A parameter setting method and device of a wind farm and a computer device

Abstract

The application provides a wind farm parameter setting method, device and computer equipment. The method comprises the following steps: obtaining a full-order linearization state space model of a grid-connected double-fed wind farm based on a state space model of each double-fed wind turbine of the grid-connected double-fed wind farm; performing dynamic equivalent transformation on the full-order linearization state space model of the grid-connected double-fed wind farm to obtain a plurality of mutually independent subsystem models of the grid-connected double-fed wind farm; obtaining a characteristic equation corresponding to the grid-connected double-fed wind farm based on the plurality of mutually independent subsystem models of the grid-connected double-fed wind farm; and obtaining a setting result of a preset parameter of the grid-connected double-fed wind farm based on the characteristic equation corresponding to the grid-connected double-fed wind farm and the setting of the preset parameter. The device is used for executing the above method. The wind farm parameter setting method, device and computer equipment provided by the embodiment of the application reduce the overall operation and maintenance cost.

Description

Technical Field

[0001] This invention relates to the field of new energy technology, specifically to a method, apparatus, and computer equipment for parameter tuning of a wind farm. Background Technology

[0002] With the continuous growth of global energy demand, wind power, as an important clean energy source, has been widely used and rapidly developed worldwide. Doubly fed wind turbines, due to their high efficiency and flexible adjustment capabilities, have gradually become the mainstream choice for wind farms. These units connect the stator windings directly to the grid, while the rotor windings are coordinated with the grid through a frequency converter, enabling flexible adjustment of power generation.

[0003] Doubly fed induction generator (DFIG) wind turbines often face dynamic stability issues caused by various factors (such as system parameters, network topology, and control strategies) during actual operation, particularly in the design and parameter tuning of current control strategies. During grid connection, the converter control strategy and its dynamic characteristics play a crucial role in system stability, especially under weak connection conditions. Typically, to simplify the analysis of system dynamic characteristics and key influencing factors, the dynamic problems caused by wind power grid connection systems are divided into multiple levels, including AC current control time scale, DC voltage control time scale, and electromechanical control time scale. Although existing research has provided preliminary analysis of the dynamic characteristics of direct-drive wind turbines under the AC current time scale, analysis of parameter tuning for DFIG wind turbines remains relatively scarce in practical applications. Summary of the Invention

[0004] To address the problems in the prior art, embodiments of the present invention provide a method, apparatus, and computer equipment for wind farm parameter tuning, which can at least partially solve the problems existing in the prior art.

[0005] In a first aspect, the present invention proposes a method for parameter tuning of a wind farm, comprising:

[0006] Based on the state-space model of each doubly fed wind turbine in the grid-connected doubly fed wind farm, the full-order linearized state-space model of the grid-connected doubly fed wind farm is obtained.

[0007] A dynamic equivalent transformation is performed on the full-order linearized state-space model of the grid-connected doubly-fed wind farm to obtain multiple independent subsystem models of the grid-connected doubly-fed wind farm.

[0008] Based on the model of multiple independent subsystems of the grid-connected doubly fed wind farm, the characteristic equation corresponding to the grid-connected doubly fed wind farm is obtained.

[0009] Based on the characteristic equation corresponding to the grid-connected doubly-fed wind farm, the preset parameters of the grid-connected doubly-fed wind farm are tuned to obtain the tuning result of the preset parameters of the grid-connected doubly-fed wind farm.

[0010] Furthermore, the full-order linearized state-space model of the grid-connected doubly-fed wind farm is as follows:

[0011]

[0012] in, Let ΔX be the column vector of state variables for a grid-connected doubly-fed induction generator (DFIG) wind farm. k Let A be the column vector of state variables for the k-th doubly-fed wind turbine. DFIG Let A be the state-space system matrix. DFIG =diag(A k )+diag(B k )X G diag(C k ), diag(A k ), diag(B k ) and diag(C k ) respectively represent A k B k and C k (k = 1, 2, ..., N) is a block diagonal matrix with diagonal elements, A k Let B be the system matrix in the full-order localized state-space model of the k-th doubly-fed wind turbine line. k Let C be the input matrix in the fully localized state-space model of the k-th doubly-fed wind turbine line. k This is the output matrix in the fully localized state-space model of the k-th doubly-fed wind turbine line. X gr For the network reactance matrix of a grid-connected doubly-fed wind farm, s is the Laplace operator, ω0 is the power frequency of the grid under steady state, k is a positive integer, and k is greater than or equal to 1 and less than or equal to N, and N is the total number of doubly fed wind turbines in the grid-connected doubly fed wind farm.

[0013] Furthermore, the subsystem model of the grid-connected doubly-fed wind farm is as follows:

[0014]

[0015] Where, ΔY k Let A be the state variable of the k-th equivalent subsystem. Yk Let be the system matrix of the k-th equivalent subsystem. E n λ is an n-order identity matrix; ω0 is the power frequency of the power grid under steady-state conditions; k A represents the eigenvalues ​​of the impedance matrix. cB is the state matrix for a single wind turbine. c For a single wind turbine, the input matrix is ​​C. c This is the output matrix for a single wind turbine; k = 1, 2, ..., N; N is the number of wind turbines in the wind farm.

[0016] Furthermore, the characteristic equation corresponding to the grid-connected doubly-fed wind farm is:

[0017] a2s 2 +a1s+a0=0

[0018] Where a0, a1, and a2 are the coefficients in the characteristic equation. K ip V0 is the phase-locked loop integral coefficient; Q0 is the steady-state voltage at the grid connection point; K is the steady-state reactive power value; p ω0 is the proportional gain of the phase-locked loop; ω0 is the power frequency of the grid under steady-state conditions; P0 is the steady-state value of active power; X ss For the stator winding self-inductance; η max This is the largest eigenvalue of the impedance matrix of a doubly fed wind farm.

[0019] Furthermore, the preset parameters include the maximum eigenvalue of the impedance matrix of the doubly-fed wind farm and / or the active power of the doubly-fed wind farm.

[0020] Secondly, the present invention provides a parameter tuning device for a wind farm, comprising:

[0021] The first acquisition module is used to obtain the full-order linearized state-space model of the grid-connected doubly-fed wind farm based on the state-space model of each doubly-fed wind turbine in the grid-connected doubly-fed wind farm.

[0022] The transformation module is used to perform dynamic equivalent transformation on the full-order linearized state-space model of the grid-connected doubly fed wind farm to obtain multiple independent subsystem models of the grid-connected doubly fed wind farm.

[0023] The second obtaining module is used to obtain the characteristic equations corresponding to the grid-connected doubly fed wind farm based on multiple independent subsystem models of the grid-connected doubly fed wind farm.

[0024] The third obtaining module is used to adjust the preset parameters of the grid-connected doubly-fed wind farm based on the characteristic equation corresponding to the grid-connected doubly-fed wind farm, and obtain the tuning result of the preset parameters of the grid-connected doubly-fed wind farm.

[0025] Furthermore, the full-order linearized state-space model of the grid-connected doubly-fed wind farm is as follows:

[0026]

[0027] in, Let ΔX be the column vector of state variables for a grid-connected doubly-fed induction generator (DFIG) wind farm. k Let A be the column vector of state variables for the k-th doubly-fed wind turbine. DFIG Let A be the state-space system matrix. DFIG =diag(A k )+diag(B k )X G diag(C k ), diag(A k ), diag(B k ) and diag(C k ) respectively represent A k B k and C k (k = 1, 2, ..., N) is a block diagonal matrix with diagonal elements, A k Let B be the system matrix in the full-order localized state-space model of the k-th doubly-fed wind turbine line. k Let C be the input matrix in the fully localized state-space model of the k-th doubly-fed wind turbine line. k This is the output matrix in the fully localized state-space model of the k-th doubly-fed wind turbine line. X gr For the network reactance matrix of a grid-connected doubly-fed wind farm, s is the Laplace operator, ω0 is the power frequency of the grid under steady state, k is a positive integer, and k is greater than or equal to 1 and less than or equal to N, and N is the total number of doubly fed wind turbines in the grid-connected doubly fed wind farm.

