A flexible interconnection converter control stability improvement method, system, device and medium

Abstract

The application discloses a flexible interconnected converter control stability improvement method, system, device and medium, comprising: establishing a large signal average model of an AC / DC interface unit; constructing a dynamic limiting boundary according to a DC side power shortage and a DC bus energy recovery demand, and conditionally increasing a d-axis current reference limiting value within a short-time overcurrent range allowed by a device; equivalent the dynamic limiting to a time-varying saturation gain, establishing a T-S fuzzy model considering the dynamic limiting and a constant power load, and estimating an attraction domain of a target working point based on a Lyapunov function and a linear matrix inequality; introducing a counter-calculation feedback type anti-saturation link matched with the dynamic limiting, so as to inhibit voltage outer loop integral accumulation. The application can improve the transient active power support capability of the flexible interconnected converter in the large disturbance recovery stage, improve the DC bus voltage recovery process, and expand the recoverable range of the target working point without changing the basic structure of the original double closed loop control.

Description

Technical Field

[0001] This invention relates to the field of power electronic converter control technology, and in particular to a method, system, device and medium for improving the control stability of flexible interconnected converters. Background Technology

[0002] With the development of new power systems, the high proportion of power electronic equipment and the integration of various types of DC loads have led to a deep coupling between power sources, grids, loads, and energy storage in power distribution systems. Flexible interconnected converters, as key equipment, play a crucial role in power coordination and voltage support in AC / DC hybrid power distribution systems. In typical double-ended flexible DC power distribution systems, when large disturbances such as sudden load increases or source-load mismatch occur, the system power balance is disrupted, and the release of stored energy from the DC bus capacitors causes a voltage drop. At this time, the transient active power support capability of the AC / DC interface unit, which is responsible for voltage support, is limited by the current limiting mechanism of the controller.

[0003] In commonly used dual-loop control structures in engineering, the fixed current limit set for protecting devices restricts the system's short-term active power output during the strong disturbance recovery phase. When the fixed limit value is lower than the recovery requirement, the converter cannot provide sufficient power compensation, resulting in a difficult-to-recover energy loss in the DC link, especially under constant power loads. Simultaneously, the fixed limit causes a mismatch between the controller's internal recovery requirements and actual execution capability, leading to voltage outer loop integral saturation. This results in overshoot, oscillation, or recovery hysteresis in the system during the exit phase of the limit setting, affecting transient stability.

[0004] Therefore, there is an urgent need for a method that can dynamically adjust the limiting boundary based on system power deficit and energy recovery requirements without altering the traditional dual-closed-loop control structure. This method needs to address the insufficient support capability and integral saturation issues caused by fixed limiting, and quantify its impact on the system's recoverable range through large-signal stability analysis, thereby improving the recovery capability and transient stability of flexible interconnected converters under large disturbance conditions. Summary of the Invention

[0005] In view of the aforementioned existing problems, the present invention is proposed.

[0006] Therefore, this invention provides a method, system, device, and medium for improving the control stability of flexible interconnected converters. This addresses the problem that in the dual closed-loop control of flexible interconnected converters, the use of a fixed current limiting strategy leads to insufficient transient active power support under large disturbance conditions, controller integral saturation, and consequently, difficulty in DC bus voltage recovery and system transient instability.

[0007] To solve the above-mentioned technical problems, the present invention provides the following technical solution: In a first aspect, the present invention provides a method for improving the control stability of a flexible interconnected converter, comprising: Obtain the DC bus voltage and AC side electrical quantities, establish a large signal average model of the AC-DC interface unit on the constant DC bus voltage side, and calculate the DC side load power, power deficit, and DC bus energy recovery requirements. Based on the power deficit and DC bus energy recovery requirements, a dynamic limiting boundary is constructed within the short-time overcurrent range allowed by the device, and the direct-axis current reference value output by the outer voltage loop is dynamically limited to obtain the direct-axis current command value. By combining the characteristics of the dynamic limiting element with the characteristics of the constant power load, large-signal stability analysis is performed, the feasible region of the anti-saturation feedback gain is solved, and the design constraints of the anti-saturation element are generated. In the dynamic limiting process, a back-calculation feedback anti-saturation stage is introduced. The anti-saturation feedback gain is tuned using the design constraints. The direct-axis current command value after dynamic limiting and anti-saturation correction is input into the inner current loop to generate the converter modulation voltage command.

[0008] As a preferred embodiment of the method for improving the control stability of the flexible interconnected converter described in this invention, the step of establishing a large-signal averaging model of the AC-DC interface unit on the constant DC bus voltage side includes: Modeling preparation is carried out based on physical topology, and an equivalent circuit including AC power supply, filter inductor, converter, DC bus capacitor and DC load is constructed. Based on the topological relationship of the equivalent circuit, the analysis is performed in a synchronous rotating coordinate system. The dynamic process in the circuit is represented as a state-space equation, in which the AC side voltage, current and the projection components of the switching function in the coordinate system are recorded as state variables. Based on the state-space equation framework, specific load characteristic constraints are introduced, the DC-side load is set as a constant power load, and the mathematical relationship between the load current, DC bus voltage and power value is determined according to the definition of constant power load, thus completing the establishment of the large-signal average model.

[0009] As a preferred embodiment of the method for improving the control stability of flexible interconnected converters according to the present invention, the construction of the dynamic limiting boundary includes: Based on the analysis of the energy balance relationship on the DC side, the critical active current required to prevent the bus voltage from continuing to drop is calculated, and the additional recovery power required by the system during the preset bus voltage recovery time is further calculated. The critical active current is superimposed with the additional recovery power requirement to obtain the total direct-axis active current required by the converter during the large disturbance recovery phase. Based on the total direct-axis active current, a time-varying limiting boundary is dynamically constructed between the device's allowable short-time maximum overcurrent limit and the fixed limiting value under normal operating conditions.

[0010] As a preferred embodiment of the flexible interconnected converter control stability improvement method of the present invention, the step of performing large-signal stability analysis includes: The dynamic limiting circuit is equivalent to a time-varying saturation gain, and the working mechanism of the limiting circuit is characterized by the state of the time-varying saturation gain. Based on the equivalent time-varying saturation gain, a TS fuzzy model is established, which includes a constant power load reciprocal nonlinear term and a dynamic limiting saturation gain nonlinear term. A local linear model is constructed by a two-endpoint sector partitioning algorithm, and a global model is obtained by normalizing the membership function. Based on the global model, combined with Lyapunov functions and linear matrix inequalities, the attraction domain of the target operating point is estimated. By comparing the changing trends of the attraction domain cross section under different saturation gain values, the recoverable range of the system under large disturbances is determined.

