Method, device and equipment for suppressing power oscillation of network-type flexible direct current converter and medium

Abstract

The application discloses a network-constructed flexible direct current converter power oscillation suppression method, device, equipment and medium, and belongs to the field of power grid equipment control. The method is as follows: according to oscillation characteristic information under a plurality of preset short-circuit ratio conditions, a target oscillation mode is determined from an oscillation mode corresponding to each short-circuit ratio condition; wherein the oscillation characteristic information comprises characteristic roots and characteristic vectors of a plurality of state variables corresponding to each control link; according to the characteristic vectors, a participation factor of each state variable to the target oscillation mode is calculated to identify a target control link causing power oscillation; according to the characteristic roots, a sensitivity of each control parameter in the target control link to the target oscillation mode is calculated to screen a plurality of to-be-optimized control parameters; and an optimized value of each to-be-optimized control parameter is determined in a feasible region, and the corresponding control link is controlled through the optimized value to suppress power oscillation. The application can improve the accuracy of network-constructed flexible direct current converter power oscillation suppression.

Description

Technical Field

[0001] This application relates to the field of power grid equipment control, and in particular to a method, apparatus, equipment and medium for suppressing power oscillations in grid-type flexible DC converters. Background Technology

[0002] With the rapid development of new energy power generation and flexible DC transmission technology, grid-type flexible DC converters, due to their voltage source characteristics and independent grid connection capabilities, are widely used in weak grid and islanded grid operation scenarios. In these application environments, the grid short-circuit ratio is low, the system impedance changes significantly, and the coupling relationship between the converter and the grid is enhanced, easily inducing low-frequency power oscillations or even system instability. Therefore, effectively identifying and suppressing power oscillations in grid-type flexible DC converters is of great significance for improving the operational stability and power supply reliability of the power system.

[0003] However, existing methods for suppressing power oscillations in grid-type flexible DC converters largely rely on empirical parameter tuning or stability analysis under single operating conditions. These methods struggle to accurately reflect the coupling relationship between system oscillation modes and control mechanisms under different short-circuit ratios, leading to inaccurate location of key oscillation sources and unclear direction of control parameter adjustments. Consequently, the oscillation suppression effect exhibits significant uncertainty and arbitrariness. Therefore, improving the accuracy of power oscillation suppression in grid-type flexible DC converters under multiple short-circuit ratio conditions has become a pressing technical problem in this field. Summary of the Invention

[0004] This application provides a method, apparatus, equipment, and medium for suppressing power oscillations in grid-type flexible DC converters, which can solve the problem of low accuracy in suppressing power oscillations in existing technologies.

[0005] Some embodiments of this application provide a method for suppressing power oscillations in a grid-type flexible DC converter, including: Obtain oscillation characteristic information corresponding to several preset short-circuit ratio conditions; wherein, the oscillation characteristic information includes: feature vectors and feature roots corresponding to several oscillation modes; the feature vectors include: feature values ​​corresponding to several preset state variables, each state variable corresponding to a control loop; For each short-circuit ratio condition, a target oscillation mode that satisfies the preset oscillation condition is determined from the corresponding oscillation modes based on the oscillation characteristic information of the short-circuit ratio condition. For each state variable, a participation factor characterizing the degree of correlation between the state variable and the target oscillation mode is calculated based on the feature vector. The target control link that causes the occurrence of the target oscillation mode is identified from the control link based on each participation factor. For each control parameter of the target control loop corresponding to each target oscillation mode, the sensitivity of the control parameter to the adjustment effect of the target oscillation mode is calculated based on the characteristic root, and several control parameters to be optimized are selected from the control parameters based on the sensitivity of each parameter. Based on the oscillation characteristic information corresponding to each short-circuit ratio condition, the feasible region of each control parameter to be optimized is determined, and the optimized value of each control parameter to be optimized is determined within the feasible region. The corresponding control loop is controlled by each optimized value to suppress power oscillation under each short-circuit ratio condition.

[0006] Compared with existing technologies, the above embodiments have the following beneficial effects: This application obtains the oscillation characteristic information of the grid-type flexible DC converter under multiple short-circuit ratio conditions, identifies the system oscillation modes based on eigenvalues ​​and eigenvectors, further determines the state variables and their corresponding control links that are highly correlated with the target oscillation mode through participation factor analysis, and then screens the control parameters to be optimized by combining the sensitivity analysis of the control parameters with the eigenvalues. The control parameters are then optimized and tuned under multiple operating condition constraints, thereby achieving step-by-step positioning and targeted adjustment from the system oscillation mode to the control links and key parameters. Compared with existing methods that rely on empirical tuning or single-condition analysis, this application can accurately identify the key control links and their sensitive parameters that cause power oscillations under different short-circuit ratio conditions, improving the accuracy of oscillation source positioning and the targeted nature of control parameter adjustment, thereby effectively improving the accuracy and stability of power oscillation suppression in the grid-type flexible DC converter.

[0007] Further, determining the target oscillation mode that satisfies the preset oscillation condition from the corresponding oscillation modes based on the oscillation characteristic information of the short-circuit ratio condition includes: Extract the real and imaginary parts of the eigenvalues ​​corresponding to each oscillation mode, and determine the oscillation frequency of each oscillation mode based on the imaginary part of the eigenvalues; The damping ratio of each oscillation mode is determined based on the ratio of the real part to the imaginary part of the characteristic root. The oscillation mode with a damping ratio lower than a preset damping threshold and an oscillation frequency within a preset power oscillation frequency range is identified as the target oscillation mode.

[0008] Compared with the prior art, the above embodiments have the following beneficial effects: by extracting the real and imaginary parts of the characteristic roots under each short-circuit ratio condition and using them to calculate the oscillation frequency and damping ratio respectively, and then using the damping ratio threshold and oscillation frequency range as criteria to screen the target oscillation mode, the determination process of the target oscillation mode has a clear physical meaning and quantitative judgment standard, thereby avoiding the uncertainty brought about by identifying the oscillation mode based solely on experience or a single indicator, and improving the accuracy and repeatability of oscillation mode identification.

