A method for improving active power transmission capacity of a wind turbine under asymmetric fault

Abstract

The application discloses a kind of wind turbine active power transmission capacity promotion methods under asymmetric fault, to solve the problems such as existing technology wind turbine active power transmission capacity is limited under asymmetric fault, prone to overcurrent overvoltage and transient instability etc..The method first establishes the optimal active power transmission capacity promotion model containing rotor current, rotor voltage, voltage unbalance degree and transient stability constraint;Then, through the reconstruction of double sequence coordinate system and semi-positive relaxation technique, the non-convex model is convex, to ensure the global optimality of solution;Finally, according to the actual power limit, the active power transmission promotion and voltage unbalance suppression are adaptively coordinated.The application can make full use of the power and current capacity of wind turbine, significantly improve the active power output capacity under asymmetric fault, and effectively suppress the voltage imbalance under the premise of ensuring safe and stable operation, and provide a reference for improving the active power transmission capacity of wind turbine under asymmetric fault.

Description

Technical Field

[0001] This invention relates to the field of wind power generation control technology, and in particular to a method for improving the active power transmission capability of a wind turbine generator set based on a doubly fed induction generator under grid asymmetric fault conditions. Background Technology

[0002] With the gradual replacement of large-scale synchronous generators, renewable energy resources (RES) are required to maintain active power transfer capability (APTC) even during grid faults to reduce the risk of power supply shortages. However, compared with symmetrical faults, asymmetrical faults pose a severe challenge to the active power transfer capability of renewable energy resources, especially doubly-fed wind turbines.

[0003] Reference ① [Z. Wang et al. PLL Synchronization Transient Stability Analysis of a Weak-Grid Connected VSC During Asymmetric Faults[J]. IEEE Transactions on Power Electronics, 2024, 39(2): 2140-2154.] points out that the dual-sequence coupling effect cannot be ignored when the fault location is close to the point of common coupling. Due to the dual-sequence coupling effect, the transient stability feasible regions considering positive-sequence and negative-sequence currents will interact. Reference ② [Y. Feng, W. Huang, Z. Jin, Y. Li, ZJShen and Z. Shuai. Voltage Support Strategy for Improving Power Transfer Capability of Grid-Connected Converter Under Unbalanced Conditions[J]. IEEE Transactions on Power Electronics, 2024, 39(7): 7863-7875.] proposes a negative-sequence voltage compensation strategy to increase the output active power, in which a smaller amount of negative-sequence current is injected into the grid to attenuate the voltage imbalance. Reference 3 GB3 ③ [H. Zhang, R. Liu, C. Xue and Y. Li. Active Power Enhancement Control Strategy of Grid-Forming Inverters Under Asymmetrical Grid Faults[J].IEEE Transactions on Power Electronics, 2024,39(1): 1447-1459.] points out that the power angle in a dual-sequence network is a key factor affecting APTC, and proposes an accurate voltage compensation strategy based on a controllable dual-sequence power angle.

[0004] Previous research has primarily focused on enhancing the APTC of traditional grid-connected converters. However, wind turbine generators based on doubly fed induction generators (DFIGs) differ significantly in structure and control methods, mainly due to their rotor-side converters (RSCs). Further exploration of the active power margin of DFIG wind turbines presents challenges in optimal current command design: i) Due to the high back EMF caused by the reverse-rotating negative-sequence flux linkage, DFIGs are susceptible to overcurrent, overmodulation, and transient instability. ii) Asymmetric faults introduce multivariable coupling, and nonlinear transformation relationships exist between stator and rotor physical quantities in DFIGs. The nonconvexity arising from the double-sequence coupling effect and inherent slip characteristics complicates the optimization problem.

[0005] Therefore, how to design an effective control strategy to maximize the active power transmission capacity of DFIG under asymmetrical faults while meeting various safety constraints, and at the same time suppressing voltage imbalance, is a technical problem that urgently needs to be solved. Summary of the Invention

[0006] The purpose of this invention is to provide a method for improving the active power transmission capability of wind turbine generators under asymmetrical faults, in order to solve the problems mentioned in the background art, such as limited active power transmission of DFIG under asymmetrical faults, difficulty in solving non-convex models, and difficulty in coordinating active power improvement and voltage imbalance suppression.