[0011] As a preferred embodiment of the method for improving the control stability of the flexible interconnected converter described in this invention, the method of introducing a back-calculation feedback anti-saturation element includes: Calculate the deviation between the reference value of the direct-axis current output without voltage limiting in the outer voltage loop and the actual direct-axis current command value after dynamic limiting; The deviation is fed back to the input terminal of the integrator branch of the outer voltage loop, and a negative feedback term is generated using the deviation when the system enters the limiting region; Based on the proportional relationship between the voltage outer loop integral time constant and the amplitude limiting process tracking time constant, the anti-saturation feedback gain corresponding to the negative feedback term is tuned.

[0012] The beneficial effects of this preferred technical solution are that by introducing a back-calculation feedback anti-saturation mechanism, the voltage outer loop integral term can be actively corrected in real time using the limiting deviation, effectively suppressing the integral saturation phenomenon caused by dynamic limiting, thereby significantly accelerating the system's recovery speed from saturation and improving the converter's dynamic response performance and stability under large disturbances.

[0013] As a preferred embodiment of the method for improving the control stability of the flexible interconnected converter described in this invention, the step of tuning the anti-saturation feedback gain using the design constraints includes: Based on the TS fuzzy model and Lyapunov stability conditions, feasible solutions to the linear matrix inequalities that make the system asymptotically stable are obtained. The feasible region of the anti-saturation feedback gain is determined by incorporating it as an optimization variable into the linear matrix inequality constraints obtained from the solution. Based on the feasible region, in the simulation, in response to the system recovery time being greater than a preset time threshold, the anti-saturation feedback gain is adjusted based on the system recovery process; In response to system oscillations near the limiting boundary, negative feedback adjustment is performed on the anti-saturation feedback gain based on the system oscillation state until the stability requirements after dynamic limiting and anti-saturation correction are met.

[0014] The beneficial effects of this preferred technical solution are that by combining linear matrix inequality solving with dynamic simulation feedback, the theoretical feasible region of anti-saturation gain can be scientifically defined, and on this basis, adaptive and precise tuning can be performed according to the system recovery speed and oscillation state, achieving the optimal balance between system dynamic recovery performance and robustness while ensuring the stability of large signals.

[0015] As a preferred embodiment of the method for improving the control stability of flexible interconnected converters according to the present invention, wherein: the generation of converter modulation voltage commands includes: The direct-axis current command value obtained after dynamic limiting and anti-saturation correction is used as the input signal of the inner current loop. Combining the quadrature-axis current command value of the inner current loop with the direct-axis current command value input in the previous step, direct-axis and quadrature-axis modulated voltage components are generated through proportional-integral control. The modulated voltage component is used to generate the drive signal for the converter switching transistor using space vector pulse width modulation technology.

[0016] Secondly, the present invention provides a flexible interconnected converter control stability improvement system, comprising: The demand calculation module is used to obtain the DC bus voltage and AC side electrical quantities, establish a large signal average model of the AC to DC interface unit on the constant DC bus voltage side, and calculate the DC side load power, power deficit and DC bus energy recovery demand. The current limiting module is used to construct a dynamic limiting boundary within the short-time overcurrent range allowed by the device according to the power deficit and DC bus energy recovery requirements, and to dynamically limit the direct-axis current reference value output by the voltage outer loop to obtain the direct-axis current command value. The constraint generation module is used to combine the characteristics of the dynamic limiting element with the characteristics of the constant power load to perform large signal stability analysis, solve the feasible region of the anti-saturation feedback gain, and generate the design constraints of the anti-saturation element. The modulation command generation module is used to introduce a back-calculation feedback anti-saturation link during dynamic limiting. It uses the design constraints to tune the anti-saturation feedback gain and inputs the direct-axis current command value after dynamic limiting and anti-saturation correction into the inner current loop to generate the converter modulation voltage command.

[0017] Thirdly, the present invention provides an electronic device, comprising: Memory, used to store programs; a processor, configured to execute the computer-executable instructions, where the computer-executable instructions, when executed by the processor, implement the steps of the method for improving control stability of the flexible interconnection converter.

[0018] In a fourth aspect, the present invention provides a computer-readable storage medium, wherein when the program is executed by a processor, the steps of the aforementioned method for improving control stability of the flexible interconnection converter are implemented.

[0019] The beneficial effects of the present invention are as follows: the present invention does not change the basic structure of the conventional double closed-loop control consisting of an outer voltage loop and an inner current loop, only dynamically reconstructs the output limiting boundary of the outer voltage loop, which has low engineering implementation difficulty and is convenient to deploy in the existing flexible interconnection converter control system; the dynamic limiting boundary is constructed starting from the power deficit and the DC bus energy recovery demand, so that the limiting value can be increased for a short time along with the large disturbance recovery demand, and more transient active power support capability is released on the premise of not exceeding the allowable short-time overcurrent upper limit of the device; the dynamic limiting is equivalent to a time-varying saturation gain and embedded into the T-S fuzzy model (T-S Fuzzy Model), so that the change of control constraints can be incorporated into a unified large-signal stability analysis framework; the domain of attraction of the target operating point is estimated through a Lyapunov function and a linear matrix inequality, which can characterize the difference in the recoverable range of the system under the conditions of fixed limiting and dynamic limiting from the perspective of large signals; the anti-windup design matched with the dynamic limiting is introduced, which can suppress the integral accumulation of the outer voltage loop, reduce the bus voltage overshoot and recovery hysteresis in the limiting exit stage, and improve the actual operation performance of the dynamic limiting strategy. Brief Description of the Drawings