[0028] Furthermore, the subsystem model of the grid-connected doubly-fed wind farm is as follows:

[0029]

[0030] Where, ΔY k Let A be the state variable of the k-th equivalent subsystem. Yk Let be the system matrix of the k-th equivalent subsystem. E n λ is an n-order identity matrix; ω0 is the power frequency of the power grid under steady-state conditions; k A represents the eigenvalues ​​of the impedance matrix. c B is the state matrix for a single wind turbine. c For a single wind turbine, the input matrix is ​​C. c This is the output matrix for a single wind turbine; k = 1, 2, ..., N; N is the number of wind turbines in the wind farm.

[0031] Furthermore, the characteristic equation corresponding to the grid-connected doubly-fed wind farm is:

[0032] a2s2 +a1s+a0=0

[0033] Where a0, a1, and a2 are the coefficients in the characteristic equation. K ip V0 is the phase-locked loop integral coefficient; Q0 is the grid connection point voltage; K is the reactive power; p ω0 is the proportional gain of the phase-locked loop; ω0 is the power frequency of the grid under steady-state conditions; P0 is the active power; X0 ss For the stator winding self-inductance; η max This is the largest eigenvalue of the impedance matrix of a doubly fed wind farm.

[0034] Furthermore, the preset parameters include the maximum eigenvalue of the impedance matrix of the doubly-fed wind farm and / or the active power of the doubly-fed wind farm.

[0035] Thirdly, the present invention provides a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the program to implement the parameter tuning method for wind farms described in any of the above embodiments.

[0036] Fourthly, the present invention provides a computer-readable storage medium storing a computer program / instructions that, when executed by a processor, implement the parameter tuning method for a wind farm as described in any of the above embodiments.

[0037] Fifthly, the present invention provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the parameter tuning method for a wind farm as described in any of the above embodiments.

[0038] The wind farm parameter tuning method, apparatus, and computer equipment provided in this invention can obtain a full-order linearized state-space model of the grid-connected doubly-fed induction generator (DFIG) wind farm based on the state-space model of each DFIG turbine; perform dynamic equivalent transformation on the full-order linearized state-space model of the grid-connected DFIG wind farm to obtain multiple independent subsystem models of the grid-connected DFIG wind farm; obtain the characteristic equation corresponding to the grid-connected DFIG wind farm based on the multiple independent subsystem models of the grid-connected DFIG wind farm; and tune the preset parameters of the grid-connected DFIG wind farm based on the characteristic equation corresponding to the grid-connected DFIG wind farm to obtain the tuning result of the preset parameters of the grid-connected DFIG wind farm. This method is applicable to the practical application of large-scale DFIG wind farms and provides an effective solution for adjusting control strategies during design and actual operation. By optimizing control parameters, it improves system stability and reduces overall operation and maintenance costs. Attached Figure Description

[0039] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings:

[0040] Figure 1 This is a flowchart illustrating the parameter tuning method for a wind farm provided in the first embodiment of the present invention.

[0041] Figure 2 This is a schematic diagram of the grid-connected system structure of a doubly fed wind farm provided in the second embodiment of the present invention.

[0042] Figure 3 This is a schematic diagram of the equivalent subsystem provided in the third embodiment of the present invention.

[0043] Figure 4 This is a schematic diagram of the inner loop control of the rotor-side converter of a doubly fed wind turbine provided in the fourth embodiment of the present invention.

[0044] Figure 5 This is a schematic diagram of the control of the grid-side converter of the doubly fed wind turbine provided in the fifth embodiment of the present invention.

[0045] Figure 6 This is a schematic diagram of the relative positions between the dq coordinate system and the xy coordinate system provided in the sixth embodiment of the present invention.

[0046] Figure 7 This is a schematic diagram of the working principle of the phase-locked loop provided in the seventh embodiment of the present invention.

[0047] Figure 8 This is a schematic diagram of the nonlinear simulation results of Embodiment 1 provided in the eighth embodiment of the present invention.

[0048] Figure 9 This is a schematic diagram of the nonlinear simulation results of Embodiment 2 provided in the ninth embodiment of the present invention.

[0049] Figure 10 This is a schematic diagram of the structure of the parameter setting device for a wind farm provided in the tenth embodiment of the present invention.

[0050] Figure 11 This is a schematic diagram of the physical structure of the computer device provided in the eleventh embodiment of the present invention. Detailed Implementation

[0051] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. Here, the illustrative embodiments and their descriptions are used to explain the present invention, but are not intended to limit the present invention. It should be noted that, unless otherwise specified, the embodiments and features in the embodiments of this application can be arbitrarily combined with each other. The acquisition, storage, use, and processing of data in the technical solutions of this application all comply with relevant laws and regulations. The user information in the embodiments of this application is obtained through legal and compliant means, and the acquisition, storage, use, and processing of user information have been authorized and agreed upon by the customer.

[0052] To facilitate understanding of the technical solution provided in this application, the relevant content of the technical solution in this application will be explained below.

[0053] Doubly fed induction generator (DFIG) wind turbines often face dynamic stability problems caused by various factors during actual operation, especially in the design and parameter tuning of current control strategies. Model analysis studies have revealed that the small-disturbance stability of the turbine decreases significantly with decreasing system connection strength. Further research on the interaction of control loops has shown that the interaction between AC current control and the dynamic characteristics of the phase-locked loop (PLL) may exacerbate system instability. Further model analysis and impedance analysis reveal that the stability of DFIG wind turbines is closely related to system configuration, the number of DFIGs, and their connection to the grid. Specifically, when the bandwidth of the PLL is similar to that of the AC current control loop, the coupling between the two is a significant factor leading to system instability. Existing research focuses on the impact of PLL models on the stability of DFIG wind turbines. Although several studies have indicated that the stability of DFIG wind power systems is closely related to the dynamic characteristics of the PLL, a comprehensive understanding of its interaction and stability mechanisms under different conditions remains insufficient.

[0054] Existing research largely focuses on analyses of a few wind turbine units, failing to adequately consider the stability of large-scale wind farm grid-connected systems. Typically, to simplify the analysis of system dynamics and key influencing factors, the dynamic problems arising from wind power grid-connected systems are divided into multiple levels, including AC current control timescale, DC voltage control timescale, and electromechanical control timescale. Since the bandwidth of the current control inner loop is usually tens of times larger than that of the power control outer loop, the dynamic response speed of the inner loop is much faster than that of the outer loop. Therefore, the stability problem of the current control inner loop under the AC current timescale can be discussed separately from the stability problem of the power control outer loop under the DC voltage timescale. Consequently, a systematic and flexible parameter tuning method is urgently needed to ensure the stability of doubly-fed induction generator (DFIG) wind farms under different operating conditions.

[0055] While existing research has provided preliminary analyses of the dynamic characteristics of direct-drive wind turbines on the AC current timescale, reduced-order modeling and analysis methods for doubly-fed induction generator (DFIG) wind turbines remain scarce in practical applications, especially regarding the dynamic problems of DFIGs connected to the grid. Therefore, there is an urgent need to provide a comprehensive analytical framework and parameter tuning strategies through deeper theoretical exploration and model optimization, thereby effectively ensuring the system stability of DFIG wind turbines under various operating conditions, particularly under weak grid connections and heavy loads.