[0007] According to a first aspect of the embodiments of this application, a method for improving the active power transmission capability of a wind turbine under asymmetrical faults is provided, comprising:

[0008] An optimal active power transmission capability enhancement model for doubly-fed induction generator (DFIG) wind turbines under asymmetrical faults is established. The model includes an objective function, rotor current constraints, rotor voltage constraints, voltage imbalance constraints, and transient stability constraints.

[0009] Based on the aforementioned optimal active power transmission capacity enhancement model, the positive and negative sequence synchronously rotated coordinate systems... d The axes are unified to the grid voltage orientation mode, and the dual-sequence synchronous rotating coordinate system is reconstructed to eliminate the nonlinearity and coupling characteristics caused by the dual-sequence power angular coupling term;

[0010] Based on the electrical quantities after the dual-sequence synchronous rotating coordinate system, a second-order cone relaxation transformation is performed on the rotor current constraint and the rotor voltage constraint, and a positive semidefinite relaxation transformation is performed on the voltage imbalance constraint. An augmented matrix variable is constructed and a rank constraint is introduced to form a standard positive semidefinite programming problem.

[0011] Based on the semidefinite programming model, and according to the actual active power limit, the active power transmission capacity improvement and voltage imbalance suppression are adaptively coordinated. The voltage imbalance constraint limit value is iteratively adjusted until the calculated active power is less than or equal to the actual active power limit.

[0012] According to a second aspect of the embodiments of this application, a device for improving the active power transmission capacity of a wind turbine under asymmetrical faults is provided, comprising:

[0013] The model building module is used to build an optimal active power transmission capability improvement model for doubly fed wind turbines under asymmetrical faults. The model includes an objective function, rotor current constraints, rotor voltage constraints, voltage imbalance constraints, and transient stability constraints.

[0014] The first convexity processing module is used to synchronously rotate the positive-sequence and negative-sequence coordinate systems based on the optimal active power transmission capability improvement model. d The axes are unified to the grid voltage orientation mode, and the dual-sequence synchronous rotating coordinate system is reconstructed to eliminate the nonlinearity and coupling characteristics caused by the dual-sequence power angular coupling term;

[0015] The second convexity processing module is used to perform second-order cone relaxation transformation on the rotor current constraint and the rotor voltage constraint based on the electrical quantities after the dual-sequence synchronous rotating coordinate system, and to perform semi-positive definite relaxation transformation on the voltage imbalance constraint, constructing augmented matrix variables and introducing rank constraints to form a standard semi-positive definite programming problem.

[0016] The adaptive solution module is used to adaptively coordinate the improvement of active power transmission capacity and the suppression of voltage imbalance based on the semidefinite programming model and the actual active power limit. It iteratively adjusts the limit value of voltage imbalance constraint until the calculated active power is less than or equal to the actual active power limit.

[0017] According to a third aspect of the embodiments of this application, an electronic device is provided, characterized in that it includes:

[0018] One or more processors;

[0019] Memory, used to store one or more programs;

[0020] When the one or more programs are executed by the one or more processors, the one or more processors perform the method as described in the first aspect.

[0021] According to a fourth aspect of the embodiments of this application, a computer-readable storage medium is provided that stores computer instructions thereon, which, when executed by a processor, implement the steps of the method as described in the first aspect.

[0022] The technical solutions provided by the embodiments of this application may include the following beneficial effects:

[0023] As can be seen from the above embodiments, this application effectively prevents overcurrent and overmodulation caused by high negative sequence electromotive force by establishing an optimal active power transmission capacity improvement model, which includes an objective function, rotor current constraints, rotor voltage constraints, voltage imbalance constraints, and transient stability constraints. It also ensures the stable equilibrium point of the dual-sequence phase-locked loop (PLL) and improves the safety of system operation. Through convexity reduction techniques such as dual-sequence coordinate system reconstruction and semi-definite relaxation, the inherent slip characteristics of the DFIG and the non-convexity problem introduced by the dual-sequence coupling effect are effectively solved, guaranteeing the global optimality or high-quality approximation of the optimization solution. Geometric analysis reveals the mutual constraint relationship between VUF suppression and APTC improvement, and an adaptive coordination mechanism is designed. This mechanism can flexibly adjust the priority of the two objectives while considering actual power limitations, fully utilizing the power and current capacity of the DFIG. The proposed method can significantly improve the active power transmission capacity of the DFIG under asymmetrical faults while maintaining effective VUF suppression capability. This is the method we provide.

