Method for improving active supporting capacity of doubly-fed wind turbine generator under asymmetric fault

Abstract

The invention discloses a doubly-fed wind turbine generator active support capability improvement method under an asymmetric fault, and the method comprises the steps: building a doubly-fed wind turbine generator optimization model with the minimum voltage unbalance degree of a common connection point, and delimiting an optimization problem as two sub-optimization problems: a negative sequence voltage can be eliminated and a negative sequence voltage cannot be eliminated; according to the method, constraint is contracted by using a Kaush-Kuhn-Tuck condition and a geometric analysis method, and an analytical solution form of rotor positive and negative sequence current instructions is obtained, so that the problem of insufficient unbalanced voltage suppression capability under the asymmetric fault of the doubly-fed fan is solved, and the effect of greatly reducing the voltage unbalance degree of the common connection point under the asymmetric fault is achieved. And a reference is provided for improving the active support capability of the doubly-fed fan under the asymmetric fault.

Description

Technical Field

[0001] The present application relates to the field of wind power generation control technology, and in particular to a method for improving the active support capability of a doubly-fed wind turbine generator set under an asymmetric fault. Background Art

[0002] As a core part of the new energy power generation system, wind power generation occupies a significant share in the new power system. However, in recent years, due to unexpected factors such as asymmetric grid failures, voltage imbalance problems have frequently occurred, which poses a severe challenge to the stability of wind power grid connection and threatens the safe and stable operation of the entire power system.

[0003] At present, the grid standard puts forward support requirements for wind farms, that is, when the wind turbine detects an asymmetric fault in the grid, it should inject positive and negative sequence currents into the grid to suppress the unbalanced voltage at the point of common coupling (PCC). As the main type of wind power generation, the doubly fed induction generator (DFIG) is of great significance to improving the grid-connected adaptability of wind power systems by shouldering the responsibility of supporting the grid while operating without disconnecting from the grid.

[0004] At present, the following studies have been conducted on asymmetric fault ride-through of DFIG at home and abroad: ① Reference [[6]Xu Lie. Enhanced Control and Operation of DFIG-Based Wind Farms During Network Unbalance[J], IEEE Transactions on Energy Conversion, 2008, 23(4):1073-1081] proposed a positive and negative sequence current control strategy to eliminate the double frequency oscillation of electromagnetic torque under unbalanced voltage, but increased the risk of overmodulation of the rotor side converter. = 2 \* GB3 ② Reference [Xu Hailiang, Zhang Yufeng, Li Zhi, et al. Reactive current constraints and coordinated control of DFIG'sRSC and GSC during asymmetric grid condition[J]. IEEE Access, 2020,8(1):184339-184349] On the basis of eliminating the double frequency oscillation of electromagnetic torque on the generator side, the controllable current margin of the grid-side converter is used to cooperatively suppress the voltage unbalance factor (VUF) of the PCC. Reference = 3 \* GB3 ③[Chang Yuanzhu, Ilhan Kocar, Hu Jiabing, et al. Coordinated Control of DFIG Converters to Comply with Reactive Current Requirements in Emerging Grid Codes[J]. Journal of Modern Power Systems and Clean Energy, 2022, 10(2):502-514] From the perspective of the positive and negative sequence requirements of the power grid, a DFIG positive and negative sequence instruction allocation strategy based on priority current limiting (positive sequence reactive power, negative sequence reactive power, positive sequence active power) is proposed.

[0005] The acquisition of the above instructions is mostly based on droop control using voltage deviation or PI control using pre-set values, which does not fully utilize the current and voltage capacity of the rotor side and cannot achieve optimal voltage unbalance factor attenuation (OVUFA) of the DFIG. Summary of the invention

[0006] The purpose of the embodiments of the present application is to provide a method for improving the active support capability of a doubly-fed wind turbine generator set under an asymmetric fault, so as to solve the technical problem in the related art that the current and voltage capacity of the DFIG rotor side cannot be fully utilized to achieve optimal voltage imbalance suppression.