[0056] Figure 1 This is a flowchart illustrating the parameter tuning method for a wind farm provided in the first embodiment of the present invention, as shown below. Figure 1 As shown, the wind farm parameter tuning method provided in this embodiment of the invention includes:

[0057] S101. Based on the state-space model of each doubly fed wind turbine in the grid-connected doubly fed wind farm, obtain the full-order linearized state-space model of the grid-connected doubly fed wind farm.

[0058] Specifically, a grid-connected doubly-fed induction generator (DFIG) wind farm includes multiple DFIG wind turbines, each with a corresponding state-space model. Based on the state-space models of each DFIG wind turbine in the grid-connected DFIG wind farm, a full-order linearized state-space model of the entire grid-connected DFIG wind farm can be obtained.

[0059] For example, such as Figure 2 As shown, the doubly-fed induction generator (DFIG) wind farm comprises M branches, each branch containing multiple DFIG wind turbines. Each DFIG wind turbine uses a DFIG induction generator to generate wind power. The DFIG wind farm is connected to the busbar B via the M branches, and the external power system is connected to the busbar B through port A of the DFIG wind farm. i M represents the number of doubly fed wind turbines in the i-th branch, where i is a natural number, and M represents the total number of branches included in the doubly fed wind farm.

[0060] exist Figure 2 The grid-connected system structure of the doubly-fed induction generator (DFIG) wind farm shown is represented by the state-space model of the k-th DFIG turbine as follows:

[0061]

[0062] Among them, X k Let X be the column vector of state variables for the k-th doubly-fed wind turbine. k =[ΔI nd ΔI nq ΔV dc Δx1Δx2Δx3Δx4] T , where ΔI nd Let ΔI be the d-axis current. nq Let ΔV be the q-axis current. dcFor DC voltage, Δx1 represents the d-axis state of the inner ring of the rotor-side converter, Δx2 represents the q-axis state of the inner ring of the rotor-side converter, Δx3 represents the d-axis state of the inner ring of the grid-side converter, and Δx4 represents the q-axis state of the inner ring of the grid-side converter. A k Let B be the system matrix in the linearized state-space model of the k-th doubly-fed wind turbine. k Let C be the input matrix in the linearized state-space model of the k-th doubly-fed wind turbine. k Let I be the output matrix in the linearized state-space model of the k-th doubly-fed wind turbine. k =[I kx I ky ] T U represents the output current vector at the grid connection point of the k-th wind turbine in the common xy coordinate system. k =[U kx U ky ] T Let Δ represent the output current and voltage vectors at the grid connection point of the k-th wind turbine in the common xy coordinate system, where Δ represents the increment of the corresponding phasor.

[0063] Assuming the k-th doubly-fed wind turbine is located on the j-th branch of the doubly-fed wind farm, according to Figure 2 The voltage equation for the branch containing the k-th doubly-fed wind turbine, as shown in the grid-connected system structure, can be obtained as follows:

[0064]

[0065] Where, x k Let I be the line impedance of the kth wind turbine. lkx Let I be the x-axis current at the grid connection point of the kth wind turbine. lky U is the y-axis current at the grid connection point of the k-th wind turbine, ω0 is the power frequency of the grid under steady-state conditions, and U k =[U kx U ky ] T Let be the voltage at the grid connection point of the k-th doubly-fed wind turbine.

[0066] By further deriving equation (2), the relationship between voltage and current can be expressed using the Laplace operator and the identity matrix, resulting in:

[0067]

[0068] Where s is the Laplace operator, E2 is the identity matrix, and I lk Let be the grid connection current of the kth wind turbine.

[0069] From this, the network impedance matrix equation of a doubly-fed wind farm can be derived as follows:

[0070] ΔU=X G ΔI (4)

[0071] in, The voltage column vector of each node in a doubly-fed wind farm Let be the column vector of currents at each node of the doubly-fed wind farm, and we have:

[0072]

[0073] in, Let be the transformation matrix.

[0074] Therefore, the network reactance matrix of a grid-connected doubly-fed wind farm can be further defined as follows:

[0075]

[0076] Based on equations (1) to (6), the dynamic characteristic model of a grid-connected doubly-fed wind farm can be obtained as follows:

[0077]

[0078] Equation (7) represents Figure 2 The diagram shows a fully linearized state-space model of a grid-connected doubly-fed wind farm. In the model, A... DFIG For the state-space system matrix, Let A be the column vector of state variables of a grid-connected doubly-fed induction generator (DFIG) wind farm, and let A be the column vector of state variables. DFIG =diag(A k )+diag(B k )X G diag(C k ), diag(A k ) indicates that A k For a block diagonal matrix with diagonal elements, diag(B) k ) indicates that B k For a block diagonal matrix with diagonal elements, diag(C k ) indicates that C k It is a block diagonal matrix with diagonal elements (k = 1, 2, ..., N).

[0079] S102. Perform dynamic equivalent transformation on the full-order linearized state-space model of the grid-connected doubly-fed wind farm to obtain multiple independent subsystem models of the grid-connected doubly-fed wind farm.

[0080] Specifically, based on the full-order linearized state-space model of the grid-connected doubly-fed wind farm, the dynamic characteristic differences between the individual doubly-fed wind turbines in the grid-connected doubly-fed wind farm are ignored, and the full-order linearized state-space model of the grid-connected doubly-fed wind farm is dynamically equivalent to a subsystem model of multiple independent doubly-fed wind turbines.

[0081] By converting the full-order linearization model of a grid-connected doubly-fed wind farm into multiple independent subsystem models, the complex high-order wind farm model is decomposed into multiple low-order subsystem models, and the two maintain consistency in dynamic characteristics. This not only simplifies the system modeling process but also significantly reduces the amount of computation, thereby greatly simplifying the complexity and computation of stability analysis for large-scale grid-connected wind farms.

[0082] In actual wind farm operation, wind turbines in the same grid-connected system are usually of the same model, and their operating parameters and control settings are often very similar. Although the uneven distribution of wind speed may cause some differences in the steady-state operating points of each wind turbine, these differences usually do not significantly affect the linearization model of the system. Therefore, it can be assumed that the dynamic characteristics of all wind turbines are approximately the same. Based on this assumption, it is assumed that the dynamic characteristics of all doubly-fed induction generators (DFIGs) in a grid-connected DFIG wind farm are the same, i.e., differences in the linearization models between DFIG turbine units are not considered. From this, we can conclude:

[0083] A k =A c B k =B c C k =C c k = 1, 2, ..., N (8)

[0084] Substituting equation (8) into equation (7), we can obtain:

[0085]

[0086] in, It is a second-order identity matrix.

[0087] Let λ k (k = 1, 2, ..., N) represents the network reactance matrix X of the grid-connected doubly fed wind farm. gr If the eigenvalues ​​are such that there exists a matrix Q such that:

[0088]

[0089] In equation (10), diag(λ) k ) represents λ k (k = 1, 2, ..., N) is a diagonal matrix with elements on the main diagonal.

[0090] make

[0091]

[0092] Define the similarity transformation matrix as:

[0093]

[0094] In equation (12), n is the order of a single doubly fed wind turbine, and E n It is an n-order identity matrix.

