourthly, a computer-readable medium is provided having a computer program stored thereon, the computer program being executed by a processor to implement the wind power grid-connected low-frequency oscillation analysis method based on the inverse characteristic trajectory method as described in any one of the first aspects.

[0072] Compared with the prior art, the present invention has the following beneficial effects:

[0073] 1. The low-frequency oscillation analysis method for wind power grid connection based on the inverse characteristic trajectory method provided by this invention improves the accuracy of the stability margin approximation value on the basis of the characteristic trajectory method, obtains an inverse similarity matrix and stability margin expression with simple mathematical relationship, and obtains a clear explanation of the influence mechanism of wind turbine access on low-frequency oscillation.

[0074] 2. This invention can decompose the impact of wind turbine connection on low-frequency oscillation into the impact of dynamic wind turbine introduction on low-frequency oscillation and the impact of system power flow changes on low-frequency oscillation, thus explaining the mechanism of wind turbine connection on low-frequency oscillation more clearly.

[0075] 3. This invention utilizes the inverse feature trajectory method to obtain an inverse matrix with a higher degree of diagonal dominance than the original similar matrix, thereby obtaining a stability margin with higher accuracy. Compared with existing methods, the method proposed in this invention is safer, simpler to analyze, and has a more rigorous theoretical basis. Attached Figure Description

[0076] The accompanying drawings, which are included to provide a further understanding of embodiments of the invention and form part of this application, do not constitute a limitation thereof. In the drawings:

[0077] Figure 1 This is a flowchart from Embodiment 1 of the present invention;

[0078] Figure 2 This is a schematic diagram of the feedback connection model in Embodiment 1 of the present invention;

[0079] Figure 3 This is a schematic diagram of the excitation control circuit in Embodiment 1 of the present invention;

[0080] Figure 4 This is a schematic diagram of the increased output of the fan in Embodiment 1 of the present invention;

[0081] Figure 5 This is a system block diagram in Embodiment 2 of the present invention. Detailed Implementation

[0082] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the embodiments and accompanying drawings. The illustrative embodiments and descriptions of the present invention are only used to explain the present invention and are not intended to limit the present invention.

[0083] Example 1: A method for analyzing low-frequency oscillations in wind power grid connection based on the inverse characteristic trajectory method, such as... Figure 1 As shown, it includes the following steps:

[0084] S101: Construct a Heffron-Phillips model that considers wind turbine grid connection;

[0085] S102: The Heffron-Phillips model considering wind turbine grid connection is simplified into a feedback connection model that enables the application of the characteristic trajectory method;

[0086] S103: Based on the feedback connection model, the inverse characteristic trajectory method is applied to solve the stability margin;

[0087] S104: Analyze the impact of wind power grid connection on the system open-loop transfer function matrix;

[0088] S105: Analyze the impact of wind power grid connection on low-frequency oscillations of the system.

[0089] In step S101, based on the traditional Heffron-Phillips model, using the injected power of the wind turbine as the system input signal and the voltage amplitude of the wind turbine connected to the bus as the system output signal, we can obtain:

[0090] Equation (1);

[0091] In the formula, column vector Δω represents the rotational speed of each generator; column vector Δδ represents the angular displacement of each generator rotor relative to the synchronous reference shaft, i.e., the power angle; column vector ΔE' q The cross-axis transient electromotive force of each generator; column vector ΔE fd The output voltage of the automatic voltage regulator; ∆P w and ∆Q w Injecting incremental active and reactive power into the wind turbine; ∆U w The increment of the bus voltage amplitude injected into the wind turbine is s, where s is the generalized frequency.

[0092] A g B g C g D g Let be the system matrix, input matrix, output matrix, and direct transition matrix of the above differential-algebraic equation, respectively, where:

[0093] Equation (2);

[0094] In the formula, the diagonal matrix M contains the inertial constant of the generator rotor motion; the diagonal matrix K D Including rotor motion damping coefficient; diagonal matrix T' d0 Includes the d-axis transient time constant of each generator; K A For excitation gain, T A It is a time constant; For ω to P w The partial derivative coefficient matrix, For ω to Q w The partial derivative coefficient matrix, K PE For E' q For P w The partial derivative coefficient matrix, K QE For E' q Q w The partial derivative coefficient matrix, K Pf For E fd For P w The partial derivative coefficient matrix, K Qf For E fd Q w The partial derivative coefficient matrix, K Vδ For U w The partial derivative coefficient matrix with respect to δ, K VE For Uw For E' q The partial derivative coefficient matrix, K VP For U w For P w The partial derivative coefficient, K VQ For U w Q w The partial derivative coefficients.