[0024] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0025] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0026] Figure 1 This is a flowchart illustrating a method for improving the active power transmission capability of a wind turbine under asymmetrical faults, according to an exemplary embodiment.

[0027] Figure 2 This is a system topology and control block diagram of a doubly fed wind turbine under asymmetric fault, as shown in an embodiment of the present invention.

[0028] Figure 3 This is a schematic diagram of the reconstruction of the dual-sequence coordinate system of a doubly fed wind turbine according to an embodiment of the present invention.

[0029] Figure 4 This is a geometrical diagram illustrating the relationship between enhanced active power transmission capability and suppression of voltage imbalance according to an embodiment of the present invention.

[0030] Figure 5 This is an algorithm flowchart illustrating the method of the present invention according to an embodiment of the present invention.

[0031] Figure 6This is a block diagram illustrating a device for enhancing the active power transmission capacity of a wind turbine under asymmetrical faults, according to an exemplary embodiment. Detailed Implementation

[0032] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0033] The terminology used in this application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The singular forms “a,” “the,” and “the” used in this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

[0034] Figure 1 This is a flowchart illustrating a method for improving the active power transmission capacity of a wind turbine under asymmetrical faults, according to an exemplary embodiment. Figure 1 As shown, the method may include the following steps:

[0035] S1: Establish an optimal active power transmission capability improvement model for doubly fed wind turbine generators under asymmetrical faults. The model includes an objective function, rotor current constraints, rotor voltage constraints, voltage imbalance constraints, and transient stability constraints.

[0036] Specifically, Figure 2 This is a topology and control block diagram of a doubly-fed induction generator (DFIG) system under asymmetrical fault conditions, according to an embodiment of the present invention. The control of the DFIG includes a synchronization unit and a dual-sequence current control unit. A commonly used decoupled double synchronous reference frame phase-locked loop (DDSRF-PLL) is used as the synchronization unit. Improving the stator output active power of the DFIG through the RSC is key to enhancing the DFIG's APTC (Active Power Tolerance), and is also the focus of this invention. Since the grid-side converter (GSC) primarily maintains a constant DC bus voltage, this invention simplifies the analysis by treating the GSC as an equivalent constant DC voltage.

[0037] When an asymmetrical fault occurs (including single-phase grounding, two-phase grounding, and phase-to-phase faults), due to the dual-sequence coupling effect, the stator voltage equation can be expressed as:

[0038]

[0039] U g This is the grid voltage. K + The positive sequence voltage equivalent coefficient. K − This is the equivalent coefficient for negative sequence voltage. Z e This represents the equivalent order self-impedance. Z c This represents the equivalent sequence coupling impedance.

[0040] During asymmetrical faults, overcurrent must be prevented and RSC protected. Therefore, the rotor current constraint can be expressed as:

[0041]

[0042] x s This indicates the stator inductance of the doubly-fed wind turbine. x m This indicates the mutual inductance of the doubly-fed wind turbine. I rmax This indicates the upper limit of the rotor current.

[0043] To ensure the controllability of the DFIG during a fault, the RSC must avoid overmodulation. Therefore, the rotor voltage constraint can be expressed as:

[0044]

[0045] s σ represents the slip of the doubly-fed induction generator (DFIG), and σ represents the leakage flux coefficient of the DFIG. U rmax This indicates the upper limit of the rotor voltage.

[0046] Under asymmetric fault conditions, the DFIG should suppress the VUF to a predetermined range. Therefore, the VUF constraint can be expressed as:

[0047]

[0048] η This indicates the upper limit of voltage imbalance.

[0049] Based on the orientation angle obtained from DDSRF-PLL, the stator voltage equation can be further transformed using the Park transformation:

[0050]

[0051] r e , x e They represent Z e The real and imaginary parts, r c , x c They represent Z c The real and imaginary parts of S, where S+(−) represents the transient stability coefficient corresponding to the positive and negative order. I sq+(−) Indicates positive and negative q shaft current, I ′ sd+(−) Indicates positive and negative order d Projection of axis current, I ′ sq+(−) Indicates positive and negative order q Projection of axis current.