[0095] From equations (10) to (12), we can obtain:

[0096]

[0097] Perform equivalent transformation ΔX DFIG =Q fc ΔY DFIG Combining equations (7) and (8), we can obtain:

[0098] sΔY DFIG =Q fc -1 diag(A c )Q fc ΔY DFIG +Q fc -1 diag(B c )X G diag(C c )Q fc ΔY DFIG (14)

[0099] From equations (12) and (14), we can obtain:

[0100] Q fc -1 diag(A c )Q fc =diag(A c (15)

[0101] From equations (12), (13), and (14), we can obtain:

[0102]

[0103] From equations (15) and (16), we have:

[0104] Q fc -1 A c Q fc =A pd (17)

[0105] In equation (17),

[0106] According to formula (17), matrix A pd With matrix A DFIGSince they are similar matrices, their eigenvalues ​​are identical, and the systems they describe exhibit consistent dynamic behavior. (By A) pd From the expression, it can be seen that the original grid-connected doubly-fed induction generator (DFIG) wind farm can be equivalently represented as N independent subsystems, both of which have consistent dynamic characteristics. Assume the k-th equivalent subsystem model of the grid-connected DFIG wind farm can be expressed as:

[0107]

[0108] Where, ΔY k Let A be the state variable of the k-th equivalent subsystem. Yk Let be the system matrix of the k-th equivalent subsystem. E n λ is an n-order identity matrix; ω0 is the power frequency of the power grid under steady-state conditions; k A represents the eigenvalues ​​of the impedance matrix. c B is the state matrix for a single wind turbine. c For a single wind turbine, the input matrix is ​​C. c This is the output matrix for a single wind turbine; k = 1, 2, ..., N; N is the number of wind turbines in the wind farm.

[0109] For the equivalent subsystem, the established characteristic equations take into account the influence of the dynamic characteristics of the AC current over time, revealing more intuitively and clearly the influencing factors and mechanisms of the AC current control loop on the small-disturbance stability of the doubly fed electric field grid-connected system, providing more precise guidance for the optimization of wind farm control parameters.

[0110] Equation (18) describes Figure 1 Equivalent subsystem model of a grid-connected doubly-fed induction generator (DFIG) wind farm. According to equation (18), the k-th equivalent subsystem can be regarded as a DFIG wind turbine generator with reactance λ. k The power transmission line is connected to port A, such as... Figure 3 As shown. Figure 3 Medium:U DFIG For the grid connection point voltage of the doubly-fed generator unit, I ac U is the output current phasor of the doubly-fed generator unit. A This is the grid connection point voltage at port A of the doubly fed wind farm.

[0111] S103. Based on the multiple independent subsystem models of the grid-connected doubly fed wind farm, obtain the characteristic equations corresponding to the grid-connected doubly fed wind farm.

[0112] Specifically, in the operation of a grid-connected doubly-fed induction generator (DFIG) wind farm, AC current control plays a crucial role in the system's dynamic characteristics, directly affecting the stability and overall performance of the wind farm. Under the AC current timescale, the system's dynamic response is closely related to the control strategy. Therefore, by analyzing the key control mechanisms of the DFIG wind turbine and its network connectivity characteristics, the characteristic equations of the equivalent subsystem can be derived, thereby revealing the dynamic behavior of the wind farm under small disturbance conditions. The characteristic equations corresponding to the grid-connected DFIG wind farm can be obtained based on multiple independent subsystem models of the aforementioned grid-connected DFIG wind farm.

[0113] A dynamic model of the doubly-fed induction generator (DFIG) wind turbine under the AC time scale is established, specifically including the grid-side converter inner loop control, the rotor-side converter inner loop control, the phase-locked loop, and the line model, to analyze the stability of the DFIG wind farm under the AC current time scale.

[0114] The inner-loop control of the rotor-side converter of a doubly-fed induction generator (DFIG) mainly consists of a series of dynamic and algebraic equations, describing the regulation and feedback mechanism of the rotor-side current. The control block diagram is shown below. Figure 4 As shown. The dynamic and algebraic equations for rotor-side control are as follows:

[0115]

[0116]

[0117] In the formula: x1 and x2 are intermediate variables, representing the output of the rotor-side converter inner loop control integral controller; K i_ird and K i_irq I represents the integral coefficient of the inner loop control of the machine-side converter; rq I is the q-axis current of the rotor-side converter. rd I is the d-axis current of the rotor-side converter. rqref This is the reference value for the q-axis current of the rotor-side converter; I rdref X is the reference value for the d-axis current of the rotor-side converter; m The mutual inductance between the stator and rotor windings; X ss For stator winding self-inductance; X rr For rotor winding self-inductance; I sqref I is the reference value for the q-axis current in the stator voltage equation; sdref V is the reference value for the d-axis current in the stator voltage equation. sq K represents the q-axis grid connection point voltage. p_irq and K p_ird V is the proportional gain of the control loop of the machine-side converter; rdref V is the d-axis component of the output voltage of the rotor-side converter. rqref Let V be the q-axis component of the rotor-side converter output voltage; the converter uses an average model, which can be approximated as V.rdref =V rd V rqref =V rq .

[0118] The power control of the stator-side converter involves the regulation of active and reactive power, and its expression is:

[0119]

[0120] Among them, P s For stator-side output active power; V sd I is the stator d-axis voltage; sd V is the d-axis current on the stator side. sq I is the stator q-axis voltage; sq Q is the q-axis current on the stator side. s It outputs reactive power to the stator side.

[0121] Grid-side converter control system, such as Figure 5 As shown, the dynamic equations included in its inner-loop control are:

[0122]

[0123] Where x3 and x4 are intermediate state variables of the inner loop proportional-integral stage; K i_nq and K i_nd K represents the integral coefficient of the inner loop control loop of the grid-side converter; p_vdc The proportional coefficient for the DC voltage outer loop control; ΔV vdc =V vdc -V vdcref V dcref This is the reference value for the DC capacitor voltage; I nd I represents the d-axis current component of the grid-side converter. nq This represents the q-axis current component of the grid-side converter.

[0124] The voltage regulation and filter reactance regulation equations for the grid-side converter are as follows:

[0125]

[0126] Among them, V nqref K is the reference value for the q-axis voltage of the grid-side converter. p_vdc K is the proportional-integral multiple of the DC voltage outer loop; p_nq The proportional multiple of the q-axis proportional-integral element of the inner loop controller; I nd I represents the d-axis current component of the grid-side converter. nq V represents the q-axis current component of the grid-side converter. vdc V is the DC capacitor voltage; vdcref K is the reference value for DC capacitor voltage.p_nd X is the proportional multiple of the d-axis proportional-integral element of the inner loop controller; f V represents the filter reactance; nd V represents the d-axis component of the voltage at the grid connection point. nq I represents the q-axis component of the grid-connected voltage corresponding to the grid-side converter. nd I represents the d-axis current component of the grid-side converter. nq V represents the q-axis current component of the grid-side converter. sq V is the stator q-axis voltage; sd V is the stator d-axis voltage; ndref This is the reference value for the d-axis voltage at the grid connection point of the grid-side converter; I ndref ω0 is the reference value of the d-axis current at the grid connection point of the grid-side converter; ω0 is the power frequency of the grid under steady-state conditions.

[0127] The power equation for the DC capacitor and the output power of the grid-side converter are expressed as follows:

[0128]

[0129] P dc =V nd I nd +V nq I nq (25)

[0130] Where: V dc P is the DC bus voltage; C is the DC capacitor; P is the DC bus voltage. n P represents the active power input from the DC side to the grid-side converter. m P represents the active power from the machine-side converter to the DC side. dc This refers to the active power injected by the grid-side converter into the DC capacitor.