[0095] Matrices K1, K2, K3, K4, K5, and K6 are the linearized model coefficient matrices in the classic Heffron-Phillips model, reflecting the network structure, component parameters, operating conditions, and load characteristics, as follows:

[0096] ;

[0097] In the formula, P e E q U t These represent the electromagnetic power, generator electromotive force, and generator terminal voltage amplitude in the classical model, respectively.

[0098] The small-signal model of the wind turbine is:

[0099] Equation (3);

[0100] in, express right The transfer function; express right The transfer function.

[0101] Combining equations (2) and (3), we can obtain the linearized model of the wind turbine after it is connected to the power system, specifically:

[0102] Equation (4);

[0103] In equation (4):

[0104] Equation (5).

[0105] According to formula (2), B g C g and D g The form can be used to derive matrix K WTG (s) takes the following form:

[0106] Equation (6);

[0107] In the formula, K w1 -K w6 The transition matrix in the derivation process:

[0108] Equation (7).

[0109] The system matrix after connecting the wind turbine is as follows:

[0110] Equation (8);

[0111] in, Represents a diagonal matrix containing the inertial constant of the generator rotor; Represents a diagonal matrix containing the rotor motion damping coefficients; This represents the transfer function matrix of the governor-prime mover system; Represents a diagonal matrix containing the d-axis transient time constants of each generator; Represents the time constant; Indicates excitation gain; Represents the PSS transfer function matrix; This represents the coefficient matrix of the linearized model after the wind turbine is connected, and is similar to that in the classic Heffron-Phillips model. The difference is that a fan is connected to the system.

[0112] In equation (8):

[0113] Equation (9);

[0114] By A gw As can be seen from the expression, the prime mover-governor circuit remains unchanged before and after the wind turbine is connected. Therefore, the impact of the prime mover-governor circuit on the system stability margin will no longer be considered in the subsequent analysis.

[0115] This allows us to obtain the Heffron-Phillips model of the power system after the wind turbines are connected to the grid.

[0116] In step S102, the Heffron-Phillips model for wind turbine grid connection is simplified to obtain the following: Figure 2 The feedback connection model shown contains three loops, where and The block diagram is as follows Figure 3 As shown.

[0117] The two transfer functions of the excitation control loop in the feedback connection model are as follows:

[0118] Equation (10);

[0119] in, This represents the first transfer function of the excitation control loop; This represents the second transfer function of the excitation control loop; Represents the transfer function matrix of the excitation system; This indicates the synchronous speed.

[0120] Furthermore, the open-loop transfer function matrix of the system in the feedback connection model is specifically as follows:

[0121] Equation (11);

[0122] in, This represents the open-loop transfer function matrix of the system.

[0123] In step S103, the process of applying the inverse characteristic trajectory method to solve for the stability margin is as follows:

[0124] (1) Substitution We can obtain:

[0125] Equation (12);

[0126] in, This represents the angular frequency of the generator; Represents the imaginary number symbol.

[0127] To obtain analytical expressions for the impact of each control loop on the stability margin, it is necessary to... Make the following transformations. First, due to M and K D Since they are all diagonal matrices, they can be decomposed as follows:

[0128] Equation (13);

[0129] Substituting equation (13) into equation (12), we get:

[0130] Equation (14).

[0131] (2) For ease of analysis, the open-loop transfer functions related to K1 are defined respectively. and the open-loop transfer function of the rest as follows:

[0132] Equation (15);

[0133] Equation (16).

[0134] (3) Since K1 is an approximately symmetric real matrix, it can be diagonalized. Since K1 is the matrix obtained by multiplying it by a diagonal matrix, we can perform eigenvalue decomposition on this matrix:

[0135] Equation (17);

[0136] in, Let be a real diagonal matrix, and its diagonal elements be... eigenvalues, U is The right eigenvector matrix.

[0137] (4) Substituting the above equation into equation (14) yields:

[0138] Equation (18);

[0139] From the above formula, we can see the matrix Similar to ,use express Then we have:

[0140] Equation (19);

[0141] in, This represents the eigenvalues ​​of the matrix within the parentheses.

[0142] (5) Similarity matrix This can be further expressed as: ;

[0143] Then similar matrix With stability margin It can be represented as:

[0144] ;

[0145] in, Indicates the stability margin of the matrix in parentheses; This represents the smallest eigenvalue of the matrix within the parentheses; This represents a simplified form of a similarity matrix after hiding the independent variables. This represents the simplified form of the open-loop transfer function matrix of the system after hiding the independent variables.

[0146] In step S104, the output of the synchronous machine in the original system remains unchanged, only the output of the wind turbine is increased, and an equal amount of load is added to the system to absorb it.