[0009] Further, determining the feasible region of each control parameter to be optimized based on the oscillation characteristic information corresponding to each short-circuit ratio condition includes: Stability constraints are constructed by constraining the real part of the eigenvalues ​​of each oscillation mode corresponding to each short-circuit ratio condition to be negative. Damping index constraints are constructed by constraining the damping ratio of the target oscillation mode corresponding to each short-circuit ratio condition to be no less than the preset damping threshold. Based on the stability constraints and the damping index constraints, a set of constraints is constructed. For each short-circuit ratio condition, the range of values ​​of each control parameter to be optimized is calculated based on the set of constraints so that the characteristic root satisfies the set of constraints in the complex plane. For each of the control parameters to be optimized, the corresponding value ranges under each short-circuit ratio condition are superimposed to obtain the feasible region covering all short-circuit ratio conditions.

[0010] Compared with the prior art, the above embodiments have the following beneficial effects: by constructing a set of constraints including stability constraints and damping index constraints, and calculating the value range of the control parameters to be optimized under each short-circuit ratio condition, and then superimposing the value ranges under each condition to form a unified feasible domain, the determined control parameters can simultaneously meet the stability and damping performance requirements of multiple conditions, thereby avoiding the problem that parameter tuning is only for a single condition and becomes unstable under other conditions, and improving the applicability and robustness of the control parameters over a wide operating range.

[0011] Further, determining the optimized value for each of the control parameters to be optimized within the feasible domain includes: An objective function is established with the optimization objective of increasing the damping ratio of each target control oscillation mode corresponding to each short-circuit ratio condition; The feasible region is used as the optimization constraint range, and a preset evolutionary algorithm is used to perform iterative search within the optimization constraint range to obtain the parameter combination that makes the objective function reach the extreme value. Each value in the parameter combination is determined as the optimized value corresponding to the control parameter to be optimized.

[0012] Compared with the prior art, the above embodiments have the following beneficial effects: by constructing an objective function with the improvement of the target oscillation mode damping ratio as the optimization objective, and using an evolutionary algorithm to perform a global search for the control parameters to be optimized under the constraints of the feasible region, the parameter tuning process can find a better combination of parameters under the premise of satisfying stability constraints, avoiding the problem that traditional manual adjustment or local search methods are prone to getting trapped in local optima, thereby further improving the power oscillation suppression effect and the global optimality of the control parameter optimization results.

[0013] Further, the feature vector includes: a left feature vector and a right feature vector; the step of calculating, for each state variable, a participation factor characterizing the degree of correlation between the state variable and the target oscillation mode based on the feature vector, and identifying the target control link causing the occurrence of the target oscillation mode from the control link based on each participation factor, includes: The participation factor of each state variable under the target oscillation mode is calculated based on the Adama product of the left eigenvector and the right eigenvector. The participating factors are numerically sorted, and the state variables corresponding to the participating factors whose values ​​are greater than a preset weight threshold are selected as the target state variables. Based on the physical affiliation between the target state variable and each control element in the grid-type flexible DC converter, the control element corresponding to the target state variable is determined as the target control element.

[0014] Compared with the prior art, the above embodiments have the following beneficial effects: by introducing left and right eigenvectors and calculating the participation factor based on their Adama product, the participation degree of each state variable in the target oscillation mode is quantified. Then, the target control link is determined by combining the physical membership relationship between the state variables and the control link. This transforms the oscillation source localization from qualitative analysis to quantitative analysis based on modal participation, thereby improving the accuracy and interpretability of identifying the key control links that cause power oscillation.

[0015] Further, for each control parameter of the target control loop corresponding to each target oscillation mode, the sensitivity of the control parameter to the adjustment effect of the target oscillation mode is calculated based on the eigenvalue, and several control parameters to be optimized are selected from the control parameters based on the sensitivity, including: Calculate the partial derivatives of the eigenvalues ​​corresponding to the target oscillation mode with respect to each of the control parameters, and use the partial derivatives as the sensitivity; The same control parameter whose sensitivity satisfies the preset target influence condition under each target oscillation mode is determined as the control parameter to be optimized.

[0016] Compared with the prior art, the above embodiments have the following beneficial effects: by calculating the partial derivatives of the characteristic roots of the target oscillation mode with respect to each control parameter to obtain the sensitivity, and by screening the control parameters based on the sensitivity, the subsequent optimization is only performed on the key parameters that have a greater impact on the oscillation mode, thereby avoiding ineffective adjustment of irrelevant or low-sensitivity parameters, reducing the dimension and computational complexity of parameter optimization, and improving the efficiency and pertinence of the control parameter tuning process.

[0017] Furthermore, the acquisition of oscillation characteristic information corresponding to several preset short-circuit ratio conditions includes: A pre-constructed AC / DC coupling dynamic model is obtained, and the AC / DC coupling dynamic model is linearized under each short-circuit ratio condition to obtain a small-signal model that characterizes the dynamic characteristics of the corresponding short-circuit ratio condition within a preset disturbance range; wherein, the AC / DC coupling dynamic model is constructed and obtained based on the topology of the AC / DC system and each control element. The state space matrix corresponding to each short-circuit ratio condition is obtained through the small-signal model. Eigenvalue decomposition is performed on each state space matrix to obtain the eigenvalue and eigenvector corresponding to each short-circuit ratio condition, and the eigenvalue and eigenvector are determined as the oscillation characteristic information.

[0018] Compared with the prior art, the above embodiments have the following beneficial effects: by linearizing the AC-DC coupling dynamic model under each short-circuit ratio condition to construct a small-signal model, and obtaining the state space matrix and its eigenvalues ​​and eigenvectors based on the small-signal model, the oscillation characteristic information can reflect the dynamic characteristic changes of the grid-type flexible DC converter under different grid strength conditions, thereby providing a unified and physically based model basis for subsequent oscillation mode identification, participation factor analysis and sensitivity analysis, and improving the accuracy and consistency of oscillation analysis results.