[0131] To simplify the analysis model, equations (19) to (25) are combined, and the dynamic characteristics of the outer rings of the rotor-side and grid-side converters are ignored. The state variables of the rotor-side and grid-side outer rings are simplified to approach zero, i.e.: ΔI rqref =ΔI rdref =0, ΔI nqref =ΔI ndref =0, thus obtaining the simplified AC current time-scale transfer function model of the doubly fed wind turbine in the dq coordinate system as follows:

[0132]

[0133] Phase-locked loops (PLLs) are the core component for synchronization between doubly-fed wind turbines and the power grid. Figure 6 The conversion between the dq coordinate system and the xy coordinate system shown depends on the normal operation of the phase-locked loop, so its dynamic behavior has an important impact on the stability of the wind farm. Figure 6 θ pll The phase-locked loop angle is the angle between the dq coordinate system and the xy coordinate system measured by the phase-locked loop; θ xy U represents the actual angle between the dq coordinate system and the xy coordinate system. g ∠θ xy =U gx +jU gy Indicates the voltage amplitude U at the grid connection point g With phase angle θ xy The magnitude component U of the grid connection point voltage on the x-axis gx The magnitude component U of the grid connection point voltage on the x-axis gy This indicates that in a doubly-fed wind farm, the dynamics of the phase-locked loop (PLL) are as follows: Figure 7 As shown, θ xy With θ pll The angle difference and the initial value U of the voltage amplitude at the grid connection point g0 The product is then passed through a low-pass filter T(s), and the result is further processed by a scaling factor K. p_θ The amplification process yields the first result, and the filtering result is further processed by the integration coefficient K. i_θ The integration process yields the second result x. θ The first and second results are summed and then integrated to obtain θ. pll The equations and the relationship between the phase angle and the port output can be expressed by the following formula:

[0134]

[0135]

[0136] Where, θ pll K represents the phase-locked loop angle. p V is the proportional control coefficient of the phase-locked loop; w0 X represents the steady-state voltage at the wind turbine's grid connection point; p In phase-locked loop state; K ip V represents the integral control coefficient of the phase-locked loop; wy0 V represents the steady-state y-axis value of the voltage at the wind turbine's grid connection point. wx0 V represents the steady-state value of the grid-connected voltage of the wind turbine along the x-axis. wx The voltage at the wind turbine's grid connection point is shown on the x-axis; V wy The voltage at the wind turbine's grid connection point is on the y-axis; K θ for V xy For [ΔV] wx ΔV wy ] T .

[0137] Based on the state-space form of the simplified model of the doubly fed wind turbine under the AC current time scale shown in Equation (26), and combining the xy and dq coordinate system transformation relationships expressed in Equations (27) to (28), the equivalent grid-connected doubly fed wind turbine model under the AC current time scale is obtained as follows:

[0138]

[0139]

[0140] Among them: G dq1 -G dq4 Let θ be the corresponding element of the transfer function shown in equation (26). pll V is the phase angle obtained from the phase-locked loop. dx0 V dy0 V d0 These represent the steady-state voltage values ​​along the x-axis, y-axis, and voltage amplitude, respectively. V dd0 V dq0 These are the steady-state voltage values ​​along the d-axis and q-axis, respectively. Based on the conclusion derived from equation (18), it is assumed that the equivalent reactance of a single doubly fed wind turbine after a certain period is η. max The transmission line connected to the external power grid constitutes the dynamic equivalent model of the doubly-fed wind farm. Therefore, the line dynamics are established as follows:

[0141]

[0142] Therefore, combining equations (28) and (30), the characteristic equation of the dynamic equivalent reduced-order model of the grid-connected doubly-fed wind farm (i.e., the characteristic equation corresponding to the grid-connected doubly-fed wind farm) is as follows:

[0143] a2s 2 +a1s+a0=0 (31)

[0144] Where a0, a1, and a2 are the coefficients in the characteristic equation. K ip V0 is the phase-locked loop integral coefficient; Q0 is the steady-state voltage at the grid connection point; K is the steady-state reactive power value; p ω0 is the proportional gain of the phase-locked loop; ω0 is the power frequency of the grid under steady-state conditions; P0 is the steady-state value of active power; X ss For the stator winding self-inductance; η max This represents the largest eigenvalue of the impedance matrix of a doubly-fed induction generator (DFIG) wind farm. The coefficients in the characteristic equation are related to the converter control parameters, steady-state power, and line impedance.

[0145] S104. Based on the characteristic equation and preset parameters corresponding to the grid-connected doubly fed wind farm, obtain the tuning results of the preset parameters of the grid-connected doubly fed wind farm.

[0146] Specifically, the Routh-Hurwitz criterion can be used to analyze the characteristic equation corresponding to the grid-connected doubly-fed induction generator (DFIG) wind farm to obtain the necessary and sufficient conditions for system stability. Under these conditions, preset parameters in the characteristic equation are used as variables to simplify the characteristic equation, thus obtaining the tuning results of the preset parameters of the DFIG wind farm. These preset parameters include, but are not limited to, parameters of the DFIG wind farm such as active power and the maximum eigenvalue of the impedance matrix. They are selected according to actual needs, and this embodiment of the invention does not impose any limitations. The characteristic equation corresponding to the DFIG wind farm includes the preset parameters of the DFIG wind farm.

[0147] The wind farm parameter tuning method provided in this invention can obtain a full-order linearized state-space model of the grid-connected doubly-fed induction generator (DFIG) wind farm based on the state-space model of each DFIG turbine. It then performs a dynamic equivalent transformation on the full-order linearized state-space model to obtain multiple independent subsystem models of the DFIG wind farm. Based on these independent subsystem models, it obtains the characteristic equations corresponding to the DFIG wind farm. Finally, based on these characteristic equations, it tunes the DFIG wind farm's parameters and preset parameters to obtain the tuning results. This method is applicable to large-scale DFIG wind farm applications and provides an effective solution for adjusting control strategies during design and operation. By optimizing control parameters, it improves system stability and reduces overall operation and maintenance costs.

[0148] Based on the above embodiments, the full-order linearized state-space model of the grid-connected doubly-fed wind farm is further as follows:

[0149]

[0150] in, Let ΔX be the column vector of state variables for a grid-connected doubly-fed induction generator (DFIG) wind farm. k Let A be the column vector of state variables for the k-th doubly-fed wind turbine. DFIG Let A be the state-space system matrix. DFIG =diag(A k )+diag(B k )X G diag(C k ), diag(A k ), diag(B k ) and diag(C k ) respectively represent A k B k and C k(k = 1, 2, ..., N) is a block diagonal matrix with diagonal elements, A k Let B be the system matrix in the full-order localized state-space model of the k-th doubly-fed wind turbine line. k Let C be the input matrix in the fully localized state-space model of the k-th doubly-fed wind turbine line. k This is the output matrix in the fully localized state-space model of the k-th doubly-fed wind turbine line. X gr For the network reactance matrix of a grid-connected doubly-fed wind farm, s is the Laplace operator, ω0 is the power frequency of the grid under steady state, k is a positive integer, and k is greater than or equal to 1 and less than or equal to N, and N is the total number of doubly fed wind turbines in the grid-connected doubly fed wind farm.

[0151] Based on the above embodiments, the subsystem model of the grid-connected doubly-fed wind farm is further as follows:

[0152]

[0153] Where, ΔY k Let A be the state variable of the k-th equivalent subsystem. Yk Let be the system matrix of the k-th equivalent subsystem. E n λ is an n-order identity matrix; ω0 is the power frequency of the power grid under steady-state conditions; k A represents the eigenvalues ​​of the impedance matrix. c B is the state matrix for a single wind turbine. c For a single wind turbine, the input matrix is ​​C. c This is the output matrix for a single wind turbine; k = 1, 2, ..., N; N is the number of wind turbines in the wind farm.

[0154] Based on the above embodiments, the characteristic equation corresponding to the grid-connected doubly-fed wind farm is further as follows:

[0155] a2s 2 +a1s+a0=0

[0156] Where a0, a1, and a2 are the coefficients in the characteristic equation. K ip V0 is the phase-locked loop integral coefficient; Q0 is the steady-state voltage at the grid connection point; K is the steady-state reactive power value; p ω0 is the proportional gain of the phase-locked loop; ω0 is the power frequency of the grid under steady-state conditions; P0 is the steady-state value of active power; X ss For the stator winding self-inductance; η max This is the largest eigenvalue of the impedance matrix of a doubly fed wind farm.