[0052] The positive and negative order coupling terms need to be projections from the original orientation mode, expressed as:

[0053] .

[0054] Throughout the asymmetrical fault, the PLL should remain synchronized with the grid voltage, which means the PLL must have a stable equilibrium point (SEP). Therefore, S + >0 and S − >0 must be considered a transiently stable constraint expression because it is consistent with the existence of SEP.

[0055] As the optimization objective, the objective function is the output active power under asymmetric faults, which consists of positive-sequence and negative-sequence components, and can be expressed as:

[0056]

[0057] Where max represents the maximum value. P s For stator active power, U s+ This is the stator positive sequence voltage. U s− The stator negative sequence voltage, I sd+ For stator positive sequence d shaft current, I sd− For stator negative sequence d Axis current.

[0058] S2: Based on the aforementioned optimal active power transmission capacity enhancement model, the positive and negative sequence synchronously rotated coordinate systems. d The axes are unified to the grid voltage orientation mode, and the dual-sequence synchronous rotating coordinate system is reconstructed to eliminate the nonlinearity and coupling characteristics caused by the dual-sequence power angular coupling term;

[0059] Specifically, in order to eliminate the effects of coupling and nonlinear characteristics related to power angle coupling terms, considering that the grid voltage source is the source of the equivalent positive and negative sequence sources in the circuit model, the d-axis of the positive and negative sequence synchronous coordinate system is oriented to the grid voltage. Figure 3 This is a schematic diagram of the reconstructed dual-sequence coordinate system for a DFIG wind turbine. The voltage equation in the reconstructed dual-sequence synchronous coordinate system can be expressed as:

[0060]

[0061] U sd+ Indicates stator positive d shaft voltage, U sd− Indicates stator negative d shaft voltage, U sq+ Indicates stator positive sequence q Shaft voltage; U sq− Indicates stator negative sequence q Shaft voltage; K 1+ , K 2+ They represent K + The real and imaginary parts, K 1− , K 2− They represent K − The real and imaginary parts of , ^ represent the state components in the reconstructed bi-order coordinate system.

[0062] After the dual-order synchronous coordinate system is reconstructed, the transient stability constraints are naturally included in the above equations. Since the reconstruction process is merely an equivalent mathematical transformation, the solvability of the reconstruction equations establishes the existence of a stable equilibrium point in the dual-order PLL. As long as the optimal APTC augmentation problem has a feasible solution, it must satisfy... S + >0 and S − >0, thus ensuring that the PLL has a stable equilibrium point.

[0063] S3: Based on the electrical quantities after the dual-sequence synchronous rotating coordinate system, perform a second-order cone relaxation transformation on the rotor current constraint and rotor voltage constraint, perform a semi-definite relaxation transformation on the voltage imbalance constraint, construct augmented matrix variables and introduce rank constraints to form a standard semi-definite programming problem.

[0064] Specifically, the stator voltage equations in the reconstructed dual-sequence synchronous coordinate system can be expressed in matrix form:

[0065] u = Zi + k

[0066] u Represents the stator voltage matrix. i Represents the stator current matrix. k This represents the grid voltage matrix.

[0067] To eliminate the non-convexity of the rotor current constraint, based on Cauchy's inequality, the rotor current constraint can be further relaxed into a second-order conical form as follows:

[0068]

[0069] Z I This represents the impedance matrix in rotor current constraints. Q This represents the auxiliary matrix for stator-rotor transformation.

[0070] Because this form is a standard second-order cone form, the convexity of the rotor current constraint is guaranteed. Similarly, the rotor voltage constraint can also be converted into a second-order cone form as follows:

[0071]

[0072] Z V This represents the impedance matrix in the rotor voltage constraint. G This represents the rotor voltage auxiliary matrix.

[0073] For VUF constraints, they cannot be directly converted into convex constraints; therefore, positive semidefinite relaxation is considered. The positive semidefinite augmented matrix variable Y is constructed as follows:

[0074]

[0075] Y The variables represent the semidefinite programming problem.

[0076] Therefore, the positive semi-definite matrix form of the VUF constraint can be expressed as:

[0077]

[0078] tr Represents the trace of a matrix. D This represents the auxiliary matrix for voltage unbalance. A c This represents the voltage unbalance coefficient matrix.