[0019] Another embodiment of this application also provides a power oscillation suppression device for a grid-type flexible DC converter, including: a data acquisition module, a first identification module, a second identification module, a third identification module, and an optimization module; The data acquisition module is used to acquire oscillation characteristic information corresponding to several preset short-circuit ratio conditions; wherein, the oscillation characteristic information includes: feature vectors and feature roots corresponding to several oscillation modes; the feature vectors include: feature values ​​corresponding to several preset state variables, each of the state variables corresponding to a control loop; The first identification module is used to determine, for each short-circuit ratio condition, a target oscillation mode that meets the preset oscillation conditions from the corresponding oscillation modes based on the oscillation characteristic information of the short-circuit ratio condition; The second identification module is used to calculate, for each state variable, a participation factor characterizing the degree of correlation between the state variable and the target oscillation mode based on the feature vector, and to identify the target control link that causes the occurrence of the target oscillation mode from the control link based on each participation factor; The third identification module is used to calculate the sensitivity of the control parameter to the adjustment effect of the target oscillation mode based on the characteristic root for each control parameter of the target control link corresponding to each target oscillation mode, and to select a number of control parameters to be optimized from the control parameters based on each sensitivity. The optimization module is used to determine the feasible region of each control parameter to be optimized based on the oscillation characteristic information corresponding to each short-circuit ratio condition, and to determine the optimized value of each control parameter to be optimized within the feasible region. The optimized value is used to control the corresponding control loop to suppress power oscillation under each short-circuit ratio condition.

[0020] Another embodiment of this application also provides a terminal device, including: a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the steps of the power oscillation suppression method for grid-type flexible DC converters as described in this application.

[0021] Another embodiment of this application also provides a computer-readable storage medium item, including: a stored computer program, which, when the computer program is running, controls the device where the computer-readable storage medium is located to perform the steps of the power oscillation suppression method for grid-type flexible DC converters of this application. Attached Figure Description

[0022] To more clearly illustrate the technical solution of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0023] Figure 1 This is a flowchart illustrating the power oscillation suppression method for a grid-type flexible DC converter provided in some embodiments of this application; Figure 2 This is a schematic diagram of a grid-type flexible DC system considering AC / DC interaction provided in some embodiments of this application; Figure 3 This is an AC / DC interaction logic diagram of a network-type flexible DC system provided in some embodiments of this application; Figure 4This is a flowchart illustrating a differential evolution algorithm provided in some embodiments of this application; Figure 5 This is a eigenvalue distribution map of an initial operating point provided in some embodiments of this application; Figure 6 This is a comparison and verification diagram of a small-signal model and an electromagnetic simulation model provided in some embodiments of this application; Figure 7 This is a schematic diagram of the system eigenvalue results under a wide range of short-circuit ratio variations provided in some embodiments of this application; Figure 8 This is a schematic diagram illustrating the variation of system oscillation frequency and damping ratio under a wide range of short-circuit ratio variations provided in some embodiments of this application; Figure 9 This is a schematic diagram showing the results of the participation factor and sensitivity of a target oscillation mode provided in some embodiments of this application; Figure 10 This is a schematic diagram of the feasible domain of a control parameter to be optimized, provided in some embodiments of this application; Figure 11 This is a schematic diagram comparing electromagnetic simulation results before and after control parameter optimization in some embodiments of this application; Figure 12 This is a schematic diagram of the power oscillation suppression device for a grid-type flexible DC converter provided in some embodiments of this application. Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0025] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims, and foregoing description of the drawings are intended to cover non-exclusive inclusion.

[0026] In the description of the embodiments of this application, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly defined.

[0027] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0028] In the description of the embodiments in this application, the term "and / or" merely describes the relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following associated objects are in an "or" relationship.

[0029] In the description of the embodiments of this application, the term "multiple" refers to two or more (including two), similarly, "multiple sets" refers to two or more (including two sets), and "multiple pieces" refers to two or more (including two pieces).

[0030] In the description of the embodiments of this application, unless otherwise expressly specified and limited, technical terms such as "installation," "connection," "joining," and "fixing" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. For those skilled in the art, the specific meaning of the above terms in the embodiments of this application can be understood according to the specific circumstances.

[0031] Existing methods for suppressing power oscillations in grid-type flexible DC converters mostly rely on empirical parameter tuning or stability analysis under a single operating condition. These methods fail to accurately reflect the coupling relationship between the system oscillation modes and the control loop under different short-circuit ratios, leading to inaccurate location of key oscillation sources and unclear direction of control parameter adjustment. Consequently, the oscillation suppression effect has significant uncertainty and randomness.

[0032] Please refer to Figure 1To address the problem of low accuracy in suppressing power oscillations in grid-type flexible DC converters under multiple short-circuit ratio conditions in existing technologies, the power oscillation suppression method for grid-type flexible DC converters provided in this application includes the following steps S101 to S105: S101: Obtain oscillation characteristic information corresponding to several preset short-circuit ratio conditions; wherein, the oscillation characteristic information includes: feature vectors and feature roots corresponding to several oscillation modes; the feature vectors include: feature values ​​corresponding to several preset state variables, each of the state variables corresponding to a control loop.

[0033] Furthermore, in some embodiments of this application, obtaining the oscillation characteristic information corresponding to each of the several preset short-circuit ratio conditions includes the following steps S1011 to S1013: S1011: Obtain the pre-constructed AC / DC coupling dynamic model, and linearize the AC / DC coupling dynamic model under each short-circuit ratio condition to obtain a small-signal model that characterizes the dynamic characteristics of the corresponding short-circuit ratio condition within a preset disturbance range; wherein, the AC / DC coupling dynamic model is constructed and obtained based on the topology of the AC / DC system and each of the control links.

[0034] Preferably, in some embodiments of this application, reference is made to Figure 2 The AC / DC coupling dynamic model is obtained by uniformly modeling the main circuit, DC side, and control system of the AC power grid and the grid-type flexible DC converter. The control system includes several control links. Specifically, the AC / DC coupling dynamic model includes: AC power grid model, grid-type flexible DC converter main circuit model, DC side and DC line model, grid control and power filtering model, voltage outer loop model, and current inner loop model.