[0157] Based on the above embodiments, the preset parameters further include the maximum eigenvalue of the doubly-fed wind farm impedance matrix and / or the active power of the doubly-fed wind farm.

[0158] For example, the preset parameters include the maximum eigenvalue of the impedance matrix of the doubly-fed wind farm and the active power of the doubly-fed wind farm, and the characteristic equation corresponding to the grid-connected doubly-fed wind farm is a2s. 2 +a1s+a0=0. According to the Routh-Hurwitz criterion, the necessary and sufficient condition for system stability is: a2>0, a1>0. Since a2 is greater than 0 under normal operating conditions, further considering only a1>0, and simplifying the characteristic equation corresponding to the grid-connected doubly-fed wind farm by taking the maximum eigenvalue of the impedance matrix and the active power of the doubly-fed wind farm as variables, we can obtain the following two conclusions:

[0159]

[0160]

[0161] Where ω0 is the power frequency of the grid under steady-state conditions; V0 is the steady-state value of the bus voltage; K p P0 is the proportional gain of the phase-locked loop; K is the active power; ip is the integral coefficient of the phase-locked loop; Q0 is the reactive power.

[0162] Equations (32) and (33) above represent the η required for system stability in a doubly-fed wind farm under the alternating current time scale proposed in this invention. max The above equation also shows that instability is more likely to occur when the line length is long and the system power is high.

[0163] To verify the effectiveness of the above theoretical derivation, this embodiment of the invention uses a grid-connected doubly-fed wind farm consisting of 12 grid-connected doubly-fed wind turbines as an example to verify the correctness of the tuning results of the grid-connected doubly-fed wind farm based on the small disturbance stability parameters of the system under a fast time scale obtained by equations (32) and (33). In this embodiment, each parameter uses per-unit values.

[0164] The parameters for Example 1 are set as follows: the maximum value η of the characteristic value of the wind farm line impedance. max The proportional gain K of the phase-locked loop is 0.25. p The integral coefficient K is 0.55. ip Given 300, substitute these parameters into equation (33) to solve for the active power corresponding to critical stability. The dominant oscillation modes and their stability criteria for wind farms at different active power levels, calculated based on the linearized state-space model of the system, are shown in Table 1.

[0165] Table 1. Stability Criterion Results When Active Power P0 Changes

[0166] <![CDATA[P0]]> Judgment result Oscillation mode 0.3 Stablize -2.12±j210.51 0.312 Critical stability -0.11±j252.24 0.33 Unstable 2.65±j250.09

[0167] According to the results in Table 1, if the active power P0 is too large and exceeds the critical stability point obtained by equation (33), the system becomes unstable, and the damping of the corresponding oscillation mode becomes negative. Conversely, by appropriately adjusting the system operating parameters to increase the critical stability point of the system, it helps to improve the stability margin of the system. In order to further verify the correctness of the above theoretical derivation and linearization analysis results, a nonlinear simulation of the grid-connected doubly fed wind farm system was carried out. The simulation was set as follows: at t = 0.3s, the wind speed of doubly fed wind turbines 1-3 increased by 5% and recovered at t = 0.35s. The results of the nonlinear simulation under different power outputs are as follows. Figure 8 As shown, the vertical axis represents the change based on the steady-state value. Figure 8 It can be seen that as P0 increases beyond the stable operating boundary, the system gradually tends to become unstable from the initial stable state, which is consistent with the result obtained by the stability criterion proposed in this invention.

[0168] Similarly, to analyze the maximum value η of the eigenvalues ​​of the wind farm impedance matrix... max The impact of changes on system stability is considered. The parameters for Example 2 are set as follows: the output power P0 of the doubly fed wind farm is 0.3, and the phase-locked loop parameters are consistent with those of Example 1. Substituting these parameters into equation (32) yields the solution. The results of the stability criteria calculation for different equivalent impedances are shown in Table 2.

[0169] Table 2. Maximum value η of the anti-matrix eigenvalues max Stability criterion results during change

[0170] <![CDATA[η max ]]> Judgment result Oscillation mode 0.24 Stablize -4.37±j212.33 0.28 Critical stability -0.15±j203.22 0.31 Unstable 1.58±j202.21

[0171] Nonlinear simulation results under different equivalent impedances are as follows Figure 9 As shown.

[0172] Simulation results show that: (1) an excessively large maximum equivalent impedance of the collector line, i.e., a low short-circuit ratio of the doubly fed wind farm through a long line system, will also lead to instability of the doubly fed wind turbine in the AC current time scale; (2) adjusting the unit operating parameters of the doubly fed wind farm can change the critical stability point of the system, i.e., the stability margin of the system can be increased by adjusting the parameters; (3) the stability criterion proposed in this invention and the linearization analysis results are consistent with the conclusions obtained from the time-domain simulation.

[0173] Figure 10 This is a schematic diagram of the structure of the wind farm parameter setting device provided in the tenth embodiment of the present invention, as shown below. Figure 10As shown, the wind farm parameter tuning device provided in this embodiment of the invention includes a first acquisition module 1001, a transformation module 1002, a second acquisition module 1003, and a third acquisition module 1004, wherein:

[0174] The first obtaining module 1001 is used to obtain the full-order linearized state-space model of the grid-connected doubly-fed wind farm based on the state-space model of each doubly-fed wind turbine in the doubly-fed wind farm; the transformation module 1002 is used to perform dynamic equivalent transformation on the full-order linearized state-space model of the grid-connected doubly-fed wind farm to obtain multiple independent subsystem models of the grid-connected doubly-fed wind farm; the second obtaining module 1003 is used to obtain the characteristic equation corresponding to the grid-connected doubly-fed wind farm based on the multiple independent subsystem models of the grid-connected doubly-fed wind farm; the third obtaining module 1004 is used to tune the preset parameters of the grid-connected doubly-fed wind farm based on the characteristic equation corresponding to the grid-connected doubly-fed wind farm to obtain the tuning result of the preset parameters of the grid-connected doubly-fed wind farm.

[0175] Specifically, the grid-connected doubly-fed induction generator (DFIG) wind farm includes multiple DFIG wind turbines, each with a corresponding state-space model. The first acquisition module 1001 can obtain the full-order linearized state-space model of the grid-connected DFIG wind farm based on the state-space models of each DFIG wind turbine.

[0176] Based on the full-order linearized state-space model of the grid-connected doubly-fed wind farm, and ignoring the differences in dynamic characteristics between the individual doubly-fed wind turbines, the transformation module 1002 dynamically transforms the full-order linearized state-space model of the grid-connected doubly-fed wind farm into a subsystem model of multiple independent doubly-fed wind turbines.

[0177] In the operation of a grid-connected doubly-fed induction generator (DFIG) wind farm, AC current control plays a crucial role in the system's dynamic characteristics, directly affecting the stability and overall performance of the wind farm. Under the AC current timescale, the system's dynamic response is closely related to the control strategy. Therefore, by analyzing the key control mechanisms of the DFIG wind turbine and its network connectivity characteristics, the characteristic equations of the equivalent subsystem can be derived, thereby revealing the dynamic behavior of the wind farm under small disturbance conditions. The second acquisition module 1003 can obtain the characteristic equations corresponding to the grid-connected DFIG wind farm based on multiple independent subsystem models of the DFIG wind farm.