[0007] According to a first aspect of an embodiment of the present application, a method for improving the active support capability of a doubly-fed wind turbine generator set under an asymmetric fault is provided, comprising: Establish an optimization model for doubly-fed wind turbines with the voltage imbalance at the common connection point minimized; Based on the doubly-fed wind turbine optimization model, the negative sequence voltage suppression capability of the doubly-fed wind turbine is judged, and the optimization problem is delimited into a sub-optimization problem in which the negative sequence voltage can be completely eliminated and a sub-optimization problem in which the negative sequence voltage cannot be completely eliminated; For the negative sequence voltage total elimination sub-optimization problem, the necessary conditions are obtained using the Karush-Kuhn-Tucker conditions, and the current command is further solved; For the sub-optimization problem that the negative sequence voltage cannot be completely eliminated, the geometric analysis method is used to shrink the constraints, determine the distribution boundary of the optimal solution, and obtain the analytical solution.

[0008] According to a second aspect of an embodiment of the present application, a device for improving active support capability of a doubly-fed wind turbine generator set under an asymmetric fault is provided, comprising: A model building module is used to build a doubly-fed wind turbine optimization model with the voltage imbalance at the common connection point minimized; A definition module is used to judge the negative sequence voltage suppression capability of the doubly fed wind turbine based on the doubly fed wind turbine optimization model, and define the optimization problem into a sub-optimization problem in which the negative sequence voltage can be completely eliminated and a sub-optimization problem in which the negative sequence voltage cannot be completely eliminated; A first solving module is used for obtaining necessary conditions for the negative sequence voltage full elimination sub-optimization problem by using the Karush-Kuhn-Tucker condition, and further solving the current command; The second solution module is used to shrink the constraints of the sub-optimization problem that the negative sequence voltage cannot be completely eliminated by using a geometric analysis method, determine the distribution boundary of the optimal solution, and obtain an analytical solution.

[0009] According to a third aspect of an embodiment of the present application, there is provided an electronic device, characterized in that it includes: 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 as described in the first aspect.

[0010] The technical solution provided by the embodiments of the present application may have the following beneficial effects: It can be seen from the above embodiments that since the present application establishes an optimization model for a doubly fed wind turbine with the voltage imbalance at the common connection point minimized, and defines the optimization problem as two sub-optimization problems in which the negative sequence voltage can be eliminated and cannot be eliminated, the constraints are shrunk using the Karush-Kuhn-Tucker conditions and the geometric analysis method, and the analytical solution form of the rotor positive and negative sequence current instructions is obtained, the problem of insufficient unbalanced voltage suppression capability of the doubly fed wind turbine under asymmetric faults is overcome, thereby achieving the effect of greatly reducing the voltage imbalance at the common connection point under asymmetric faults.

[0011] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0013] Figure 1 It is a flow chart of a method for improving the active support capability of a doubly-fed wind turbine generator set under an asymmetric fault according to an exemplary embodiment.

[0014] Figure 2 The topology diagram of a doubly-fed wind power generation system is shown according to an exemplary embodiment.

[0015] Figure 3 is a diagram showing the relationship between voltage imbalance and rotor positive and negative sequence currents according to an exemplary embodiment.

[0016] Figure 4 is a diagram showing the relationship between voltage imbalance and rotor positive and negative sequence voltages according to an exemplary embodiment.

[0017] Figure 5 is a schematic diagram of geometric characteristics under rotor current constraints according to an exemplary embodiment.

[0018] Figure 6 is a schematic diagram of geometric characteristics under rotor voltage constraints according to an exemplary embodiment.

[0019] Figure 7 is a schematic diagram of geometric characteristics under dual constraints of rotor current and voltage according to an exemplary embodiment.

[0020] Figure 8 It is a block diagram of a device for improving the active support capability of a doubly-fed wind turbine generator set under an asymmetric fault according to an exemplary embodiment. DETAILED DESCRIPTION

[0021] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0022] The terms used in this application are for the purpose of describing specific embodiments only and are not intended to limit this application. The singular forms of "a", "said" and "the" used in this application and the appended claims are also intended to include plural forms unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0023] Figure 1 is a flow chart of a method for improving the active support capability of a doubly-fed wind turbine generator set under an asymmetric fault according to an exemplary embodiment. Figure 1 As shown, the method may include the following steps: S1: Establish an optimization model for a doubly-fed wind turbine with the voltage imbalance at the common connection point minimized; Specifically, Figure 2 The topology diagram of a doubly-fed wind power generation system is shown according to an exemplary embodiment. The DFIG is controlled by the RSC and the stator is directly connected to the external power grid. The positive and negative sequence components are separated by a decoupling dual synchronous phase-locked loop, and the transient flux is obtained by the flux observer. According to the measured state, the control signal is obtained by the method proposed in the present application, and after modulation, it is input into the RSC to control the DFIG.