[0035] Preferably, in some embodiments of this application, the AC power grid model is constructed through the following process: The AC grid connected in parallel with a grid-type flexible DC converter is represented as a voltage source using the Thevenin equivalent model. Series impedance .

[0036] Under standardized conditions, the short-circuit ratio (SCR) and the grid-side equivalent reactance The relationship is approximated as: ; in, The system's rated frequency; For AC grid-side inductance; It is an imaginary number.

[0037] By changing The value of allows for wide short-circuit ratio variations from strong to weak and even extremely weak networks. The active and reactive power on the network side are approximately... ; in, For the grid connection point current Quantity; This refers to the active power on the grid side. This refers to the reactive power on the grid side.

[0038] Preferably, in some embodiments of this application, the main circuit model of the grid-type flexible DC converter is constructed through the following process: The AC side of the grid-type flexible DC converter adopts an L-shaped filter structure. In a synchronous rotating coordinate system, the dynamic current of the filter inductor is as follows: ; in, For grid-type flexible DC converters Voltage.

[0039] The active and reactive power of the port are: ; in, Active power at the port; This refers to the reactive power at the port.

[0040] Preferably, in some embodiments of this application, the DC side and DC line model are constructed through the following process: The DC bus voltage of the converter is The capacitance is The DC-side power balance approximation gives the converter DC current. .

[0041] The differential equations for DC buses and lines are as follows: ; in, The voltage across the two ends of the DC line; For each segment of the DC link; This refers to the DC power supply or the voltage of the upstream DC system. This refers to the DC-side bus voltage of the converter. This is the equivalent inductance of a DC line; This is the equivalent resistance of a DC line. This is the equivalent capacitance of a DC line to ground. For variables The first derivative.

[0042] Preferably, in some embodiments of this application, the network control and power filtering model is constructed through the following process: Reactive power droop control provides a port voltage reference value. : ; in, The reactive power-voltage droop factor; This is a reference value for reactive power. This is the rated value for AC line voltage.

[0043] The active and reactive power at the port are filtered by a first-order filter: ; in, These are the filtered active and reactive power values; , These are the first-order filter time constants for active and reactive power, respectively.

[0044] Active power frequency droop and DC voltage droop constitute grid frequency control: ; in, This refers to virtual angular velocity; This is the rated angular frequency; The active-frequency droop factor; For virtual damping; The equivalent inertia time constant; Phase angle of the terminal voltage; To take into account the equivalent active power reference value after DC voltage droop correction; The active power setpoint; This is the DC voltage droop factor; This refers to the rated voltage or reference voltage on the DC side. This represents the system's baseline capacity.

[0045] Preferably, in some embodiments of this application, the voltage outer loop model is constructed through the following process: Voltage amplitude reference obtained from reactive power-voltage droop. and the phase angle obtained from active-frequency control Based on this, the AC side voltage is generated. Axis reference value: ; Measuring the voltage at the grid connection point or converter terminal Quantity Construct a voltage outer-loop PI controller, whose output is the current reference value. Specifically: ; in, These are the proportional and integral coefficients of the outer voltage loop, respectively. , These represent the voltage errors along the d-axis and q-axis, respectively. , These represent the d-axis and q-axis components of the voltage reference value in the dq coordinate system. This voltage loop adjusts the amplitude and phase of the AC voltage and converts the voltage error into a current command for subsequent current inner loop tracking.

[0046] Preferably, in some embodiments of this application, the current inner loop model is constructed through the following process: The current reference given in the voltage outer loop Next, an AC current inner-loop PI controller is constructed to control the converter output voltage reference. .

[0047] Current error , for: ; Current PI control combined with cross-coupling decoupling term get: ; in, The ratio and integral coefficient of the inner current loop; The instantaneous angular velocity is obtained by the network control.

[0048] The modulation stage can be considered as ideal tracking, that is: .

[0049] Preferably, in some embodiments of this application, the flexible DC system uses a grid-type flexible DC converter as an interface to realize the interaction of AC and DC energy and information, and the interaction mechanism is as follows: Figure 3 As shown, by appropriately selecting state variables and conducting detailed small-signal modeling, the AC / DC coupling effect in a flexible DC system can be comprehensively and accurately characterized.

[0050] Specifically, the selection of state variables and the construction of the small-signal model are as follows: First, based on system modeling, key physical quantities of the grid-type flexible DC converter and its AC / DC system are selected as state variables: ; in, This is a state vector, which includes the state variables of each control element.

[0051] Subsequently, under a given short-circuit ratio, the AC / DC coupling dynamic model in the above embodiments is uniformly written as follows: ,in, This represents the general form of the differential equations corresponding to the AC / DC coupling dynamic model. In the steady state under the stated short-circuit ratio condition, we have... Therefore, by solving The steady-state operating point for each of the aforementioned short-circuit ratio conditions is obtained. The steady-state current , It can be approximated as: ; DC current estimated as .

[0052] Finally, a small signal offset is introduced near the steady-state operating point. , (i.e., the preset disturbance range): ; right First-order linearization, ignoring higher-order terms, yields a small-signal state-space model. : ; in: ; The relationship between reactive power, voltage droop, and small-signal port voltage is as follows: ; in, Small-signal disturbance to the converter port voltage reference value; Small-signal disturbance to the reactive power output of the converter (feedback value after filtering); and These represent the small-signal disturbances of the converter port voltage in the synchronously rotating coordinate system of the d-axis and q-axis, respectively. It is the small-signal disturbance of the converter's internal potential relative to the grid's synchronous coordinate system, specifically the power angle.

[0053] The corresponding active and reactive small signals are: ; in, and These represent the small-signal disturbances in the active and reactive power outputs of the converter. The small-signal equations for the remaining states are similarly expanded, forming a state-space matrix. The elements.