[0178] The third acquisition module 1004 can analyze the characteristic equation corresponding to the grid-connected doubly-fed induction generator (DFIG) wind farm using the Routh-Herwitz criterion to obtain the necessary and sufficient conditions for system stability. Under these conditions, preset parameters in the characteristic equation are used as variables to simplify the characteristic equation, thereby obtaining the tuning results of the preset parameters of the DFIG wind farm. These preset parameters include, but are not limited to, parameters of the DFIG wind farm such as active power and the maximum eigenvalue of the impedance matrix. They are selected according to actual needs, and this embodiment of the invention does not impose any limitations. The characteristic equation corresponding to the DFIG wind farm includes the preset parameters of the DFIG wind farm.

[0179] The wind farm parameter tuning device provided in this invention can obtain a full-order linearized state-space model of the grid-connected doubly-fed induction generator (DFIG) wind farm based on the state-space model of each DFIG turbine. It then performs a dynamic equivalent transformation on the full-order linearized state-space model to obtain multiple independent subsystem models of the DFIG wind farm. Based on these independent subsystem models, it obtains the characteristic equations corresponding to the DFIG wind farm. Finally, based on these characteristic equations, it tunes the preset parameters of the DFIG wind farm and obtains the tuning results for these preset parameters. This device is suitable for large-scale DFIG wind farm applications and provides an effective solution for adjusting control strategies during design and operation. By optimizing control parameters, it improves system stability and reduces overall operation and maintenance costs.

[0180] Based on the above embodiments, the full-order linearized state-space model of the grid-connected doubly-fed wind farm is further as follows:

[0181]

[0182] in, Let ΔX be the column vector of state variables for a grid-connected doubly-fed induction generator (DFIG) wind farm. k Let A be the column vector of state variables for the k-th doubly-fed wind turbine. DFIG Let A be the state-space system matrix. DFIG =diag(A k )+diag(B k )X G diag(C k ), diag(A k ), diag(B k ) and diag(C k ) respectively represent A k B k and C k(k = 1, 2, ..., N) is a block diagonal matrix with diagonal elements, A k Let B be the system matrix in the full-order localized state-space model of the k-th doubly-fed wind turbine line. k Let C be the input matrix in the fully localized state-space model of the k-th doubly-fed wind turbine line. k This is the output matrix in the fully localized state-space model of the k-th doubly-fed wind turbine line. X gr For the network reactance matrix of a grid-connected doubly-fed wind farm, s is the Laplace operator, ω0 is the power frequency of the grid under steady state, k is a positive integer, and k is greater than or equal to 1 and less than or equal to N, and N is the total number of doubly fed wind turbines in the grid-connected doubly fed wind farm.

[0183] Based on the above embodiments, the subsystem model of the grid-connected doubly-fed wind farm is further as follows:

[0184]

[0185] Where, ΔY k Let A be the state variable of the k-th equivalent subsystem. Yk Let be the system matrix of the k-th equivalent subsystem. E n λ is an n-order identity matrix; ω0 is the power frequency of the power grid under steady-state conditions; k A represents the eigenvalues ​​of the impedance matrix. c B is the state matrix for a single wind turbine. c For a single wind turbine, the input matrix is ​​C. c This is the output matrix for a single wind turbine; k = 1, 2, ..., N; N is the number of wind turbines in the wind farm.

[0186] Based on the above embodiments, the characteristic equation corresponding to the grid-connected doubly-fed wind farm is further as follows:

[0187] a2s 2 +a1s+a0=0

[0188] Where a0, a1, and a2 are the coefficients in the characteristic equation. K ip V0 is the phase-locked loop integral coefficient; Q0 is the steady-state voltage at the grid connection point; K is the steady-state reactive power value; p ω0 is the proportional gain of the phase-locked loop; ω0 is the power frequency of the grid under steady-state conditions; P0 is the steady-state value of active power; X ss For the stator winding self-inductance; η max This is the largest eigenvalue of the impedance matrix of a doubly fed wind farm.

[0189] Based on the above embodiments, the preset parameters further include the maximum eigenvalue of the doubly-fed wind farm impedance matrix and / or the active power of the doubly-fed wind farm.

[0190] The embodiments of the device provided in this invention can be used to execute the processing flow of the above-described method embodiments. Its functions will not be repeated here, but can be referred to the detailed description of the above-described method embodiments.

[0191] Figure 11 This is a schematic diagram of the physical structure of a computer device provided in an embodiment of the present invention, as shown below. Figure 11 As shown, the computer device may include: a processor 1101, a communications interface 1102, a memory 1103, and a communications bus 1104, wherein the processor 1101, the communications interface 1102, and the memory 1103 communicate with each other through the communications bus 1104. The processor 1101 can call logic instructions in the memory 1103 to execute the following methods: based on the state-space model of each doubly-fed wind turbine in the grid-connected doubly-fed wind farm, obtain a full-order linearized state-space model of the grid-connected doubly-fed wind farm; perform dynamic equivalent transformation on the full-order linearized state-space model of the grid-connected doubly-fed wind farm to obtain multiple independent subsystem models of the grid-connected doubly-fed wind farm; based on the multiple independent subsystem models of the grid-connected doubly-fed wind farm, obtain the characteristic equation corresponding to the grid-connected doubly-fed wind farm; based on the characteristic equation corresponding to the grid-connected doubly-fed wind farm, tune the preset parameters of the grid-connected doubly-fed wind farm and obtain the tuning result of the preset parameters of the grid-connected doubly-fed wind farm.

[0192] Furthermore, the logical instructions in the aforementioned memory 1103 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, essentially, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0193] This embodiment discloses a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium. The computer program includes program instructions, and when the program instructions are executed by the computer, the computer can execute the methods provided in the above-described method embodiments, such as: obtaining a full-order linearized state-space model of the grid-connected doubly-fed wind farm based on the state-space model of each doubly-fed wind turbine; performing a dynamic equivalent transformation on the full-order linearized state-space model of the grid-connected doubly-fed wind farm to obtain multiple independent subsystem models of the grid-connected doubly-fed wind farm; obtaining the characteristic equation corresponding to the grid-connected doubly-fed wind farm based on the multiple independent subsystem models of the grid-connected doubly-fed wind farm; tuning the preset parameters of the grid-connected doubly-fed wind farm based on the characteristic equation corresponding to the grid-connected doubly-fed wind farm; and obtaining the tuning result of the preset parameters of the grid-connected doubly-fed wind farm.

[0194] This embodiment provides a computer-readable storage medium storing a computer program / instruction that causes a computer to execute the methods provided in the above-described method embodiments. For example, the methods include: obtaining a full-order linearized state-space model of the grid-connected doubly-fed wind farm based on the state-space model of each doubly-fed wind turbine; performing a dynamic equivalent transformation on the full-order linearized state-space model of the grid-connected doubly-fed wind farm to obtain multiple independent subsystem models of the grid-connected doubly-fed wind farm; obtaining the characteristic equation corresponding to the grid-connected doubly-fed wind farm based on the multiple independent subsystem models of the grid-connected doubly-fed wind farm; and tuning preset parameters of the grid-connected doubly-fed wind farm based on the characteristic equation corresponding to the grid-connected doubly-fed wind farm, and obtaining the tuning result of the preset parameters of the grid-connected doubly-fed wind farm.

[0195] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention 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.

[0196] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. 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 illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0197] 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.

[0198] 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.