[0024] When an asymmetric fault occurs in the power grid, due to the excitation of external positive-sequence and negative-sequence sources, the DFIG stator side induces positive-sequence and negative-sequence flux. Due to the slip characteristics caused by the DFIG motor structure, the circuit relationship between the positive-sequence current and voltage on the rotor side can be expressed as: ; ; In the formula L s is the stator inductance, L r is the rotor inductance, L m For mutual induction, σ =1− L 2 m / L s Lr is the magnetic flux leakage coefficient; s is the slip rate; ω 1 is the grid synchronization angular velocity, I r+ and I r- are the positive and negative sequence currents of the rotor respectively, U r+ and U r- are the positive and negative sequence voltages of the rotor respectively, U s+ and U s- They are the positive and negative sequence voltages of the stator respectively; bold indicates vector.

[0025] The positive and negative sequence synchronous rotating coordinate systems are oriented by the positive and negative sequence components of the stator side voltage respectively, and the circuit constraints can be expressed as: ; ; In the formula, L g is the grid inductance; U g+ and U g- are the positive and negative sequence voltages of the power grid respectively; I sd+ and I sd- are the positive and negative sequence active currents of the stator respectively; I sq+ and I sq- are the positive and negative sequence reactive currents of the stator respectively.

[0026] Under asymmetric faults, DFIG should first ensure its own safety, and then inject positive and negative sequence currents into the grid to support the grid voltage. Therefore, DFIG should avoid overcurrent and overmodulation, that is, meet the rotor side current and voltage stress constraints. The optimization model can be expressed as follows: ; Where VUF represents the voltage unbalance, obj represents the optimization target, min represents the minimum, I r+ and I r- are the positive and negative sequence currents of the rotor respectively, U r+ and U r- are the positive and negative sequence voltages of the rotor respectively, max and rmax They are the current and voltage capacity limitations of the rotor respectively.

[0027] Establishing an optimization model for minimum voltage imbalance can maximize the unbalanced voltage suppression capability of DFIG.

[0028] S2: Based on the doubly-fed wind turbine optimization model, the negative sequence voltage suppression capability of the doubly-fed wind turbine is judged, and the optimization problem is delimited into a sub-optimization problem in which the negative sequence voltage can be completely eliminated and a sub-optimization problem in which the negative sequence voltage cannot be completely eliminated; Specifically, the negative sequence voltage suppression capability of DFIG is judged according to the rotor current and voltage capacity that DFIG can allocate, as well as the negative sequence voltage and grid strength, and the optimization problem is delimited into two sub-optimization problems: the negative sequence voltage can be completely eliminated and the negative sequence voltage cannot be completely eliminated.

[0029] If the grid voltage imbalance is low, the negative sequence voltage can be completely eliminated and the VUF can be reduced to 0. The rotor side capacity required for the optimization problem should meet the following requirements: ; ; In the formula I b Indicates the defined rotor current limits.

[0030] On the contrary, if the grid voltage is highly unbalanced and the negative sequence voltage cannot be completely eliminated, the above conditions are not met.

[0031] By delimiting the optimization problem into sub-optimization problems, the calculation accuracy can be improved and the global optimality of the solution can be guaranteed.

[0032] S3: For the negative sequence voltage full elimination sub-optimization problem, the necessary conditions are obtained using the Karush-Kuhn-Tucker conditions, and the current command is further solved; Specifically, it degenerates into a positive sequence support problem with negative sequence constraints, which requires fully supporting the positive sequence voltage of the power grid under the premise of eliminating the negative sequence voltage, that is: ; In the formula, max means the maximum, U g+ and U g- are the positive and negative sequence voltages of the power grid respectively; U sd is the positive sequence d-axis voltage of the stator, U sq+ is the positive sequence q-axis voltage of the stator, I sd is the positive sequence d-axis current of the stator, I sq+ is the positive sequence q-axis current of the stator; I rd+is the positive sequence d-axis current of the rotor, I rq+ is the positive sequence q-axis current of the rotor; U rd+ is the sequence d axis voltage of the rotor, U rq+ is the positive sequence q-axis voltage of the rotor.