[0147] Figure 4 A schematic diagram illustrating the process of increasing the output of a wind turbine. In the diagram, SG represents a synchronous machine, WTG represents the wind turbine, and P... SG and Q SG P represents the active power and reactive power generated by the synchronous machine, respectively. w and Q w P represents the active power and reactive power generated by the wind turbine, respectively. Total and QTotal These represent the total active power and reactive power of the wind turbine and the synchronous machine, respectively.

[0148] The difference in the open-loop transfer function matrix of the system before and after increasing the wind turbine's output can be decomposed into two parts: one part depends only on the dynamic changes of the wind turbine, and the other part depends only on the dynamic changes of the synchronous machine whose output is being replaced. Assume the frequencies of the system's low-frequency oscillations before and after increasing the wind turbine's output are respectively... and Then the open-loop transfer function matrices of the system before and after the replacement can be expressed as follows: and .

[0149] in The expression is:

[0150] Equation (21);

[0151] and The expression is:

[0152] Equation (22);

[0153] After a series of derivations, we can obtain:

[0154] Equation (23);

[0155] in, and These are the loop transfer function matrices in L″(jω″) that are only related to the dynamic changes of the wind turbine and the loop transfer function matrices that are related to the dynamic changes of the synchronous machine whose output is being replaced, respectively.

[0156] As can be seen from the above equation, the impact of increasing the turbine's output on the system's open-loop transfer function matrix can be decomposed into a part that is only related to the dynamic changes of the synchronous machine that are being replaced and a part that is only related to the dynamic changes of the turbine. The following section will analyze the impact of increasing the turbine's output on the system's stability margin based on this decomposition.

[0157] In step S105, similar to the decomposition method of the open-loop transfer function matrix of the system connected to the wind turbine, the open-loop transfer function matrix of the system after the wind turbine is connected and the power flow is changed can be decomposed into a part that is only related to the dynamics of the wind turbine and a part that is only related to the changes in the power flow. The relationship between the open-loop transfer function matrix L′(jω′) of the system before the wind turbine increases its output and the open-loop transfer function matrix L″(jω″) of the system after the wind turbine increases its output is as follows:

[0158] Equation (24);

[0159] in , S M The loop transfer function matrix is ​​only related to the dynamic changes of the wind turbine and the loop transfer function matrix is ​​only related to the dynamic changes of the synchronous machine whose output is replaced.

[0160] Able to obtain the similarity matrix S M Inverse matrix S M --1 The expression:

[0161] Equation (25);

[0162] in , S M -1 The loop transfer function matrix is ​​only related to the dynamic changes of the wind turbine and the loop transfer function matrix is ​​only related to the dynamic changes of the synchronous machine whose output is replaced.

[0163] , , , The transition matrix in the derivation process is defined as follows:

[0164] Equation (26);

[0165] Since the inverse of a similar matrix is ​​highly diagonally dominant, the reciprocal of its diagonal element furthest from the -1 point can better approximate the system's stability margin. Based on the above formula, we can obtain the impact of increasing turbine output on the stability margin due to dynamic changes in the turbine and the impact of system power flow changes on the stability margin.

[0166] It should be noted that, for ease of description, this invention hides and simplifies the independent variables in some matrices such as similarity matrices, but their meaning remains unchanged.

[0167] For example, using the IEEE 4-machine 11-node system as an example, the inverse characteristic trajectory method is used to analyze the changes in system stability margin at the transmitting and receiving ends of the 4-machine 11-node system and after wind turbines are connected to long-distance transmission lines. and The impact of wind turbines on system stability is as follows: It can be seen that when wind turbines are connected to the sending end of the system and their output is increased, the system's stability margin decreases; conversely, when connected to the receiving end of the system and their output is increased, the system's stability margin increases. When connected to long-distance transmission lines, if the load at the sending end absorbs the wind turbine output, the system's stability margin increases; if the load at the receiving end absorbs the wind turbine output, the system's stability margin decreases. Furthermore, after wind turbines are connected to the system and their output is increased, the impact of power flow changes on system stability is always greater than the impact of dynamic changes in wind turbines on stability.

[0168] Example 2: Wind power grid-connected low-frequency oscillation analysis system based on the inverse characteristic trajectory method. This system is used to implement the wind power grid-connected low-frequency oscillation analysis method based on the inverse characteristic trajectory method described in Example 1, such as... Figure 5 As shown, it includes a model reconstruction module, a model simplification module, a margin analysis module, a grid connection analysis module, and an oscillation analysis module.