[0199] In the description of this specification, the references to terms such as "an embodiment," "a specific embodiment," "some embodiments," "for example," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0200] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions 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 parameter tuning in a wind farm, characterized in that, include: Based on the state-space model of each doubly fed wind turbine in the grid-connected doubly fed wind farm, the full-order linearized state-space model of the grid-connected doubly fed wind farm is obtained. A dynamic equivalent transformation is performed on the full-order linearized state-space model of the grid-connected doubly-fed wind farm to obtain multiple independent subsystem models of the grid-connected doubly-fed wind farm. Based on the model of multiple independent subsystems of the grid-connected doubly fed wind farm, the characteristic equation corresponding to the grid-connected doubly fed wind farm is obtained. Based on the characteristic equation corresponding to the grid-connected doubly fed wind farm, the preset parameters of the grid-connected doubly fed wind farm are tuned to obtain the tuning results of the preset parameters of the grid-connected doubly fed wind farm. The step of performing a dynamic equivalent transformation on the full-order linearized state-space model of the grid-connected doubly-fed wind farm to obtain multiple independent subsystem models of the grid-connected doubly-fed wind farm includes: The network reactance matrix in the full-order linearized state-space model of the grid-connected doubly fed wind farm is decomposed into eigenvalues ​​to obtain multiple eigenvalues. Based on the multiple eigenvalues, the full-order linearized state-space model is dynamically and equivalently transformed into multiple independent subsystem models, wherein each subsystem model corresponds to one eigenvalue. The preset parameters of the grid-connected doubly-fed induction generator (DFIG) wind farm include the maximum eigenvalue of the DFIG wind farm impedance matrix and the active power of the DFIG wind farm; correspondingly, the tuning result for obtaining the maximum eigenvalue of the DFIG wind farm impedance matrix is ​​as follows: The active power setting result for the doubly-fed wind farm is as follows: in, The largest eigenvalue of the impedance matrix of the doubly fed wind farm is... The power frequency of the power grid under steady-state conditions; This is the steady-state value of the bus voltage; This refers to the proportional gain of the phase-locked loop; The active power of the doubly-fed wind farm; These are the integral coefficients of the phase-locked loop; This refers to reactive power.

2. The method according to claim 1, characterized in that, The full-order linearized state-space model of the grid-connected doubly-fed wind farm is as follows: in, This is the column vector of state variables for a grid-connected doubly-fed induction generator (DFIG) wind farm. Let K be the column vector of state variables for the k-th doubly-fed wind turbine. For the state-space system matrix, , , and They represent respectively with , and A block diagonal matrix with diagonal elements. Let be the system matrix in the full-order localized state-space model of the k-th doubly-fed wind turbine line. Let be the input matrix in the fully localized state-space model of the k-th doubly-fed wind turbine line. This is the output matrix in the fully localized state-space model of the k-th doubly-fed wind turbine line. , , X gr For the network reactance matrix of a grid-connected doubly-fed wind farm, , s For the Laplace operator, Let k be the power frequency of the grid under steady-state conditions, k be a positive integer, and k is greater than or equal to 1 and less than or equal to N, where N is the total number of doubly fed wind turbines in the grid-connected doubly fed wind farm.

3. The method according to claim 1, characterized in that, The subsystem model of the grid-connected doubly fed wind farm is as follows: in, Let k be the state variables of the k-th equivalent subsystem. Let be the system matrix of the k-th equivalent subsystem. , It is an n-order identity matrix; The power frequency of the power grid under steady-state conditions; These are the eigenvalues ​​of the impedance matrix; The state matrix for a single wind turbine; The input matrix for a single wind turbine; This is the output matrix for a single wind turbine; ; ; This refers to the number of wind turbines in the wind farm.

4. The method according to claim 1, characterized in that, The characteristic equation corresponding to the grid-connected doubly fed wind farm is: in, , and The coefficients in the characteristic equation, , , , These are the integral coefficients of the phase-locked loop; This is the steady-state value of the grid connection point voltage; This represents the steady-state value of reactive power. This refers to the proportional gain of the phase-locked loop; The power frequency of the power grid under steady-state conditions; This represents the steady-state value of active power. For stator winding self-inductance; This is the largest eigenvalue of the impedance matrix of a doubly fed wind farm.

5. A parameter tuning device for a wind farm, characterized in that, include: The first acquisition module is used to obtain the full-order linearized state-space model of the grid-connected doubly-fed wind farm based on the state-space model of each doubly-fed wind turbine in the grid-connected doubly-fed wind farm. The transformation module is used to perform dynamic equivalent transformation on the full-order linearized state-space model of the grid-connected doubly fed wind farm to obtain multiple independent subsystem models of the grid-connected doubly fed wind farm. The second obtaining module is used to obtain the characteristic equations corresponding to the grid-connected doubly fed wind farm based on multiple independent subsystem models of the grid-connected doubly fed wind farm. The third obtaining module is used to adjust the preset parameters of the grid-connected doubly fed wind farm based on the characteristic equation corresponding to the grid-connected doubly fed wind farm, and obtain the tuning result of the preset parameters of the grid-connected doubly fed wind farm. Specifically, the transformation module is used to perform eigenvalue decomposition on the network reactance matrix in the full-order linearized state-space model of the grid-connected doubly fed wind farm to obtain multiple eigenvalues; based on the multiple eigenvalues, the full-order linearized state-space model is dynamically and equivalently transformed into multiple independent subsystem models, wherein each subsystem model corresponds to an eigenvalue; The preset parameters of the grid-connected doubly-fed induction generator (DFIG) wind farm include the maximum eigenvalue of the DFIG wind farm impedance matrix and the active power of the DFIG wind farm; correspondingly, the tuning result for obtaining the maximum eigenvalue of the DFIG wind farm impedance matrix is ​​as follows: The active power setting result for the doubly-fed wind farm is as follows: 。 6. The apparatus according to claim 5, characterized in that, The full-order linearized state-space model of the grid-connected doubly-fed wind farm is as follows: in, This is the column vector of state variables for a grid-connected doubly-fed induction generator (DFIG) wind farm. Let K be the column vector of state variables for the k-th doubly-fed wind turbine. For the state-space system matrix, , , and They represent respectively with , and A block diagonal matrix with diagonal elements. Let be the system matrix in the full-order localized state-space model of the k-th doubly-fed wind turbine line. Let be the input matrix in the fully localized state-space model of the k-th doubly-fed wind turbine line. This is the output matrix in the fully localized state-space model of the k-th doubly-fed wind turbine line. , , X gr For the network reactance matrix of a grid-connected doubly-fed wind farm, , s For the Laplace operator, Let k be the power frequency of the grid under steady-state conditions, k be a positive integer, and k is greater than or equal to 1 and less than or equal to N, where N is the total number of doubly fed wind turbines in the grid-connected doubly fed wind farm.

7. The apparatus according to claim 5, characterized in that, The subsystem model of the grid-connected doubly fed wind farm is as follows: in, Let k be the state variables of the k-th equivalent subsystem. Let be the system matrix of the k-th equivalent subsystem. , It is an n-order identity matrix; The power frequency of the power grid under steady-state conditions; These are the eigenvalues ​​of the impedance matrix; The state matrix for a single wind turbine; The input matrix for a single wind turbine; This is the output matrix for a single wind turbine; ; ; This refers to the number of wind turbines in the wind farm.

8. The apparatus according to claim 5, characterized in that, The characteristic equation corresponding to the grid-connected doubly fed wind farm is: in, , and The coefficients in the characteristic equation, , , , These are the integral coefficients of the phase-locked loop; This refers to the voltage at the grid connection point. Reactive power; This refers to the proportional gain of the phase-locked loop; The power frequency of the power grid under steady-state conditions; Active power; For stator winding self-inductance; This is the largest eigenvalue of the impedance matrix of a doubly fed wind farm.

9. A computer device, comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 4.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program / instructions that, when executed by a processor, implement the steps of the method according to any one of claims 1 to 4.

11. A computer program product, comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the method according to any one of claims 1 to 4.

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