[0079] The linear terms in the objective function are eliminated, and can be expressed as:

[0080]

[0081] obj The objective function of the optimization problem ，A obj This represents the coefficient matrix of the objective function.

[0082] The convexized semidefinite programming problem is represented as follows:

[0083]

[0084] in Y 5,5 express Y The element in the 5th row and 5th column of the matrix. rank This represents the rank of the matrix.

[0085] Note that there is no relaxation gap for second-order cone constraints (rotor current and rotor voltage constraints). However, for VUF constraints, an auxiliary rank constraint rank(Y) = 1 must be introduced. Apart from the rank constraint, the original non-convex problem has been transformed into a semidefinite programming problem solvable by commercial solvers. When the rank constraint holds, the entire problem has no relaxation gap. If the rank constraint does not hold, the original solution can still be approximated using mature techniques (such as eigenvalue decomposition or Gaussian randomization), typically yielding high-precision results.

[0086] S4: Based on the semidefinite programming model, according to the actual active power limit, adaptively coordinate the improvement of active power transmission capacity and the suppression of voltage imbalance. By iteratively adjusting the limit value of voltage imbalance constraint, the calculated active power is less than or equal to the actual active power limit.

[0087] Specifically, in actual operating conditions, active power may be limited by actual wind speed. When active power is insufficient, in addition to providing active power support, it is also necessary to make full use of the remaining available current capacity to attenuate VUF. Therefore, the feasibility of coordinating APTC enhancement and VUF attenuation must be analyzed.

[0088] Reference Figure 4 It describes the geometric relationship between APTC enhancement and VUF attenuation. Figure 4 (a) shows the active power and VUF relative to the rotor current phase angle φ when the rotor negative sequence current is determined. -The relationship is as follows. For regions II and IV, the VUF constraint is not tight because active power increases as VUF decreases, meaning the optimal solution is not in these two regions. Since the output active power and the decaying VUF performance in region I are both worse than in region III, the optimal solution should be located in region III. More precisely, the optimal solution is located at point d when the VUF constraint boundary holds. Figure 4 (b) shows the relationship between active power and VUF relative to the negative sequence rotor current magnitude when the current constraint boundary holds. The VUF constraint is a tight constraint on the optimal APTC enhancement target because the decrease of VUF and the increase of active power are mutually restrictive.

[0089] Reference Figure 5 This is a flowchart of the algorithm for the method of this invention. When the calculated active power... P cal Greater than the actual active power limit P max VUF limit value η Decrease until P cal ≤ P max The iteration step size is set to:

[0090]

[0091] α n The iteration step size, μ The initial compensation coefficient, P cal0 This is the initial calculated active power value. P max is the maximum power limit value, and is the compensation iteration constant.

[0092] The iteration step size is controllable because a larger initial step size can speed up the convergence, while a smaller step size in the later stages can ensure the quality of the final solution.

[0093] As can be seen from the above embodiments, this application establishes an optimal active power transmission capacity improvement model that includes rotor current, rotor voltage, voltage imbalance, and transient stability constraints. Then, by reconstructing the dual-sequence coordinate system and using semi-definite relaxation techniques, the non-convex model is made convex to ensure the global optimality of the solution. Finally, active power transmission improvement and voltage imbalance suppression are adaptively coordinated according to actual power constraints. This invention can fully utilize the power and current capacity of doubly-fed induction generator (DFIG) wind turbines, significantly improving active power output capacity under asymmetrical faults while ensuring safe and stable operation, and effectively suppressing voltage imbalance.

[0094] Corresponding to the aforementioned embodiments of the method for improving the active power transmission capacity of wind turbines under asymmetrical faults, this application also provides embodiments of a device for improving the active power transmission capacity of wind turbines under asymmetrical faults.

[0095] Figure 6 This is a block diagram illustrating a device for enhancing the active power transmission capacity of a wind turbine under asymmetrical fault conditions, according to an exemplary embodiment. (Refer to...) Figure 6 The device includes:

[0096] Model building module 1 is used to build an optimal active power transmission capability improvement model for doubly fed wind turbine generators under asymmetrical faults. The model includes an objective function, rotor current constraints, rotor voltage constraints, voltage imbalance constraints, and transient stability constraints.