[0020] In order to illustrate the technical solutions of the embodiments of the present invention more clearly, the drawings that need to be used in the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention, and for those of ordinary skill in the art, other drawings can also be obtained based on these drawings without any creative effort. Wherein: Figure 1 is a schematic diagram of the basic process of a method for improving control stability of a flexible interconnection converter provided by an embodiment of the present invention; Figure 2 is a schematic diagram of the judgment process of a method for improving control stability of a flexible interconnection converter provided by an embodiment of the present invention; Figure 3 is a timing diagram of a method for improving control stability of a flexible interconnection converter provided by an embodiment of the present invention; Figure 4 is a state space average model diagram of a typical AC / DC interface unit under a constant power load for the method for improving control stability of a flexible interconnection converter provided by an embodiment of the present invention; Figure 5This is a trend diagram of the attraction domain variation under different λmin values ​​for a method to improve the control stability of a flexible interconnected converter, provided in one embodiment of the present invention. Figure 6 The simulation waveform (OP1→OP2) under fixed amplitude is shown in an embodiment of the present invention for a method to improve the control stability of a flexible interconnected converter. Figure 7 A diagram showing the d-axis current and its command value (OP1→OP2) under fixed amplitude limiting in a method for improving the control stability of a flexible interconnected converter according to an embodiment of the present invention. Figure 8 The simulation waveform (OP1→OP2) under dynamic limiting is provided for a method to improve the control stability of a flexible interconnected converter according to an embodiment of the present invention. Figure 9 A diagram showing the d-axis current and its command value (OP1→OP2) under dynamic limiting in a method for improving the control stability of a flexible interconnected converter, provided in an embodiment of the present invention. Figure 10 The simulation waveform (OP1→OP3) under fixed amplitude is shown in an embodiment of the present invention for a method to improve the control stability of a flexible interconnected converter. Figure 11 A diagram showing the d-axis current and its command value (OP1→OP3) under fixed limiting in a method for improving the control stability of a flexible interconnected converter according to an embodiment of the present invention. Figure 12 The simulation waveform (OP1→OP3) under dynamic limiting is provided for a method to improve the control stability of a flexible interconnected converter according to an embodiment of the present invention. Figure 13 A diagram showing the d-axis current and its command value (OP1→OP3) under dynamic limiting in a method for improving the control stability of a flexible interconnected converter, provided in an embodiment of the present invention. Figure 14 A comparison of outer loop output and d-axis current command values ​​under dynamic limiting (OP1→OP2) of a method for improving the control stability of a flexible interconnected converter provided in an embodiment of the present invention; Figure 15 The simulation waveforms (OP1→OP2→OP4) of a flexible interconnected converter control stability improvement method provided in an embodiment of the present invention, without considering anti-saturation, are shown. Figure 16 The figure shows the simulation waveforms (OP1→OP2→OP4) of a method for improving the control stability of a flexible interconnected converter according to an embodiment of the present invention, considering the dynamic limiting to resist saturation during sudden load reduction. Detailed Implementation

[0021] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0022] Example 1, referring to Figures 1-3 As an embodiment of the present invention, a method for improving the control stability of a flexible interconnected converter is provided, comprising: S100: Obtain DC bus voltage and AC side electrical quantities, establish a large signal average model of the AC-DC interface unit on the constant DC bus voltage side, and calculate the DC side load power, power deficit, and DC bus energy recovery requirements. S200: Based on the power deficit and DC bus energy recovery requirements, construct a dynamic limiting boundary within the short-time overcurrent range allowed by the device, and dynamically limit the direct-axis current reference value output by the voltage outer loop to obtain the direct-axis current command value. S300: Combines the characteristics of dynamic limiting circuit with constant power load characteristics to perform large signal stability analysis, solves the feasible region of anti-saturation feedback gain, and generates design constraints for anti-saturation circuit. S400: In the dynamic limiting process, a back-calculation feedback anti-saturation link is introduced. The anti-saturation feedback gain is tuned using the design constraints. The direct-axis current command value after dynamic limiting and anti-saturation correction is input into the inner current loop to generate the converter modulation voltage command.

[0023] It should be noted that flexible interconnected converters, as key power conversion and control devices in dual-ended flexible DC distribution systems, operate under extremely complex conditions. When large disturbances occur, such as sudden load increases, power redistribution, or source-load mismatch, the system's original power balance can be disrupted in a short time, leading to a DC bus voltage drop and posing a severe challenge to the converter's transient support capabilities. Existing AC / DC interface units on the constant DC bus voltage side generally employ a dual closed-loop control structure. Due to device safety limitations, a fixed current limiting circuit is typically installed between the outer voltage loop and the inner current loop. This fixed limiting mechanism restricts the system's available short-term active power support capacity within static boundaries during large disturbance recovery. This results in the converter being unable to provide sufficient AC input power to compensate for the DC power deficit, causing the DC bus energy loss to be difficult to recover in a timely manner, and voltage recovery to be slow or even unstable. At the same time, the fixed limiting also causes a continuous mismatch between the controller's internal recovery requirements and actual execution capabilities, leading to integral saturation of the voltage outer loop PI controller. This results in significant bus voltage overshoot, oscillation, or recovery lag during the exit limiting phase, severely affecting the dynamic recovery performance and transient stability of the flexible interconnected converter under large disturbance conditions.

[0024] Therefore, addressing the aforementioned issues in flexible interconnected converters using a fixed current limiting strategy in dual-loop control, which leads to insufficient transient active power support under large disturbance conditions, controller integral saturation, and consequently, difficulties in DC bus voltage recovery and system transient instability, the following steps (S100-S400) are employed. By constructing a TS fuzzy model incorporating dynamic limiting and constant power load characteristics, combined with Lyapunov stability analysis, the current limiting boundary can be reconstructed online based on power deficit and energy recovery requirements without altering the traditional dual-loop control structure. This enhances transient active power support capability, while the back-calculation feedback-type anti-saturation element suppresses integral accumulation. Consequently, the problems of slow DC bus voltage recovery, overshoot, and instability under large disturbances are effectively resolved, significantly improving the transient stability and recoverable range of the target operating point of the flexible interconnected converter.

[0025] Example 2, refer to Figures 4-5 As one embodiment of the present invention, based on the previous embodiment, a method for improving the control stability of a flexible interconnected converter is provided, comprising: In this embodiment of the application, step S100, which establishes a large-signal averaging model for the AC-DC interface unit on the constant DC bus voltage side, includes: Modeling preparation is based on the physical topology, constructing an equivalent circuit including AC power supply, filter inductor, converter, DC bus capacitor, and DC load, such as... Figure 4 As shown; Based on the topological relationship of the equivalent circuit, the analysis is carried out in a synchronous rotating coordinate system. The dynamic process in the circuit is represented as a state-space equation, in which the AC side voltage, current and the projection components of the switching function in the coordinate system are recorded as state variables. Based on the state-space equation framework, specific load characteristic constraints are introduced, and the DC-side load is set as a constant power load. According to the definition of constant power load, the mathematical relationship between load current, DC bus voltage and power value is determined, and the large-signal average model is established.

[0026] In this embodiment, a TS fuzzy model considering dynamic limiting and constant power load is established. Since the constant power load introduces reciprocal nonlinearity and the dynamic limiting introduces saturation gain nonlinearity, the system no longer only contains state variable product nonlinearity. Therefore, it is necessary to construct a TS fuzzy model that includes the equivalent saturation gain of dynamic limiting.