[0054] S1012: Obtain the state space matrix corresponding to each short-circuit ratio condition through the small-signal model.

[0055] S1013: Perform eigenvalue decomposition on each of the state space matrices to obtain the eigenvalues ​​and eigenvectors corresponding to each short-circuit ratio condition, and determine the eigenvalues ​​and eigenvectors as the oscillation characteristic information.

[0056] Preferably, in some embodiments of this application, the eigenvalue decomposition process of the state space matrix includes: For different short-circuit ratios and control parameters, the system linearization matrix is ​​denoted as: ,in This indicates the short-circuit ratio (SCR) or a certain control parameter.

[0057] Its characteristic roots Satisfy the characteristic equation ; in, Represents the determinant of a matrix; To and Identity matrices of the same dimension.

[0058] Under a given working condition (i.e.) Given a fixed eigenvalue, solve the following eigenvalue problem: ; in, For the first The eigenvalues ​​of the oscillation modes; The first The left and right eigenvectors of each oscillation mode.

[0059] This application constructs a small-signal model by linearizing the AC / DC coupling dynamic model under various short-circuit ratio conditions, and obtains the state-space matrix and its eigenvalues ​​and eigenvectors based on the small-signal model. This enables the oscillation characteristic information to reflect the dynamic characteristic changes of the grid-type flexible DC converter under different grid strength conditions, thereby providing a unified and physically based model for subsequent oscillation mode identification, participation factor analysis and sensitivity analysis, and improving the accuracy and consistency of oscillation analysis results.

[0060] S102: For each short-circuit ratio condition, determine the target oscillation mode that satisfies the preset oscillation condition from the corresponding oscillation modes based on the oscillation characteristic information of the short-circuit ratio condition.

[0061] Furthermore, in some embodiments of this application, determining the target oscillation mode that satisfies the preset oscillation condition from the corresponding oscillation modes based on the oscillation characteristic information of the short-circuit ratio condition includes: Extract the real and imaginary parts of the eigenvalues ​​corresponding to each oscillation mode, and determine the oscillation frequency of each oscillation mode based on the imaginary part of the eigenvalues; The damping ratio of each oscillation mode is determined based on the ratio of the real part to the imaginary part of the characteristic root. The oscillation mode with a damping ratio lower than a preset damping threshold and an oscillation frequency within a preset power oscillation frequency range is identified as the target oscillation mode.

[0062] Preferably, in some embodiments of this application, after solving the corresponding eigenvalue problem under a given short-circuit ratio condition, the eigenvalues ​​of each oscillation mode under that short-circuit ratio condition are further obtained. and left and right eigenvectors .in, Together they form the feature vector.

[0063] Furthermore, the oscillation frequency and damping ratio of the oscillation mode are calculated through the following processes: ; in, The oscillation frequency; The damping ratio; is the real part of the characteristic root; is the imaginary part of the characteristic roots; Pi is the mathematical constant of a circle.

[0064] Preferably, in some embodiments of this application, when the oscillation frequency and damping ratio are known, the oscillation frequency is selected to be located in the power oscillation correlation band and the damping ratio is... Smaller pairs of complex conjugate eigenvalues ​​are used as target power oscillation modes, for example. Less than hour, The minimum damping ratio requirement for the target oscillation mode is typically set to 0.05. Furthermore, by tracking the migration trajectory of the characteristic roots in the complex plane as the short-circuit ratio changes from high to low, modes that may lead to oscillation amplification under weak and extremely weak network conditions are identified.

[0065] Preferably, in some embodiments of this application, based on the calculation of eigenvalues ​​under different short-circuit ratios and control parameters, a root locus analysis method is introduced to characterize the target oscillation module as a function of parameters. The laws governing the migration of change. Let... Given a continuous variation within a given interval, solve for all eigenvalues ​​for each value. And draw on the complex plane The trajectory of the system is the root locus.

[0066] When performing root locus analysis on the short-circuit ratio, ,get: ; This allows us to observe the migration trend of the target oscillation mode as it evolves from a strong network to a weak network and even an extremely weak network, and to identify the critical short-circuit ratios where the real part is close to zero or crosses the imaginary axis, providing a basis for subsequent stability constraints and the construction of the feasible region for the parameters to be optimized.

[0067] When performing root locus analysis on control parameters, Set as a certain control parameter to be optimized For example, active-frequency droop factor Virtual damping coefficient Or reactive power – voltage droop factor ,get: ; By drawing The root locus can be used to intuitively determine the direction and sensitivity of the parameter's influence on the target oscillation mode damping and oscillation frequency, determine the parameter variation range that makes the characteristic roots move away from the imaginary axis and increase the damping ratio, and determine the range of values ​​for the feasible domain of the subsequent control parameters to be optimized and the optimization search range accordingly.

[0068] This application extracts the real and imaginary parts of the characteristic roots under various short-circuit ratio conditions and uses them to calculate the oscillation frequency and damping ratio, respectively. Then, the target oscillation mode is screened based on the damping ratio threshold and the oscillation frequency range. This makes the determination process of the target oscillation mode have clear physical meaning and quantitative judgment criteria, thereby avoiding the uncertainty caused by identifying the oscillation mode based on experience or a single indicator, and improving the accuracy and repeatability of oscillation mode identification.

[0069] S103: For each state variable, calculate the participation factor characterizing the degree of correlation between the state variable and the target oscillation mode based on the feature vector, and identify the target control link that causes the occurrence of the target oscillation mode from the control link based on each participation factor.

[0070] Further, in some embodiments of this application, the feature vector includes: a left feature vector and a right feature vector; the step of calculating, for each state variable, a participation factor characterizing the degree of correlation between the state variable and the target oscillation mode based on the feature vector, and identifying the target control link causing the occurrence of the target oscillation mode from the control link based on each participation factor, includes: The participation factor of each state variable under the target oscillation mode is calculated based on the Adama product of the left eigenvector and the right eigenvector. The participating factors are numerically sorted, and the state variables corresponding to the participating factors whose values ​​are greater than a preset weight threshold are selected as the target state variables. Based on the physical affiliation between the target state variable and each control element in the grid-type flexible DC converter, the control element corresponding to the target state variable is determined as the target control element.