[0169] The system includes the following modules: Model Reconstruction Module (for constructing a Heffron-Phillips model considering wind turbine grid connection); Model Simplification Module (for simplifying the Heffron-Phillips model considering wind turbine grid connection into a feedback connection model that allows for the application of the characteristic trajectory method); Margin Analysis Module (for solving the stability margin using the inverse characteristic trajectory method based on the feedback connection model); Grid Connection Analysis Module (for analyzing the impact of wind power grid connection on the system's open-loop transfer function matrix); and Oscillation Analysis Module (for analyzing the impact of wind power grid connection on the system's low-frequency oscillations).

[0170] Working Principle: This invention decomposes the impact of wind turbine access on low-frequency oscillations into the effects of dynamic wind turbine introduction and system power flow changes, thus providing a clearer explanation of the mechanism by which wind turbine access affects low-frequency oscillations. Using the inverse characteristic trajectory method proposed in this invention, an inverse matrix with a higher degree of diagonal dominance than the original similarity matrix can be obtained, resulting in a more accurate stability margin. Compared with existing methods, the method proposed in this invention is safer, simpler to analyze, and has a more rigorous theoretical foundation.

[0171] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0172] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0173] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0174] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0175] The above specific embodiments further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for analyzing low-frequency oscillations in wind power grid connection based on the inverse characteristic trajectory method, characterized by: Includes the following steps: Construct a Heffron-Phillips model that considers wind turbine grid connection; The Heffron-Phillips model considering wind turbine grid connection is simplified into a feedback connection model that enables the application of the characteristic trajectory method; Based on the feedback connection model, the inverse characteristic trajectory method is applied to solve the stability margin. Analyze the impact of wind power grid connection on the system's open-loop transfer function matrix; The impact of wind power grid connection on low-frequency oscillations of the system is analyzed, specifically as follows: The open-loop transfer function matrix of the wind turbine connected to the system and altering the power flow is decomposed into a part that depends only on the wind turbine dynamics and a part that depends only on the power flow changes, resulting in a similarity matrix. Inverse matrix The expression: ； in, express The loop transfer function matrix is ​​only related to the dynamic changes of the wind turbine. express The loop transfer function matrix of the part of the synchronous machine whose output is being replaced is related to the dynamic changes. This analysis examines the impact of increased turbine output on the stability margin due to dynamic changes in the turbine and the impact of changes in system power flow on the stability margin. Define the transfer function matrix : ； in, Let be a real diagonal matrix, and its diagonal elements be... eigenvalues, U is The right eigenvector matrix; M represents the diagonal matrix containing the generator rotor's inertial constant; K D This represents a diagonal matrix containing the rotor motion damping coefficient; ω0 represents the synchronous speed; ω represents the generator's angular frequency; j represents the imaginary number sign; Matrix K1 is the linearized model coefficient matrix in the classic Heffron-Phillips model, expressed as: ； In the formula, This refers to electromagnetic power in the classical model. Since the inverse of a similar matrix is ​​highly diagonally dominant, the stability margin of the system can be better approximated by using the reciprocal of the diagonal element furthest from the −1 point.

2. The method for analyzing low-frequency oscillations in wind power grid connection based on the inverse characteristic trajectory method according to claim 1, characterized in that, The process of constructing the Heffron-Phillips model that considers wind turbine grid connection is as follows: Based on the traditional Heffron-Phillips model, the injected power of the wind turbine is used as the input signal of the system, and the voltage amplitude of the wind turbine connected to the bus is used as the output signal of the system. The small-signal model of the wind turbine is: ； in, This indicates the increment of active power injected into the wind turbine; This indicates the increment of reactive power injected into the wind turbine; This indicates the increment of the voltage amplitude injected into the bus by the fan; express right The transfer function; express right The transfer function; The linearized model of the wind turbine after it is connected to the power system is as follows: ； in, Represents generalized frequency; This represents the angular displacement of each generator rotor relative to the synchronous reference shaft, i.e., the power angle; Indicates the rotational speed of each generator; This represents the cross-axis transient electromotive force of each generator; This indicates the output voltage of the automatic voltage regulator; This represents the system matrix in the classic Heffron-Phillips model; This represents the intermediate matrix determined by the input matrix, output matrix, and direct transition matrix in the classic Heffron-Phillips model; This represents the system matrix after the wind turbine is connected; The system matrix after connecting the wind turbine is as follows: ； in, Represents a diagonal matrix containing the inertial constant of the generator rotor; Represents a diagonal matrix containing the rotor motion damping coefficients; This represents the transfer function matrix of the governor-prime mover system; Represents a diagonal matrix containing the d-axis transient time constants of each generator; Represents the time constant; Indicates excitation gain; Represents the PSS transfer function matrix; This represents the coefficient matrix of the linearized model after the wind turbine is connected, and is similar to that in the classic Heffron-Phillips model. The difference is that a fan is connected to the system.