[0027] The system state variables are: The DC-side load current of a constant power load satisfies: The average value model of the system in the dq synchronous rotating coordinate system can be written as: In the control equations after introducing dynamic limiting, the outer voltage loop output can be written as: in, This is the reference value for the d-axis current of the unlimited output voltage outer loop. This is the reference value for the DC bus voltage. and These are the proportional and integral coefficients of the outer voltage loop, respectively. This represents the voltage outer loop integral state.

[0028] Introducing equivalent saturation gain Then we have: in, This indicates that the outer loop output has not entered the saturation region. This indicates that the dynamic limiting is in effect. These are not system state variables, but rather prerequisite variables for subsequent TS fuzzy modeling.

[0029] The modulation functions for the d-axis and q-axis are: in, This is the proportionality coefficient for the inner current loop. The integral coefficient of the inner current loop; To synchronize rotational angular velocity, For AC side filter inductance, The equivalent resistance on the AC side; , These are the integral state variables of the d-axis and q-axis current regulators, respectively.

[0030] After the introduction of dynamic limiting, the system control structure itself remains unchanged, but an additional layer is added before the outer loop output enters the inner loop. The process of refactoring control constraints is described.

[0031] In this embodiment of the application, the construction of the dynamic limiting boundary in step S200 includes: Based on the analysis of the energy balance relationship on the DC side, the critical active current required to prevent the bus voltage from continuing to drop is calculated, and the additional recovery power required by the system during the preset bus voltage recovery time is further calculated. By superimposing the critical active current with the additional recovery power requirement, the total direct-axis active current required by the converter during the large disturbance recovery phase is obtained. Based on the total direct-axis active current, a time-varying limiting boundary is dynamically constructed between the device's allowable short-time maximum overcurrent limit and the fixed limiting value under normal operating conditions.

[0032] In an optional implementation, the construction method of the dynamic limiting boundary in step S200 can also collect the deviation of DC bus voltage and its rate of change in real time, calculate the instantaneous active current compensation amount by combining virtual inertia and virtual damping coefficient, and superimpose it on the base current reference value to form a current limiting boundary that is dynamically adjusted according to the degree of voltage drop.

[0033] In an optional implementation, the dynamic current limiting boundary in step S200 can also be constructed by real-time acquisition of the deviation and rate of change of the DC bus voltage as input variables, online reasoning and defuzzification through a preset fuzzy rule base, and direct output of a dynamic current limiting boundary that adaptively adjusts according to the degree of system disturbance.

[0034] In this embodiment of the application, the step of constructing the dynamic amplitude limiting boundary in step S200 includes the following mathematical derivation process: Based on the DC-side energy balance relationship, establish the AC-side input power... DC-side load power The relationship between the capacitor's energy storage rate and the voltage-oriented coordinate system; neglecting converter losses and operating with a unity power factor, the formula for calculating the AC input power is: The expression for DC-side capacitor energy storage is: The average power balance relationship during the large disturbance phase is as follows: The critical condition for preventing the bus voltage from continuing to decline (i.e., the energy stored in the capacitor no longer decreases) and the corresponding minimum d-axis active current. for: in, This is the power of a constant power load.

[0035] Calculate a given recovery time Additional recovery power requirements within To replenish the energy lost during the fall: By superimposing the critical active current with the additional recovery power requirement, a reference value for the d-axis active current required during the large disturbance recovery phase can be obtained. : Dynamic limit value Defined as a fixed amplitude limit under normal operating conditions With respect to the maximum short-time overcurrent limit allowed by converter devices Dynamic boundaries between: As can be seen from the above formula, the dynamic limiting value in this embodiment is not a time-varying curve set by humans, but a physical quantity determined by the real-time load power supply demand and DC bus energy recovery demand. It can automatically increase the limiting boundary under large disturbances and release more transient active power support capacity.

[0036] In this embodiment of the application, step S300 involves large-signal stability analysis, including: The dynamic limiting stage is equivalent to a time-varying saturation gain, and the working mechanism of the limiting stage is characterized by the state of the time-varying saturation gain. Based on the equivalent time-varying saturation gain, a TS fuzzy model is established, which includes a constant power load reciprocal nonlinear term and a dynamic limiting saturation gain nonlinear term. A local linear model is constructed by a two-endpoint sector partitioning algorithm, and a global model is obtained by normalizing the membership function. Based on a global model, combined with Lyapunov functions and linear matrix inequalities, the attraction domain of the target operating point is estimated. By comparing the changing trends of the attraction domain cross-section under different saturation gain values, the recoverable range of the system under large disturbances is determined. Figure 5 As shown.

[0037] In an optional implementation, the large-signal stability analysis in step S300 can also be performed by selecting a large number of initial state points on the system phase plane for forward time-domain simulation, or by integrating backward along time from near the equilibrium point, and by numerically depicting the stability boundary of the system to estimate the attraction domain of the target operating point and determine the system stability under large disturbances.

[0038] In an optional implementation, the large-signal stability analysis in step S300 can also model the converter system including dynamic limiting as a piecewise linear or hybrid logic dynamic system. By constructing a polyhedron or piecewise quadratic Lyapunov function, the polyhedral invariant set of the system can be solved, thereby achieving the estimation of the attraction domain of the target operating point and the determination of stability.

[0039] In this embodiment of the application, before performing the above-mentioned large signal stability analysis, it is necessary to introduce error variables to shift the system equilibrium point to the vicinity of the coordinate origin, so as to facilitate subsequent model derivation and stability proof.

[0040] The target work point is defined as follows: The expression for the steady-state value of the operating point is as follows: Introducing error variables: Substituting the voltage outer loop equation into the error variable, we get: After sorting, we can obtain: Based on steady-state relations, it can be written as: Therefore, the integral state equation of the inner loop of the d-axis current is: From the above derivation, it can be seen that as long as When the deviation from 1, i.e., when the amplitude limit is triggered, an affine term will naturally appear in the error model. In other words, under fixed operating point error coordinates, after the introduction of dynamic limiting, the system no longer maintains a simple homogeneous form, which provides a theoretical basis for the subsequent construction of a TS fuzzy model containing affine terms.

[0041] After substituting the above error variables and control equations into the system average value model, the state equations can be reorganized into a unified form, as shown below: Because the DC bus voltage equation appears The nonlinear term, dynamic limiting, introduces a saturated equivalent gain. Therefore, the system contains not only state variable product nonlinearity, but also reciprocal nonlinearity and limit sector nonlinearity. In this case, it is more suitable to write the system model as a parameter-dependent affine model, as shown below: in, For the nonlinear terms appearing in the state equations, the prerequisite variables are defined as follows: In a given analysis region Inside, set: The upper and lower bounds of the five premise variables are as follows: The last interval mentioned above The order of the upper and lower bounds comes from the monotonicity of the reciprocal function, provided that the condition is always satisfied within the domain of analysis. This point needs special attention in numerical solutions and subsequent drawing of the attraction field; otherwise, the premise variables will be affected. It would lose its physical meaning.