[0033] This optimization problem is non-convex due to the existence of square roots and quadratic terms. The classical convex optimization problem solution method cannot guarantee the optimality of the solution. Since the constraints are time-varying, in order to ensure the rapidity of the solution, it is necessary to avoid using heuristic algorithms to search for iterative solutions. The KKT condition is used to further shrink the boundary and simplify the problem, but it should be noted that KKT solves the necessary conditions, not the necessary and sufficient conditions for global optimality. The Lagrangian function of the optimization problem is obtained, and the necessary condition for the optimal positive sequence voltage support is obtained. I rd+ =0, that is, DFIG does not output positive sequence active power. Therefore, the solution to the sub-optimization problem of negative sequence voltage energy elimination can be further obtained.

[0034] ; ; ; In the formula, L The Lagrangian function representing the optimization problem, f represents the objective function, g 1 and g 2 represent constraints, λ1 and λ2 represent Lagrange coefficients, L re is the equivalent inductance. I rq- are the positive and negative sequence q-axis currents of the rotor respectively.

[0035] By further shrinking the constraints through KKT conditions, the computational difficulty of the solution can be reduced while ensuring the global optimality of the solution.

[0036] S4: For the sub-optimization problem that the negative sequence voltage cannot be completely eliminated, the geometric analysis method is used to shrink the constraints, determine the distribution boundary of the optimal solution, and obtain an analytical solution.

[0037] Specifically, if the negative sequence voltage cannot be completely eliminated, the optimization problem can be further expressed as: ; In the formula, U sd- is the negative sequence d-axis voltage of the stator, U sq- is the negative sequence q-axis voltage of the stator; I sd-is the negative sequence d-axis current of the stator; I sq- is the negative sequence q-axis current of the stator; I rd- are the negative sequence d-axis current of the rotor, I rq- are the negative sequence q-axis current of the rotor respectively; U rd- are the negative sequence d-axis voltage of the rotor, U rq- are the negative-sequence q-axis voltage of the rotor respectively.

[0038] Compared with the sub-optimization problem in which the negative-sequence voltage can be completely eliminated, the existence of the VUF quotient form and the introduction of negative-sequence variables make the problem more nonlinear, the dimension higher, and the solution more difficult. Therefore, geometric analysis is used to locate the distribution of the optimal solution and further shrink the constraint boundary. Figure 3 The relationship between the rotor positive and negative sequence current and VUF is given. Figure 4 The relationship between the positive and negative sequence voltages of the rotor and VUF is given. Although the trend of VUF with the rotor side current and voltage margin is different, it can still be concluded that the minimum value of VUF is closely related to the remaining current and voltage margin after RSC demagnetization. The two are inversely proportional in the neighborhood of the optimal value, that is, the larger the current and voltage capacity, the smaller the VUF. The optimal solution falls on the current or voltage constraint boundary, and the inequality constraint can be converted into an equality constraint.

[0039] Previously, the necessary condition for optimal support of positive sequence voltage was given by KKT condition, that is, the positive sequence active current is zero. Similarly, the necessary condition for optimal suppression of negative sequence voltage can also be obtained by KKT condition, that is, the negative sequence active current is zero. Because VUF is defined as the quotient of negative sequence voltage and positive sequence voltage, the minimum connotation of VUF includes the simultaneous realization of positive sequence voltage support and negative sequence voltage suppression under specific constraints. Therefore, DFIG does not output positive and negative sequence active power, which can also be used as a necessary condition for the optimization problem, and the constraints will be further reduced.

[0040] ① If the rotor side current stress is used as the primary constraint to limit the DFIG to suppress the unbalanced voltage, and the rotor side voltage margin is sufficient. That is, the current constraint is a tight constraint, and the voltage constraint is a non-tight constraint. The inequality constraint of the rotor side current stress limitation is transformed into an equality constraint, and VUF can be expressed as: ; Figure 5 The relationship between VUF and negative sequence current amplitude under current constraint is given. In order to better describe the geometric characteristics under current constraint, the feasible region is expanded (such as the dotted line part), and the solid line part is the actual limit of the rotor side current. Figure 5It can be obtained that, under the rotor side current constraint, in order to achieve the optimal suppression of VUF, the entire current capacity should be used for negative sequence voltage suppression. At this time, the rotor positive and negative sequence current instructions are calculated by the following formula: ; = 2 \* GB3 ② If the rotor side voltage stress is the primary constraint for limiting the DFIG to suppress the unbalanced voltage, and the rotor side current margin is sufficient. That is, the voltage constraint is a tight constraint, and the current constraint is a non-tight constraint. The inequality constraint of the rotor side voltage stress limit is transformed into an equality constraint.