[0071] Preferably, in some embodiments of this application, the participation factor is calculated through the following process: First, normalize the eigenvectors to make them Further obtained the first In the target oscillation mode, the first The participation factors for each state variable are: . The larger the absolute value, the greater the contribution of the physical quantity corresponding to that state to the oscillation mode. By ranking the participation factors of the target oscillation mode, the target state variable that dominates the power oscillation is identified, and the control link corresponding to the target state variable is further identified as the target control link.

[0072] This application introduces left and right eigenvectors and calculates participation factors based on their Adama product to quantify the participation of each state variable in the target oscillation mode. Then, it combines the physical membership relationship between the state variables and the control loop to determine the target control loop. This transforms the oscillation source localization from qualitative analysis to quantitative analysis based on modal participation, thereby improving the accuracy and interpretability of identifying key control loops that cause power oscillations.

[0073] S104: For each control parameter of the target control loop corresponding to each target oscillation mode, calculate the sensitivity of the control parameter to the adjustment effect of the target oscillation mode based on the characteristic root, and select several control parameters to be optimized from the control parameters based on each sensitivity.

[0074] Furthermore, in some embodiments of this application, the step of calculating the sensitivity of the control parameter to the adjustment effect of the target oscillation mode on each control parameter of the target control loop corresponding to each target oscillation mode, based on the eigenvalue, and selecting a number of control parameters to be optimized from the control parameters based on each sensitivity, includes: Calculate the partial derivatives of the eigenvalues ​​corresponding to the target oscillation mode with respect to each of the control parameters, and use the partial derivatives as the sensitivity; The same control parameter whose sensitivity satisfies the preset target influence condition under each target oscillation mode is determined as the control parameter to be optimized.

[0075] Preferably, in some embodiments of this application, it is assumed that the set of control parameters for all current target control links is as follows: , Includes Control parameters such as the inner loop PI parameters. Furthermore, the target oscillation mode... For control parameters The sensitivity is: ; The real and imaginary parts reflect the direction and intensity of the influence of the control parameter on the target oscillation mode damping ratio and oscillation frequency, respectively. By comparing the sensitivity under different short-circuit ratio conditions, the control parameter to be optimized that has a significant impact over a wide short-circuit ratio range can be selected.

[0076] This application obtains sensitivity by calculating the partial derivatives of the characteristic roots of the target oscillation mode with respect to each control parameter, and then filters the control parameters based on the sensitivity. This ensures that subsequent optimization is only performed on key parameters that have a significant impact on the oscillation mode, thereby avoiding ineffective adjustment of irrelevant or low-sensitivity parameters, reducing the dimensionality and computational complexity of parameter optimization, and improving the efficiency and specificity of the control parameter tuning process.

[0077] S105: Based on the oscillation characteristic information corresponding to each short-circuit ratio condition, determine the feasible region of each control parameter to be optimized, and determine the optimized value of each control parameter to be optimized within the feasible region. Control the corresponding control loop through each optimized value to suppress power oscillation under each short-circuit ratio condition.

[0078] Furthermore, in some embodiments of this application, determining the feasible domain of each control parameter to be optimized based on the oscillation characteristic information corresponding to each short-circuit ratio condition includes: Stability constraints are constructed by constraining the real part of the eigenvalues ​​of each oscillation mode corresponding to each short-circuit ratio condition to be negative. Damping index constraints are constructed by constraining the damping ratio of the target oscillation mode corresponding to each short-circuit ratio condition to be no less than the preset damping threshold. Based on the stability constraints and the damping index constraints, a set of constraints is constructed. For each short-circuit ratio condition, the range of values ​​of each control parameter to be optimized is calculated based on the set of constraints so that the characteristic root satisfies the set of constraints in the complex plane. For each of the control parameters to be optimized, the corresponding value ranges under each short-circuit ratio condition are superimposed to obtain the feasible region covering all preset short-circuit ratio conditions.

[0079] Preferably, in some embodiments of this application, the feasible region needs to satisfy the following constraints: Considering several representative short-circuit ratio conditions The feasible region should satisfy: Stability constraints: ; Damping performance constraints: ; Engineering and dynamic performance constraints: ; Among them, superscript Indicates the first Short-circuit ratio operating conditions; subscript Indicates the first One target oscillation mode; subscript Indicates the first Individual engineering or dynamic performance constraints; (in parentheses) This indicates that the corresponding quantity changes with the control parameter vector; Represents the real part of a complex number; For the first Short-circuit ratio operating condition, control parameter vector The next One eigenvalue; The damping ratio corresponding to the target oscillation mode; To identify the target oscillation mode set; To preset the lower limit of stability margin; The minimum damping ratio requirement for the target oscillation mode; No. Under various working conditions Class engineering and dynamic performance constraint functions; This represents the total number of constraints related to engineering and dynamic performance constraints.

[0080] Based on the above constraints, the feasible region of the control parameters is defined. By performing grid scanning or random sampling within the parameter range, for each candidate The eigenvalues ​​and performance indices are calculated, and the parameter points that satisfy the constraints are retained to form a discrete feasible set, which can be further fitted or enclosed into a continuous feasible domain description.

[0081] This application constructs a set of constraints including stability constraints and damping index constraints, calculates the value range of the control parameter to be optimized under each short-circuit ratio condition, and then superimposes the value ranges under each condition to form a unified feasible region. This allows the determined control parameter to simultaneously meet the stability and damping performance requirements of multiple conditions, thereby avoiding the problem of parameter tuning being only for a single condition and becoming unstable under other conditions, and improving the applicability and robustness of the control parameter over a wide operating range.