[0042] In this embodiment, standard two-endpoint sector decomposition is used for each premise variable. Taking any premise variable... For example, the membership functions of its two endpoints can be defined as follows: Clearly, the above equation satisfies: The system has 5 premise variables, and each premise variable corresponds to 2 endpoint membership functions. Therefore, the total number of local fuzzy rules is: .

[0043] Let the rule index be Then the first The rule can be uniformly written as: rule :like belong , belong , belong , belong ,and belong Then the local model of the system is: Its corresponding augmented form can be written as: in , and All by , and The five premise variables are obtained by taking their upper and lower boundary values ​​respectively.

[0044] No. The unnormalized weight function for this rule is: After normalization, we obtain the normalized weight function: The global TS fuzzy model can be written as: Its augmented form is as follows: In summary, after considering dynamic limiting and constant power load, the nonlinearity of the system no longer only includes the product term between the modulation function and the state variables, but also the sector nonlinearity introduced by dynamic limiting and the reciprocal nonlinearity introduced by the constant power load. The system is extended to an affine TS fuzzy model with 5 premise variables and 32 local rules. By further processing the affine terms through augmented state unification, a global TS fuzzy model applicable to the constant power load condition can be obtained.

[0045] In this embodiment, based on the TS fuzzy model established above, the attraction domain of the target operating point is estimated using Lyapunov functions and linear matrix inequalities, thereby analyzing the difference in the recoverable range of the target operating point under fixed and dynamic limiting conditions.

[0046] The global TS fuzzy model of the system is: Based on this, construct the common quadratic form Lyapunov function of the augmented system: In the formula M̅ Let be the symmetric positive definite matrix to be found, i.e.: Differentiating the above equation, we get: Substituting the global TS fuzzy model, it can be written as: because Since the convex combination condition is satisfied, the same symmetric positive definite matrix exists for all locally augmented models. , so that: Then there is The system becomes asymptotically stable within the selected analysis region. Thus, the large-signal stability analysis problem is transformed into a feasibility problem of solving the linear matrix inequality (LMI) corresponding to the above equation.

[0047] When the above LMI is feasible, the corresponding Lyapunov function can be obtained. Furthermore, let's take its level set: During the solution process, the constraints of the analysis domain containing the premise variables must also be satisfied, that is: Especially for the newly added reciprocal type premise variable of constant power load Because of its definition and This is relevant, therefore it is necessary to ensure that the analytical region always meets the following requirements. Otherwise, the reciprocal nonlinearity itself would lose its physical meaning.

[0048] Similarly, the preconditions for dynamic limiting are... It should also satisfy: After obtaining the attraction domain estimate, the differences in the recoverable region of the target operating point under fixed and dynamic limiting conditions can be further compared. Since this embodiment establishes a TS fuzzy model considering constant power load, dynamic limiting, and augmented states, the rigorous attraction domain estimation result will be simultaneously affected by the analysis box domain, the interval of the premise variables, and the Lyapunov function form. To illustrate this more intuitively, while keeping the target operating point, system parameters, and controller parameters constant, the equivalent saturation gain is further... Considered as an equivalent parameter characterizing the strength of the amplitude limiting constraint, for different A trend comparison is made between the attraction domain cross-sections under the given conditions. This is because the core idea of ​​dynamic limiting is to dynamically increase the current limiting value during the disturbance phase. Since subsequent attraction domain analysis and LMI solution are better suited to the framework of homogeneous systems, augmented state vectors are introduced here: The aforementioned parameter-dependent affine model can be further rewritten in a homogeneous augmented form: in, The augmentation process does not mean that the affine terms are eliminated; it is merely to unify the subsequent mathematical expression by incorporating the affine terms into the augmented matrix. After the combined effect of CPL and dynamic limiting, the system is essentially still an affine TS fuzzy system. The augmented form is simply to facilitate the subsequent use of a unified LMI expression.

[0049] In this embodiment of the application, before establishing the TS fuzzy model, the step of converting the dynamic limiting stage into an analyzable variable is also included: Actual d-axis current command after dynamic limiting : Equivalent saturation gain definition: Among them, when When it indicates that it has not entered the limited range, when The time indicates that dynamic limiting is in effect. This is achieved by equating the limiting stage to a time-varying saturation gain. The limiting element, which originally had nonlinear saturation characteristics, was transformed into a time-varying gain form with bounded intervals, thus serving as a prerequisite variable for the TS fuzzy model. This allows the changes in control constraints to be incorporated into a unified framework for large-signal stability analysis.

[0050] In this embodiment of the application, step S400 introduces a back-calculation feedback type anti-saturation link, including: An anti-saturation feedback gain is introduced into the integration branch of the voltage outer loop, and the deviation between the direct-axis current reference value of the unlimited output of the voltage outer loop and the actual direct-axis current command value after dynamic limiting is fed back to the input of the integration branch. When the system enters the limiting region, a negative feedback term is generated by using the deviation fed back to the input of the integral branch; Based on the proportional relationship between the voltage outer loop integral time constant and the amplitude limiting process tracking time constant, the anti-saturation feedback gain corresponding to the negative feedback term is tuned.

[0051] In one optional implementation, the design strategy of the anti-saturation link in step S400 can also monitor the output status of the outer voltage loop controller or the error of the DC bus voltage in real time. When the controller is detected to have entered the saturation region or the system error exceeds the preset threshold, the accumulation of the integral term is directly frozen or cut off in the algorithm. The integral action is only restored when the system is not saturated or the error recovers to a small deviation range, thereby suppressing integral saturation from the source.

[0052] In an optional implementation, the design strategy of the anti-saturation circuit in step S400 can also monitor the output status of the voltage outer loop controller in real time. When the controller output is detected to reach the limiting boundary, the output of the integrator is forcibly clamped to keep it synchronized with the limiting value (i.e., the integral term is forced to be equal to the limiting value minus the proportional term), ensuring that the controller output is close to the limiting boundary, so that it immediately exits the saturation state when the error reverses.

[0053] In this embodiment, a back-calculation feedback anti-saturation circuit is further designed based on dynamic limiting. Dynamic limiting can improve the available current boundary during the disturbance phase, but if the voltage outer loop PI integrator continues to accumulate during the limiting period, it may still lead to bus voltage overshoot and recovery hysteresis when exiting the limiting phase. Therefore, it is necessary to feed back the deviation between the actual output and the original output to the integrator branch to suppress integral accumulation.