[0041] Figure 6 The relationship between VUF and rotor negative sequence voltage under rotor side voltage constraint is given. Figure 6 It can be seen that VUF and the rotor negative sequence voltage amplitude are not one-to-one corresponding, because as the degree of support for the negative sequence voltage at the grid connection point increases, Ur− will change from the same phase to the opposite phase with the negative sequence EMF. Under the voltage constraint on the rotor side, the condition for achieving optimal suppression of VUF is that the rotor negative sequence voltage is zero. At this time, the rotor positive and negative sequence current instructions are calculated by the following formula: ; = 3 \* GB3 ③ If the rotor side current and voltage constraints are also used as tight constraints, the rotor side current and voltage limits are simultaneously transformed from inequality constraints to equality constraints.

[0042] In order to more directly reflect the geometric characteristics under the rotor side current and voltage constraints, variable dimension reduction analysis is performed. Taking the rotor current as the variable, the rotor side voltage constraint is re-expressed, and its feasible domain is Figure 7 As shown in , their intersection is the projection of VUF on the feasible domain surface. Figure 7 It can be seen that the minimum value of VUF falls on the boundary of the rotor side current and voltage. However, there are two intersection points on the boundary of the feasible region of rotor side current and voltage. To ensure the optimality of OVUFA, the feasible solutions are checked one by one, and it is found that the minimum value of VUF is obtained at the intersection point where the negative sequence current is larger. The corresponding rotor positive and negative sequence current instructions are given by the following formula.

[0043] ; It can be seen from the above embodiments that the present application establishes a doubly-fed wind turbine optimization model with the minimum voltage imbalance at the common connection point, and defines the optimization problem into two sub-optimization problems: the negative sequence voltage can be eliminated and cannot be eliminated. The constraints are shrunk by using the Karush-Kuhn-Tucker condition and the geometric analysis method, and the analytical solution form of the rotor positive and negative sequence current instructions is obtained, which overcomes the problem of insufficient unbalanced voltage suppression capability under asymmetric faults of the doubly-fed wind turbine, and thus achieves the effect of greatly reducing the voltage imbalance at the common connection point under asymmetric faults. The above is the method we provide.

[0044] Corresponding to the aforementioned embodiment of the method for improving the active support capability of a doubly-fed wind turbine generator set under an asymmetric fault, the present application also provides an embodiment of a device for improving the active support capability of a doubly-fed wind turbine generator set under an asymmetric fault.

[0045] Figure 8 1 is a block diagram of a device for improving the active support capability of a doubly-fed wind turbine generator set under an asymmetric fault according to an exemplary embodiment. Figure 8 , the device comprises: Model building module 1, used to build a doubly-fed wind turbine optimization model with the voltage imbalance at the common connection point minimized; A definition module 2 is used to judge the negative sequence voltage suppression capability of the doubly fed wind turbine based on the doubly fed wind turbine optimization model, and define the optimization problem into a sub-optimization problem in which the negative sequence voltage can be completely eliminated and a sub-optimization problem in which the negative sequence voltage cannot be completely eliminated; A first solving module 3 is used for obtaining necessary conditions for the negative sequence voltage full elimination sub-optimization problem by using the Karush-Kuhn-Tucker condition, and further solving the current command; The second solution module 4 is used for shrinking the constraints of the sub-optimization problem that the negative sequence voltage cannot be completely eliminated by using a geometric analysis method, determining the distribution boundary of the optimal solution, and obtaining an analytical solution.

[0046] Regarding the device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0047] For the device embodiment, since it basically corresponds to the method embodiment, the relevant parts can refer to the partial description of the method embodiment. The device embodiment described above is only schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present application scheme. A person of ordinary skill in the art can understand and implement it without paying any creative work.

[0048] Correspondingly, the present 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 support capability of a doubly-fed wind turbine generator set under an asymmetric fault as described above.

[0049] Correspondingly, the present application also provides a computer-readable storage medium on which computer instructions are stored, and when the instructions are executed by a processor, the method for improving the active support capability of a doubly-fed wind turbine generator system under an asymmetric fault as described above is implemented.

[0050] Those skilled in the art will readily appreciate other embodiments of the present application after considering the description and practicing the contents disclosed herein. The present application is intended to cover any modification, use or adaptation of the present application, which follows the general principles of the present application and includes common knowledge or customary techniques in the art that are not disclosed in the present application. The description and examples are intended to be exemplary only, and the true scope and spirit of the present application are indicated by the claims.