[0082] Furthermore, in some embodiments of this application, determining the optimized value corresponding to each of the control parameters to be optimized within the feasible domain includes: An objective function is established with the optimization objective of increasing the damping ratio of each target control oscillation mode corresponding to each short-circuit ratio condition; The feasible region is used as the optimization constraint range, and a preset evolutionary algorithm is used to perform iterative search within the optimization constraint range to obtain the parameter combination that makes the objective function reach the extreme value. Each value in the parameter combination is determined as the optimized value corresponding to the control parameter to be optimized.

[0083] Preferably, in some embodiments of this application, when the feasible domain corresponding to each control parameter to be optimized is known... Subsequently, to further improve the power oscillation suppression effect under wide short-circuit ratio conditions, this application employs a differential evolution algorithm to globally optimize the control parameters to be optimized, the process of which is as follows: Figure 4 As shown.

[0084] First, construct the following objective function. : ; in, The damping ratio of the target oscillation mode; For power adjustment time; This is the overshoot. These are the weighting coefficients.

[0085] Then, the differential evolution optimization process is carried out based on the following procedure: Initialize the population within the feasible region of each control parameter to be optimized. , for the The generation Each individual executes this. Among them, Population size, i.e., the total number of individuals; Let be the initial control parameter vector for the i-th individual in the population.

[0086] Mutations: ; in, This is the scaling factor for variation, used to control the degree of scaling of the difference vector; Let be the mutated individual vector of the i-th individual in the g-th generation; The vectors of three unique individuals are randomly selected in the g-th generation. This is the scaling factor for the variation; The vectors of three unique individuals are randomly selected in the g-th generation. denoted as 3 unique individual vectors randomly selected in the g-th generation.

[0087] cross: ; in, Let each be an experimental individual, representing the i-th individual in the g-th generation. It is a mutated individual; For the target individual; A uniform random number on the interval [0,1]; The crossover probability; A randomly selected dimension index is used to ensure that at least one component of the experimental vector comes from the mutation vector.

[0088] Choose: Under the guarantee Under the premise that, if Then let Otherwise, retain the original value. Wherein, Let be the complete experimental individual vector of the i-th individual in the g-th generation; and These are the vectors of the (g+1)th generation individuals obtained after the selection operation.

[0089] Iterate until convergence to obtain the optimal control parameters. This enables the grid-type flexible DC converter to suppress power oscillations and achieve stable operation under various grid conditions, from strong to extremely weak grids.

[0090] This application constructs an objective function with the goal of improving the damping ratio of the target oscillation mode, and uses an evolutionary algorithm to perform a global search for the control parameters to be optimized under the constraints of the feasible region. This enables the parameter tuning process to find a better combination of parameters while satisfying stability constraints, avoiding the problem of traditional manual adjustment or local search methods easily getting trapped in local optima. This further improves the power oscillation suppression effect and the global optimality of the control parameter optimization results.

[0091] To further illustrate the effectiveness of the power oscillation suppression method for grid-type flexible DC converters provided in this application, the following specific examples will be used for explanation: In this embodiment, considering Figure 2 The system structure shown is a grid-connected flexible DC converter connected to both the AC and DC power grids, wherein the AC side of the converter is connected via a grid-connected inductor. Connect to the AC network, the DC side is connected through an inductor Line inductance Line resistance and capacitors Connect to the DC network. The flexible DC system uses a grid-type flexible DC converter as an interface to realize the interaction of AC and DC energy and information. Its interaction logic is as follows: Figure 3 As shown on the left: The AC network provides port voltage to the converter. Including node voltage amplitude, phase, and power information, the converter injects three-phase current into the AC network. The DC network provides DC-side voltage to the converter. The converter outputs DC current to the DC network. .

[0092] The main rated parameters of the system are shown in Table 1. Table 1 The converter control adopts a grid-type control structure, including active power-frequency droop, reactive power-voltage droop, voltage outer loop, and current inner loop. The specific control block diagram is shown below. Figure 2 As shown.

[0093] First, we model and verify the dynamic small-signal interaction between AC and DC: Based on the technical solution of this application, in Figure 2 Based on the system structure, a unified dynamic model was performed on the AC power grid, the main circuit of the grid-type flexible DC converter, the DC network, and the control system. The rated operating conditions in Table 1 were selected as the initial operating point, and a small-signal model of the system was established. The values ​​of the system's eigenvalues, oscillation frequency, and damping ratio at this operating point are shown in Table 2. The eigenvalue distribution diagram is shown below. Figure 5 As shown. Table 2 The correctness of the established small-signal model was verified by building a corresponding electromagnetic simulation model in MATLAB / Simulink. For example... Figure 6 Simulation results show that the established AC / DC unified dynamic model can accurately reflect the interaction between the converter and the AC and DC networks in the multi-terminal flexible DC system, providing a reliable foundation for subsequent small-signal analysis, mode identification and parameter optimization.

[0094] Next, we will analyze the short-circuit ratio frequency sweep and root locus: To study the small-signal stability characteristics of a grid-connected flexible DC converter under different grid strengths, this embodiment adjusts the grid-connected inductance value to vary the short-circuit ratio (SCR) at the grid connection point within the range of 1 to 50. For each given SCR, a small-signal state matrix is ​​constructed at the current equilibrium point according to the linearization method given in the technical content, and then the eigenvalues ​​and corresponding modes are solved.

[0095] Figure 7 The root locus changes of the system during SCR scans from 1 to 50 are presented. Different colors are used to indicate different SCRs, and five representative target oscillation modes (Mode 1 to Mode 5) are labeled. Based on the results in the figure, we can conclude that: 1) During the SCR change process, the system has 5 modes that exhibit complex conjugate eigenvalues ​​within a certain range, corresponding to 5 sets of target oscillation modes; 2) Mode3 evolves from negative real eigenvalues ​​to complex conjugate roots around an SCR of approximately 6, and begins to exhibit obvious oscillatory characteristics; 3) Mode 4 exhibits oscillations at higher SCR values, corresponding to a high-frequency oscillation mode; 4) In some SCR ranges, the real part of some modes is close to zero, indicating that the system is on the edge of small-signal stability. These critical short-circuit ratios need to be taken into account when designing parameters.