[0054] Let the voltage outer loop error be... If anti-saturation is not considered, the output of the voltage outer loop PI controller is: After dynamic limiting, the actual d-axis current command sent to the inner current loop is: When the system is not in the limiting zone, there is At this point, the integral stage works normally; however, when the original output of the outer loop exceeds the dynamic limiting boundary, and A deviation will occur. If the integrator still only considers the error... Continuous accumulation leads to a typical saturation phenomenon. The recovery demand expressed by the controller continues to increase, but the actual control quantity that can be sent into the inner loop is already limited, resulting in a persistent mismatch between the two. This problem can occur under both fixed and dynamic limiting conditions, but it is more pronounced under large disturbances and strong saturation conditions.

[0055] To address this issue, a back-calculation feedback-based anti-saturation method is employed to correct the voltage outer loop output. When the limiting circuit is active, the deviation between the actual output and the original output is fed back to the input of the integrator, thereby pulling the integral state towards the limiting value and preventing further ineffective accumulation. For ease of explanation, the voltage outer loop integral output can be introduced first. Then the voltage outer loop PI controller can be rewritten as: Based on this, the inverse feedback-type anti-saturation integral branch can be written as follows: In the formula This is for anti-saturation feedback gain. When the system has not entered the saturation region, there is... The feedback term is zero, and the outer loop controller is a standard PI controller; when the system enters the limiting region, due to... The negative feedback term inhibits the integral state from continuing to rise, thus mitigating the adverse effects of integral accumulation. This treatment does not change the fundamental principle of dynamic limiting in the anti-saturation process; instead, it makes constraint reconstruction more controllable by correcting the outer-loop integral state.

[0056] Regarding anti-saturation feedback gain The selection of this initial value can be determined by combining the integral time constant of the voltage outer loop PI. For the voltage outer loop PI, its integral time constant... Back-calculation feedback-based anti-saturation typically introduces a tracking time constant. This indicates how quickly the integral state tracks the deviation between the actual output and the original output when the limiting is in effect. Generally, it can be set as follows: and They are approximately equal, therefore we can accept: The above results are not the only analytical solution. In actual tuning, if the system recovery is still slow, it indicates that the integrator pullback is insufficient, and it can be appropriately increased. If significant reversals, additional fluctuations, or back-and-forth shaking near the amplitude limit occur during the recovery process, it indicates that the feedback is too strong, and the amplitude can be appropriately reduced. .

[0057] Dynamic limiting and anti-saturation design are actually complementary. Dynamic limiting addresses the mismatch between fixed limiting boundaries and the recovery requirements for large disturbances by reconfiguring input constraints online, releasing more transient active power support capacity for the system. Anti-saturation design, on the other hand, addresses how the controller can operate stably and smoothly at the implementation level after the constraints have been reconfigured. It reduces the deviation between the controller's internal state and the actual execution during the limiting process by suppressing outer-loop integral accumulation. The former leans more towards constraint design, while the latter leans more towards implementation correction. Combining the two gives the dynamic limiting strategy both theoretically enhanced recovery capabilities and implementation-level feasibility and stability.

[0058] In this embodiment of the application, step S400, which involves tuning the anti-saturation feedback gain using design constraints, includes: Based on the TS fuzzy model and Lyapunov stability conditions, feasible solutions to the linear matrix inequalities that make the system asymptotically stable are obtained. The feasible region of the anti-saturation feedback gain is determined by incorporating it as an optimization variable into the linear matrix inequality constraints obtained from the solution. Based on the feasible region, in the simulation, if the system recovery time is greater than the preset time threshold, the anti-saturation feedback gain is adjusted based on the system recovery process. If the system oscillates near the limiting boundary, negative feedback adjustment is performed on the anti-saturation feedback gain according to the system oscillation state until the stability requirements after dynamic limiting and anti-saturation correction are met.

[0059] In this embodiment of the application, step S400, generating the converter modulation voltage command, includes: The direct-axis current command value obtained after dynamic limiting and anti-saturation correction is used as the input signal of the inner current loop. Combining the quadrature-axis current command value of the inner current loop with the direct-axis current command value input in the previous step, direct-axis and quadrature-axis modulated voltage components are generated through proportional-integral control. The modulated voltage component is used to generate the drive signal for the converter switching transistor using space vector pulse width modulation technology.

[0060] In an optional implementation, the generation of the converter modulation voltage command in step S400 can also be achieved by restoring the d-axis and q-axis modulation voltage components generated by the PI control of the current inner loop to sinusoidal modulation waves in the three-phase stationary coordinate system through inverse Park transformation and inverse Clarke transformation, and then comparing them with high-frequency triangular carrier waves in real time to generate sinusoidal pulse width modulation drive signals for each bridge arm.

[0061] In an optional implementation, the generation of the converter modulation voltage command in step S400 can also utilize the discrete mathematical model of the converter to predict the current value in all possible switching states at the next moment in real time, construct a value function that includes current tracking error and switching loss, and directly select the optimal switching state as the driving signal through traversal optimization, thereby eliminating the need for the traditional PI regulator and modulation wave generation stage.

[0062] Example 3, referring to Figures 6-16 This embodiment of the invention provides a method for improving the control stability of a flexible interconnected converter. To verify the effectiveness of the dynamic limiting stability enhancement strategy and its supporting anti-saturation design, a simulation model of a typical AC / DC interface unit on the constant DC bus voltage side of a dual-ended flexible DC distribution system was built in Matlab / Simulink. The system parameters are shown in Table 1, and the verification was performed using a constant power load with large disturbance conditions.

[0063] Table 1 System Parameter Table

[0064] 1) Comparison and verification of fixed and dynamic amplitude limiting Case 1: The light-load constant power load is 100 kW, corresponding to operating point OP1; the heavy-load constant power load is 540 kW, corresponding to operating point OP2. When t = 0.2 s, the load suddenly increases from OP1 to OP2. The simulated waveform under fixed amplitude is as follows. Figure 6 and Figure 7 As shown. By Figure 6 and Figure 7 It can be seen that after the disturbance occurs, the outer voltage loop output quickly reaches the static boundary under the fixed limiting condition, and the d-axis current is limited to a fixed value, thus restricting the system's available active power support capability. At this time, although the input power increases, it cannot continue to replenish enough energy to the DC bus capacitor, making it difficult for the bus voltage to recover to near the target operating point.

[0065] When using dynamic limiting under the same operating conditions, the simulated waveform is as follows: Figure 8 and Figure 9 As shown. By Figure 8 and Figure 9 As can be seen, dynamic limiting can increase the limiting boundary online according to the current load power demand and bus energy recovery demand, enabling the rectifier side to release more d-axis active power support during critical transient phases. The system can not only compensate for the increased load power more quickly, but also replenish additional energy to the DC bus capacitor within a certain period of time, thus significantly enhancing the bus voltage recovery capability.