[0051] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A method for improving the active support capability of a doubly-fed wind turbine generator set under asymmetric faults, characterized in that: include: Establish an optimization model for doubly-fed wind turbines with the voltage imbalance at the common connection point minimized; Based on the doubly-fed wind turbine optimization model, the negative sequence voltage suppression capability of the doubly-fed wind turbine is judged, and the optimization problem is delimited into a sub-optimization problem in which the negative sequence voltage can be completely eliminated and a sub-optimization problem in which the negative sequence voltage cannot be completely eliminated; For the negative sequence voltage total elimination sub-optimization problem, the necessary conditions are obtained using the Karush-Kuhn-Tucker conditions, and the current command is further solved; For the sub-optimization problem that the negative sequence voltage cannot be completely eliminated, the geometric analysis method is used to shrink the constraints, determine the distribution boundary of the optimal solution, and obtain the analytical solution.

2. The method according to claim 1, characterized in that: The doubly-fed wind turbine optimization model is as follows: ； In the formula, obj represents the optimization target, min represents the minimum, st represents the constraint condition; VUF represents the voltage unbalance; I r+ and I r- are the positive and negative sequence currents of the rotor respectively; U r+ and U r- are the positive and negative sequence voltages of the rotor respectively, max and rmax They are the current and voltage capacity limitations of the rotor respectively.

3. The method according to claim 1, characterized in that: The delimitation conditions for defining the optimization problem into the sub-optimization problem where the negative sequence voltage can be completely eliminated and the sub-optimization problem where the negative sequence voltage cannot be completely eliminated are as follows: ； ； In the formula L s is the stator inductance, L r is the rotor inductance, L m For mutual induction, σ =1− L 2 m / L s L r is the magnetic flux leakage coefficient; s is the slip rate; ω 1 is the grid synchronization angular velocity, L g is the grid inductance; max and rmax are the current and voltage capacity limits of the rotor, I b is the defined current boundary.

4. The method according to claim 1, characterized in that: For the negative sequence voltage full elimination sub-optimization problem, the necessary conditions are obtained using the Karush-Kuhn-Tucker condition, and the Lagrangian function of the optimization problem is obtained. The necessary conditions for the optimal positive sequence voltage support are solved as follows: I rd+ =0, that is, the doubly fed wind turbine does not output positive sequence active power; further solving the negative sequence voltage can completely eliminate the solution of the sub-optimization problem: ； In the formula L s is the stator inductance, L r is the rotor inductance, L m For mutual induction, σ =1− L 2 m / L s L r is the magnetic flux leakage coefficient; s is the slip rate; ω 1 is the grid synchronization angular velocity, L g is the grid inductance; U g+ and U g- are the positive and negative sequence voltages of the power grid respectively; I rq+ and I rq- are the positive and negative sequence q-axis currents of the rotor respectively; L g is the equivalent inductance; max and rmax They are the current and voltage capacity limitations of the rotor respectively.

5. The method according to claim 1, characterized in that For the sub-optimization problem that the negative sequence voltage cannot be completely eliminated, the geometric analysis method is used to shrink the constraints, determine the distribution boundary of the optimal solution, and obtain the analytical solution; if the negative sequence voltage cannot be completely eliminated, the optimization problem is further expressed as: ； In the formula obj represents the optimization target, min represents the minimum, st Indicates constraints; L s is the stator inductance, L r is the rotor inductance, L m For mutual induction, σ =1− L 2 m / L s L r is the magnetic flux leakage coefficient; s is the slip rate; ω 1 is the grid synchronization angular velocity, L g is the grid inductance; U g+ and U g- are the positive and negative sequence voltages of the power grid respectively; U sd+ and U sd- are the positive and negative sequence d-axis voltages of the stator, U sq+ and U sq- are the positive and negative sequence q-axis voltages of the stator, respectively. I sd+ and I sd- are the positive and negative sequence d-axis currents of the stator respectively; I sq+ and I sq- are the positive and negative sequence q-axis currents of the stator respectively; I rd+ and I rd- are the positive and negative sequence d-axis currents of the rotor respectively, I rq+ and I rq- are the positive and negative sequence q-axis currents of the rotor respectively, U rd+ and U rd- are the positive and negative sequence d-axis voltages of the rotor respectively, U rq+ and U rq- are the positive and negative sequence q-axis voltages of the rotor respectively, max and rmax They are the current and voltage capacity limits of the rotor respectively; By using geometric analysis to locate the distribution of the optimal solution and further shrinking the constraint boundary, it is found that the minimum VUF is closely related to the remaining current and voltage margin after demagnetization of the rotor-side converter. VUF and the rotor converter capacity margin are inversely proportional in the neighborhood of the optimal value, that is, the larger the current and voltage capacity, the smaller the VUF. The optimal solution falls on the current or voltage constraint boundary, converting the inequality constraint into an equality constraint.