[0097] The first convexity processing module 2 is used to, based on the optimal active power transmission capability enhancement model, synchronously rotate the positive-sequence and negative-sequence coordinate systems. d The axes are unified to the grid voltage orientation mode, and the dual-sequence synchronous rotating coordinate system is reconstructed to eliminate the nonlinearity and coupling characteristics caused by the dual-sequence power angular coupling term;

[0098] The second convexity processing module 3 is used to perform second-order cone relaxation transformation on the rotor current constraint and the rotor voltage constraint respectively based on the electrical quantities after the dual-sequence synchronous rotating coordinate system, and to perform semi-positive definite relaxation transformation on the voltage imbalance constraint, construct augmented matrix variables and introduce rank constraints to form a standard semi-positive definite programming problem.

[0099] The adaptive solution module 4 is used to adaptively coordinate the improvement of active power transmission capacity and the suppression of voltage imbalance based on the semidefinite programming model and the actual active power limit. It iteratively adjusts the limit value of voltage imbalance constraint until the calculated active power is less than or equal to the actual active power limit.

[0100] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0101] For the device embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to in the description of the method embodiments. The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this application according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0102] Accordingly, this application also provides an electronic device, including: one or more processors; a memory for storing one or more programs; when the one or more programs are executed by the one or more processors, the one or more processors implement the method for improving the active power transmission capability of wind turbines under asymmetric faults as described above.

[0103] Accordingly, this application also provides a computer-readable storage medium storing computer instructions that, when executed by a processor, implement the method for improving the active power transmission capability of wind turbines under asymmetric faults as described above.

[0104] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and embodiments are to be considered exemplary only, and the true scope and spirit of this application are indicated by the claims.

[0105] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A method for improving the active power transmission capability of wind turbine generators under asymmetrical faults, characterized in that, include: S1: Establish an optimal active power transmission capability improvement model for doubly fed wind turbine generators under asymmetrical faults. The model includes an objective function, rotor current constraints, rotor voltage constraints, voltage imbalance constraints, and transient stability constraints. S2: Based on the aforementioned optimal active power transmission capacity enhancement model, the positive and negative sequence synchronously rotated coordinate systems. d The axes are unified to the grid voltage orientation mode, and the dual-sequence synchronous rotating coordinate system is reconstructed to eliminate the nonlinearity and coupling characteristics caused by the dual-sequence power angular coupling term; S3: Based on the electrical quantities after the dual-sequence synchronous rotating coordinate system, perform second-order cone relaxation transformation on the rotor current constraint and the rotor voltage constraint respectively, perform semi-positive definite relaxation transformation on the voltage imbalance constraint, construct augmented matrix variables and introduce rank constraints to form a standard semi-positive definite programming problem. S4: Based on the semidefinite programming model, according to the actual active power limit, adaptively coordinate the improvement of active power transmission capacity and the suppression of voltage imbalance. By iteratively adjusting the limit value of voltage imbalance constraint, the calculated active power is less than or equal to the actual active power limit.

2. The method according to claim 1, characterized in that: The objective function is expressed as follows: ； Where max represents the maximum value. P s For stator active power, U s+ This is the stator positive sequence voltage. U s− The stator negative sequence voltage, I sd+ For stator positive sequence d shaft current, I sd− For stator negative sequence d shaft current; The stator positive and negative sequence voltages are represented as follows: ； U g This is the grid voltage. K + The positive sequence voltage equivalent coefficient. K − This is the equivalent coefficient for negative sequence voltage. Z e This represents the equivalent order self-impedance. Z c Represents the equivalent sequence coupling impedance; Under the dual-sequence phase-locked loop orientation, the form after the Park transformation is as follows: ； ； r e , x e They represent Z e The real and imaginary parts, r c , x c They represent Z c The real and imaginary parts of S, S+(−) represent the transient stability coefficients corresponding to the positive and negative orders. I sq+(−) Indicates the positive and negative values ​​of the stator q shaft current, I ′ sd+(−) Indicates the positive and negative sequence of the stator d Projection of axis current, I ′ sq+(−) Indicates the positive and negative sequence of the stator q Projection of axis current.