[0066] Case 2: The heavy-duty constant power load is increased to 580 kW, corresponding to the operating point OP3. At t=0.2 s, the load suddenly increases from OP1 to OP3. The simulation waveform under fixed amplitude is as follows. Figure 10 and Figure 11 As shown. By Figure 10 and Figure 11 It can be seen that under larger disturbances, the d-axis current reference after fixed limiting quickly reaches the static boundary, and the subsequent available active power support capacity cannot be further improved with the recovery demand. Although the bus voltage rebounds briefly after the disturbance, it fails to recover to near the reference value and deteriorates further in the subsequent stage, manifesting as delayed instability after low-voltage limited operation.

[0067] When dynamic limiting is used under the same operating conditions, the simulation results are as follows: Figure 12 and Figure 13 As shown. By Figure 12 and Figure 13 It can be seen that although the bus voltage drops more under larger disturbances, dynamic limiting can still effectively enhance the system's recovery capability, enabling the actual value of the d-axis current to stably track the reference value after dynamic limiting, and the system subsequently recovers to near the target voltage.

[0068] Further observation of the outer loop output and the actual current response reveals that the problem of fixed limiting is not only reflected in insufficient active power support. Figure 11This indicates that under strong disturbances and saturation conditions, even if the reference value of the outer voltage loop output is limited, the actual d-axis current response may not always strictly adhere to this reference value during the transient phase. In other words, fixed limiting, as a nominal reference constraint, cannot always be fully realized as an effective physical current constraint. Fixed limiting may not only lead to insufficient support capacity but may also cause deviations between the nominal limiting and the actual current constraint. Figure 13 In the case of dynamic limiting, the actual value of the d-axis current stably tracks the reference value of the current, which further illustrates the effectiveness and necessity of dynamic limiting.

[0069] 2) Verification of the effectiveness of anti-saturation design Under dynamic limiting conditions, when the operating point abruptly changes from OP1 to OP2, the relationship between the outer voltage loop output and the actual current command after dynamic limiting is as follows: Figure 14 As shown, during dynamic limiting, the outer voltage loop output may continue to increase, while the actual current command of the inner loop is limited, resulting in a continuous deviation between the two. Without anti-saturation processing, this deviation will lead to integral accumulation.

[0070] After the system abruptly transitions from OP1 to OP2 under dynamic limiting and then stabilizes, the load suddenly decreases to 300 kW at t=1 s, corresponding to operating point OP4. The simulation waveform without considering saturation resistance is as follows... Figure 15 As shown, the simulation waveform considering anti-saturation is as follows: Figure 16 As shown. Comparison Figure 15 and Figure 16 It can be seen that without considering anti-saturation, the DC bus voltage shows obvious overshoot after the load suddenly decreases, with a peak value close to 1600 V; after adding anti-saturation, the DC bus voltage overshoot is significantly reduced, and the difference between the unlimited output of the voltage outer loop and the actual d-axis current command gradually decreases, indicating that the anti-saturation design can effectively suppress the integral accumulation during the limiting period and improve the dynamic performance when exiting the limiting stage.

[0071] In summary, dynamic limiting and anti-saturation design are not two independent improvements. Dynamic limiting is responsible for online reconstruction of the current constraint boundary, enhancing the system's transient support capability under large disturbances; anti-saturation design is responsible for suppressing outer-loop integral accumulation, improving the controller's performance under limiting conditions. The combination of the two can effectively improve the target operating point recoverability and transient stability of flexible interconnected converters under large disturbance conditions with sudden load increases.

[0072] Example 4 is an embodiment of the present invention. This embodiment differs from the first embodiment in that it provides a flexible interconnected converter control stability improvement system.

[0073] It should be noted that the technical solution of the flexible interconnected converter control stability improvement system and the technical solution of the flexible interconnected converter control stability improvement method mentioned above belong to the same concept. For details not described in detail in the technical solution of the flexible interconnected converter control stability improvement system in this embodiment, please refer to the description of the technical solution of the flexible interconnected converter control stability improvement method mentioned above.

[0074] This embodiment provides a flexible interconnected converter control stability improvement system, comprising: The demand calculation module is used to obtain the DC bus voltage and AC side electrical quantities, establish a large signal average model of the AC to DC interface unit on the constant DC bus voltage side, and calculate the DC side load power, power deficit and DC bus energy recovery demand. The current limiting module is used to construct a dynamic limiting boundary within the short-time overcurrent range allowed by the device according to the power deficit and DC bus energy recovery requirements, and to dynamically limit the direct-axis current reference value output by the voltage outer loop to obtain the direct-axis current command value. The constraint generation module is used to combine the characteristics of the dynamic limiting element with the characteristics of the constant power load to perform large signal stability analysis, solve the feasible region of the anti-saturation feedback gain, and generate the design constraints of the anti-saturation element. The modulation command generation module is used to introduce a back-calculation feedback anti-saturation link during dynamic limiting. It uses the design constraints to tune the anti-saturation feedback gain and inputs the direct-axis current command value after dynamic limiting and anti-saturation correction into the inner current loop to generate the converter modulation voltage command.

[0075] This embodiment also provides an electronic device applicable to a method for improving the control stability of a flexible interconnected converter, including: The system includes a memory and a processor. The memory stores computer-executable instructions, and the processor executes these instructions to implement a method for improving the control stability of a flexible interconnected converter, as proposed in the above embodiments.

[0076] This embodiment also provides a storage medium storing a computer program that, when executed by a processor, implements a method for improving the control stability of a flexible interconnected converter as proposed in the above embodiments.

[0077] The storage medium proposed in this embodiment and the method for improving the control stability of a flexible interconnected converter proposed in the above embodiments belong to the same inventive concept. Technical details not described in detail in this embodiment can be found in the above embodiments, and this embodiment has the same beneficial effects as the above embodiments.

[0078] Based on the above description of the implementation methods, those skilled in the art can clearly understand that the present invention can be implemented using software and necessary general-purpose hardware, and of course, it can also be implemented using hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk, or optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods of the various embodiments of the present invention.