6. The method according to claim 5, characterized in that If the rotor side current stress is used as the primary constraint to limit the unbalanced voltage of the doubly fed wind turbine, the inequality constraint of the rotor side current stress limitation is transformed into an equality constraint. At this time, VUF is expressed as: ； Where VUF represents the voltage unbalance; L s is the stator inductance, L r is the rotor inductance, L m For mutual induction; s is the slip rate; ω 1 is the grid synchronization angular velocity, L g is the grid inductance; U g+ and U g- are the positive and negative sequence voltages of the power grid respectively; max and rmax They are the current and voltage capacity limits of the rotor respectively; Under the rotor side current constraint, in order to achieve the optimal suppression of VUF, the entire current capacity should be used for negative sequence voltage suppression; at this time, the rotor side current command is calculated by the following formula: ； In the formula I rq+ and I rq- are the positive and negative sequence q-axis currents of the rotor respectively, max This is the current capacity limit of the rotor.

7. The method according to claim 5, characterized in that If the rotor side voltage stress is used as the primary constraint to limit the DFIG to suppress the unbalanced voltage, the inequality constraint of the rotor side voltage stress limitation is transformed into an equality constraint; VUF and the rotor negative sequence voltage amplitude are not one-to-one corresponding, because as the degree of negative sequence voltage support at the grid connection point increases, U r− It will change from the same phase to the opposite phase with the negative sequence EMF; under the voltage constraint on the rotor side, the condition for achieving optimal VUF suppression is that the rotor negative sequence voltage is zero; at this time, the command is calculated by the following formula: ； In the formula L s is the stator inductance, L r is the rotor inductance, L m For mutual induction; s is the slip rate; ω 1 is the grid synchronization angular velocity, L g is the grid inductance, L re is the equivalent inductance; U g+ and U g- are the positive and negative sequence voltages of the power grid respectively; rmax This is the voltage capacity limit of the rotor.

8. The method according to claim 5, characterized in that If the rotor side current and voltage constraints are used as tight constraints at the same time, the rotor side current and voltage limits are transformed from inequality constraints to equality constraints at the same time; the minimum value of VUF falls on the boundaries of the rotor side current and voltage, but there are two intersection points on the boundaries of the feasible domain of the rotor side current and voltage. To ensure the optimality of OVUFA, the feasible solutions are checked one by one, and it is found that the minimum value of VUF is obtained at the intersection point with a larger negative sequence current. The corresponding current command is given by the following formula: ； In the formula L s is the stator inductance, L r is the rotor inductance, L m For mutual induction, L re is the equivalent inductance; s is the slip rate; ω 1 is the grid synchronization angular velocity, L g is the grid inductance; U g+ and U g- are the positive and negative sequence voltages of the power grid respectively; I rq+ and I rq- are the positive and negative sequence q-axis currents of the rotor respectively; max and rmax They are the current and voltage capacity limitations of the rotor respectively.

9. A device for improving the active support capacity of a doubly-fed wind turbine generator set under asymmetric faults, characterized in that: include: A model building module is used to build a doubly-fed wind turbine optimization model with the voltage imbalance at the common connection point minimized; A definition module is used to judge the negative sequence voltage suppression capability of the doubly fed wind turbine based on the doubly fed wind turbine optimization model, and define the optimization problem into a sub-optimization problem in which the negative sequence voltage can be completely eliminated and a sub-optimization problem in which the negative sequence voltage cannot be completely eliminated; A first solving module is used for obtaining necessary conditions for the negative sequence voltage full elimination sub-optimization problem by using the Karush-Kuhn-Tucker condition, and further solving the current command; The second solution module is used to shrink the constraints of the sub-optimization problem that the negative sequence voltage cannot be completely eliminated by using a geometric analysis method, determine the distribution boundary of the optimal solution, and obtain an analytical solution.

10. An electronic device, characterized in that: include: 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 according to any one of claims 1 to 8.

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