3. The method according to claim 1, characterized in that: The rotor current constraint is expressed as follows: ； x s This indicates the stator inductance of the doubly-fed wind turbine. x m This indicates the mutual inductance of the doubly-fed wind turbine. I rmax Indicates the upper limit of the rotor current; The rotor voltage constraint is expressed as follows: ； s This indicates the slip rate of the doubly-fed wind turbine. σ This represents the leakage magnetic flux coefficient of a doubly-fed fan. U rmax Indicates the upper limit of the rotor voltage; The voltage unbalance constraint is expressed as follows: ； η This indicates the upper limit of voltage imbalance.

4. The method according to claim 1, characterized in that: The stator voltage equation in the reconstructed dual-sequence synchronous coordinate system is expressed as: ； U sd+ Indicates stator positive d shaft voltage, U sd− Indicates stator negative d shaft voltage, U sq+ Indicates stator positive sequence q Shaft voltage; U sq− Indicates stator negative sequence q Shaft voltage; K 1+ , K 2+ They represent K + The real and imaginary parts, K 1− , K 2− They represent K − The real and imaginary parts of , where ^ represents the state components in the reconstructed bi-order coordinate system.

5. The method according to claim 1, characterized in that: The stator voltage equations in the reconstructed dual-sequence synchronous coordinate system are expressed in matrix form: u = Zi + k； u Represents the stator voltage matrix. i Represents the stator current matrix. k Represents the grid voltage matrix; The rotor current constraint is relaxed by a second-order cone relaxation based on Cauchy's inequality, as follows: ； Z I This represents the impedance matrix in rotor current constraints. Q Represents the auxiliary matrix for stator-rotor transformation; Similarly, a second-order cone relaxation is applied to the rotor voltage constraint, as follows: ； Z V This represents the impedance matrix in the rotor voltage constraint. G Represents the rotor voltage auxiliary matrix; Create a positive semidefinite matrix variable, represented as follows: ； Y Variables representing a semidefinite programming problem; A positive semidefinite relaxation transformation is applied to the voltage imbalance constraint, as follows: ； tr Represents the trace of a matrix ，D This represents the auxiliary matrix for voltage unbalance. A c Represents the voltage unbalance coefficient matrix; The linear terms in the objective function are eliminated, as shown below: ； obj The objective function of the optimization problem ，A obj This represents the coefficient matrix of the objective function.

6. The method according to claim 5, characterized in that: The solution to the semidefinite programming problem is expressed as follows: ； in Y 5,5 express Y The element in the 5th row and 5th column of the matrix. rank This represents the rank of the matrix.

7. The method according to claim 1, characterized in that: The voltage imbalance limit value η The iteration step size is set as follows: ； α n The iteration step size, μ The initial compensation coefficient, P cal0 This is the initial calculated active power value. P max This is the maximum power limit value.

8. A device for enhancing the active power transmission capacity of wind turbine generators under asymmetrical faults, characterized in that, include: The model building module is used to build an optimal active power transmission capability improvement model for doubly fed wind turbines under asymmetrical faults. The model includes an objective function, rotor current constraints, rotor voltage constraints, voltage imbalance constraints, and transient stability constraints. The first convexity processing module is used to synchronously rotate the positive-sequence and negative-sequence coordinate systems based on the optimal active power transmission capability improvement model. d The axes are unified to the grid voltage orientation mode, and the dual-sequence synchronous rotating coordinate system is reconstructed to eliminate the nonlinearity and coupling characteristics caused by the dual-sequence power angular coupling term; The second convexity processing module is used to perform second-order cone relaxation transformation on the rotor current constraint and the rotor voltage constraint based on the electrical quantities after the dual-sequence synchronous rotating coordinate system, and to perform semi-positive definite relaxation transformation on the voltage imbalance constraint, constructing augmented matrix variables and introducing rank constraints to form a standard semi-positive definite programming problem. The adaptive solution module is used to adaptively coordinate the improvement of active power transmission capacity and the suppression of voltage imbalance based on the semidefinite programming model and the actual active power limit. It iteratively adjusts the limit value of voltage imbalance constraint until the calculated active power is less than or equal to the actual active power limit.

9. An electronic device, characterized in that, include: One or more processors; Memory, used to store one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any one of claims 1-7.

10. A computer-readable storage medium storing computer instructions thereon, characterized in that, When executed by the processor, this instruction implements the steps of the method as described in any one of claims 1-7.

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