[0079] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for improving the control stability of a flexible interconnected converter, characterized in that, include: Obtain the DC bus voltage and AC side electrical quantities, establish a large signal average model of the AC-DC interface unit on the constant DC bus voltage side, and determine the power deficit and DC bus energy recovery requirements based on the DC side energy balance relationship. Based on the power deficit and DC bus energy recovery requirements, a dynamic limiting boundary is constructed within the short-time overcurrent range allowed by the device, and the direct-axis current reference value output by the outer voltage loop is dynamically limited to obtain the direct-axis current command value. By combining the characteristics of the dynamic limiting element with the characteristics of the constant power load, large-signal stability analysis is performed, the feasible region of the anti-saturation feedback gain is solved, and the design constraints of the anti-saturation element are generated. In the dynamic limiting process, a back-calculation feedback anti-saturation stage is introduced. The anti-saturation feedback gain is tuned using the design constraints. The direct-axis current command value after dynamic limiting and anti-saturation correction is input into the inner current loop to generate the converter modulation voltage command.

2. The method for improving the control stability of a flexible interconnected converter as described in claim 1, characterized in that: The establishment of the large-signal averaging model for the AC-DC interface unit on the constant DC bus voltage side includes: Modeling preparation is carried out based on physical topology, and an equivalent circuit including AC power supply, filter inductor, converter, DC bus capacitor and DC load is constructed. Based on the topological relationship of the equivalent circuit, the analysis is performed in a synchronous rotating coordinate system. The dynamic process in the circuit is represented as a state-space equation, in which the AC side voltage, current and the projection components of the switching function in the coordinate system are recorded as state variables. Based on the state-space equation framework, specific load characteristic constraints are introduced, the DC-side load is set as a constant power load, and the mathematical relationship between the load current, DC bus voltage and power value is determined according to the definition of constant power load, thus completing the establishment of the large-signal average model.

3. The method for improving the control stability of a flexible interconnected converter as described in claim 1 or 2, characterized in that: The process of constructing a dynamic limiting boundary within the short-time overcurrent range allowed by the device and dynamically limiting the direct-axis current reference value output by the outer voltage loop to obtain the direct-axis current command value includes: Based on the analysis of the energy balance relationship on the DC side, the critical active current required to prevent the bus voltage from continuing to drop is calculated, and the additional recovery power required by the system during the preset bus voltage recovery time is further calculated. The critical active current is superimposed with the additional recovery power requirement to obtain the total direct-axis active current required by the converter during the large disturbance recovery phase. Based on the total direct-axis active current, a time-varying limiting boundary is dynamically constructed between the device's allowable short-time maximum overcurrent limit and the fixed limiting value under normal operating conditions.

4. The method for improving the control stability of a flexible interconnected converter as described in claim 3, characterized in that: The method of combining the characteristics of the dynamic limiting element with the characteristics of the constant power load for large-signal stability analysis, solving the feasible region of the anti-saturation feedback gain, and generating the design constraints of the anti-saturation element includes: The dynamic limiting circuit is equivalent to a time-varying saturation gain, and the working mechanism of the limiting circuit is characterized by the state of the time-varying saturation gain. Based on the equivalent time-varying saturation gain, a TS fuzzy model is established, which includes a constant power load reciprocal nonlinear term and a dynamic limiting saturation gain nonlinear term. A local linear model is constructed by a two-endpoint sector partitioning algorithm, and a global model is obtained by normalizing the membership function. Based on the global model, combined with Lyapunov functions and linear matrix inequalities, the attraction domain of the target operating point is estimated. By comparing the changing trends of the attraction domain cross section under different saturation gain values, the recoverable range of the system under large disturbances is determined.

5. The method for improving the control stability of a flexible interconnected converter as described in claim 4, characterized in that: The introduction of a back-calculation feedback-type anti-saturation mechanism during dynamic limiting includes: Calculate the deviation between the reference value of the direct-axis current output without voltage limiting in the outer voltage loop and the actual direct-axis current command value after dynamic limiting; The deviation is fed back to the input terminal of the integrator branch of the outer voltage loop, and a negative feedback term is generated using the deviation when the system enters the limiting region; Based on the proportional relationship between the voltage outer loop integral time constant and the amplitude limiting process tracking time constant, the anti-saturation feedback gain corresponding to the negative feedback term is tuned.

6. The method for improving the control stability of a flexible interconnected converter as described in claim 5, characterized in that: The tuning of the anti-saturation feedback gain using the design constraints includes: Based on the TS fuzzy model and Lyapunov stability conditions, feasible solutions to the linear matrix inequalities that make the system asymptotically stable are obtained. The feasible region of the anti-saturation feedback gain is determined by incorporating it as an optimization variable into the linear matrix inequality constraints obtained from the solution. Based on the feasible region, in the simulation, in response to the system recovery time being greater than a preset time threshold, the anti-saturation feedback gain is adjusted based on the system recovery process; In response to system oscillations near the limiting boundary, negative feedback adjustment is performed on the anti-saturation feedback gain based on the system oscillation state until the stability requirements after dynamic limiting and anti-saturation correction are met.

7. The method for improving the control stability of a flexible interconnected converter as described in claim 6, characterized in that: The generator modulated voltage command includes: The direct-axis current command value obtained after dynamic limiting and anti-saturation correction is used as the input signal of the inner current loop. Combining the quadrature-axis current command value of the inner current loop, and based on the direct-axis current command value, proportional-integral control is used to generate direct-axis and quadrature-axis modulated voltage components; The modulated voltage component is used to generate the drive signal for the converter switching transistor using space vector pulse width modulation technology.

8. A flexible interconnected converter control stability improvement system, using the method described in any one of claims 1-7, characterized in that, include: The demand calculation module is used to obtain the DC bus voltage and AC side electrical quantities, establish a large signal average model of the AC to DC interface unit on the constant DC bus voltage side, and calculate the DC side load power, power deficit and DC bus energy recovery demand. The current limiting module is used to construct a dynamic limiting boundary within the short-time overcurrent range allowed by the device according to the power deficit and DC bus energy recovery requirements, and to dynamically limit the direct-axis current reference value output by the voltage outer loop to obtain the direct-axis current command value. The constraint generation module is used to combine the characteristics of the dynamic limiting element with the characteristics of the constant power load to perform large signal stability analysis, solve the feasible region of the anti-saturation feedback gain, and generate the design constraints of the anti-saturation element. The modulation command generation module is used to introduce a back-calculation feedback anti-saturation link during dynamic limiting. It uses the design constraints to tune the anti-saturation feedback gain and inputs the direct-axis current command value after dynamic limiting and anti-saturation correction into the inner current loop to generate the converter modulation voltage command.

9. An electronic device, characterized in that, include: Memory, used to store programs; A processor for loading the program to perform the steps of the method as claimed in any one of claims 1-7.

10. A computer-readable storage medium storing a program, characterized in that, When the program is executed by a processor, it implements the steps of the method as described in any one of claims 1-7.

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