3. The wind power grid-connected low-frequency oscillation analysis method based on the inverse characteristic trajectory method according to claim 2, characterized in that, The two transfer functions of the excitation control loop in the feedback connection model are as follows: ； in, This represents the first transfer function of the excitation control loop; This represents the second transfer function of the excitation control loop; Represents the transfer function matrix of the excitation system; This indicates the synchronous speed.

4. The method for analyzing low-frequency oscillations in wind power grid connection based on the inverse characteristic trajectory method according to claim 2, characterized in that, The open-loop transfer function matrix of the system in the feedback connection model is specifically as follows: ； in, Represents the open-loop transfer function matrix of the system; Indicates synchronous speed; This represents the first transfer function of the excitation control loop; This represents the second transfer function of the excitation control loop.

5. The wind power grid-connected low-frequency oscillation analysis method based on the inverse characteristic trajectory method according to claim 4, characterized in that, The process of applying the inverse feature trajectory method to solve for the stability margin is as follows: (1) Substitution We can obtain: ； in, This represents the angular frequency of the generator; Represents the imaginary number symbol; (2) Define the transfer function matrix and as follows: ； (3) The matrix obtained by multiplying K1 by a diagonal matrix is ​​then subjected to eigenvalue decomposition: ； in, Let be a real diagonal matrix, and its diagonal elements be... eigenvalues, U is The right eigenvector matrix; (4) We can obtain: ； Among them, matrix Similar to ,use express Then we have: ； in, Represents the eigenvalues ​​of the matrix within the brackets; (5) Similarity matrix With stability margin It can be represented as: ； in, Indicates the stability margin of the matrix in parentheses; This represents the smallest eigenvalue of the matrix within the parentheses; This represents a simplified form of a similarity matrix after hiding the independent variables. This represents the simplified form of the open-loop transfer function matrix of the system after hiding the independent variables.

6. The wind power grid-connected low-frequency oscillation analysis method based on the inverse characteristic trajectory method according to claim 5, characterized in that, The process of analyzing the impact of wind power grid connection on the system's open-loop transfer function matrix is ​​as follows: The difference in the open-loop transfer function matrix of the system before and after the wind turbine output is increased can be decomposed into two parts: one part is only related to the dynamic changes of the wind turbine, and the other part is only related to the dynamic changes of the synchronous machine whose output is being replaced. Assume the frequencies of the system's low-frequency oscillations before and after the wind turbine's output increase are respectively and We can obtain: ； in, This represents the open-loop transfer function matrix of the system before the replacement; This represents the open-loop transfer function matrix of the system after the replacement; This represents the loop transfer function matrix that relates only to the dynamic changes of the wind turbine; The loop transfer function matrix represents the part of the synchronous machine whose output is being replaced and whose dynamic changes are related.

7. The method for analyzing low-frequency oscillations in wind power grid connection based on the inverse characteristic trajectory method according to claim 6, characterized in that, Its characteristics are, The process of analyzing the impact of wind power grid connection on low-frequency oscillations of the system also includes: The correlation matrix in the expression of the inverse of the similarity matrix satisfies: ； and , , , The transition matrix in the derivation process is defined as follows: 。 8. A wind power grid-connected low-frequency oscillation analysis system based on the inverse characteristic trajectory method, used to implement the wind power grid-connected low-frequency oscillation analysis method based on the inverse characteristic trajectory method as described in any one of claims 1-7, characterized in that, include: The model reconstruction module is used to build a Heffron-Phillips model that takes into account wind turbine grid connection. The model simplification module is used to simplify the Heffron-Phillips model that considers wind turbine grid connection into a feedback connection model that enables the application of the characteristic trajectory method. The margin analysis module is used to solve the stability margin based on the feedback connection model and the inverse characteristic trajectory method. The grid connection analysis module is used to analyze the impact of wind power grid connection on the system's open-loop transfer function matrix; The oscillation analysis module is used to analyze the impact of wind power grid connection on low-frequency oscillations in the system.

9. A computer terminal 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, it implements the wind power grid-connected low-frequency oscillation analysis method based on the inverse characteristic trajectory method as described in any one of claims 1-7.

10. A computer-readable medium having a computer program stored thereon, characterized in that, The computer program, when executed by a processor, can implement the wind power grid-connected low-frequency oscillation analysis method based on the inverse characteristic trajectory method as described in any one of claims 1-7.

Images