[0096] Root locus analysis visually demonstrates the migration pattern of the target oscillation mode in the complex plane as the short-circuit ratio changes. It can be used to identify the key modes that cause oscillation risks in weak and extremely weak networks, providing a basis for constructing feasible regions for stability constraints and control parameters.

[0097] Next, we will analyze the changes in oscillation mode frequency and damping with the short-circuit ratio: Based on root locus analysis, the frequency and damping ratio of each oscillation mode are statistically analyzed as a function of SCR, such as... Figure 8 As shown. The left figure shows the frequency of each oscillation mode as a function of SCR, and the right figure shows the damping ratio of each mode as a function of SCR. (Combined) Figure 7 And from the numerical results of the eigenvalues, we can obtain: 1) The oscillation frequency of Mode1 to Mode3 does not change much throughout the entire SCR range, and belongs to the inherent mode with basically fixed frequency and insensitive to power grid strength; 2) Mode 5 is a typical strong network triggering mode, which only appears after the SCR is slightly greater than a certain threshold, and the frequency increases with the increase of SCR; 3) In terms of damping, the damping ratio of Mode5 decreases significantly with the increase of SCR, indicating that the stronger the power grid, the more likely this mode is to become a low-damping risk mode. 4) Mode 4 only appears in the high SCR region, with a damping ratio close to 1, and has little impact on overall stability; 5) The damping of the remaining modes remains at a high level throughout the SCR range.

[0098] By combining the frequency and damping ratio curves, the target oscillation modes that need to be focused on and suppressed in different short-circuit ratio ranges can be identified.

[0099] Next, the sensitivity and feasible region of the control parameters are constructed: First, identify the sensitivity of the participating factors in the target oscillation mode, such as... Figure 9 As shown, active droop gain Equivalent inertia Virtual damping coefficient Reactive power – voltage droop factor These are the dominant control parameters under a wide range of short-circuit ratio variations. Then, these control parameters are used as the main decision variables, and a parameter feasible region is constructed based on the constraints, namely, all eigenvalues ​​have negative real parts and the target oscillation mode damping ratio is not lower than a preset threshold.

[0100] Figure 10 The feasible region of the control parameters to be optimized is shown, where: 1) The stability upper limit decreases significantly with increasing SCR. Weak networks allow for a larger active power droop gain to enhance network construction capabilities; however, under strong network conditions, a smaller gain is needed. To avoid triggering high-frequency oscillations; 2) It is basically stable within the range of values ​​considered, and the stability of small signals is less sensitive to inertia. 3) It exhibits stability over most SCR values, only approaching the stability boundary in some low-damping regions. 4) The stability upper limit decreases as the SCR increases, indicating that a larger reactive power droop factor is permissible under weak grid conditions to improve voltage support capability, while it should be appropriately reduced under strong grid conditions. To avoid low-damped voltage oscillations.

[0101] Next, the optimization parameters are designed based on the differential evolution algorithm: Based on obtaining the feasible domain of control parameters under various operating conditions, this embodiment further adopts the differential evolution algorithm to optimize the parameter configuration, so as to improve the damping capability and dynamic performance of power oscillation while satisfying stability constraints. The relevant parameter settings are shown in Table 3. Table 3 The algorithm converges around the 55th generation, having cumulatively evaluated approximately [number missing] individuals. The calculation time for a single complete optimization is approximately 20 seconds, which meets the requirements for offline tuning in engineering. The values ​​of the control parameters before and after optimization are shown in Table 4. Table 4 Finally, the performance optimization was verified: To verify the effectiveness of the control parameters obtained by the differential evolution algorithm, under steady state conditions... A small SCR perturbation was applied to the active power reference value, and simulations were performed comparing the parameters before and after optimization. Figure 11As shown, the optimized control parameters significantly reduce the drop and overshoot of active and reactive power under disturbance conditions, and accelerate oscillation decay; the fluctuation amplitude of DC bus voltage and AC side voltage is reduced, and the recovery time is shortened; thirdly, the peak values ​​of AC current and DC current are reduced, and the oscillation envelope is weakened. This indicates that under the same disturbance and extremely weak network conditions, the optimized parameters of this application can significantly improve the damping level and power oscillation suppression capability of the grid-type flexible DC converter.

[0102] In summary, the power oscillation suppression method for grid-type flexible DC converters provided in this application has the following advantages compared to existing technologies: This application obtains the oscillation characteristic information of the grid-type flexible DC converter under multiple short-circuit ratio conditions, identifies the system oscillation modes based on eigenvalues ​​and eigenvectors, further determines the state variables and their corresponding control links that are highly correlated with the target oscillation mode through participation factor analysis, and then screens the control parameters to be optimized by combining the sensitivity analysis of the control parameters with the eigenvalues. The control parameters are then optimized and tuned under multiple operating condition constraints, thereby achieving step-by-step positioning and targeted adjustment from the system oscillation mode to the control links and key parameters. Compared to existing methods that rely on empirical tuning or single-condition analysis, this application can accurately identify the key control links and their sensitive parameters that cause power oscillations under different short-circuit ratio conditions, improving the accuracy of oscillation source positioning and the targeted nature of control parameter adjustment, thereby effectively improving the accuracy and stability of power oscillation suppression in grid-type flexible DC converters.

[0103] like Figure 12 As shown, based on the above-mentioned method embodiments, an embodiment of this application provides a power oscillation suppression device for a grid-type flexible DC converter, characterized in that it includes: a data acquisition module 201, a first identification module 202, a second identification module 203, a third identification module 204, and an optimization module 205; The data acquisition module 201 is used to acquire oscillation characteristic information corresponding to several preset short-circuit ratio conditions; wherein, the oscillation characteristic information includes: feature vectors and feature roots corresponding to several oscillation modes; the feature vectors include: feature values ​​corresponding to several preset state variables, and each state variable corresponds to a control loop. The first identification module 202 is used to acquire oscillation characteristic information corresponding to several preset short-circuit ratio operating conditions, and determine the target oscillation mode corresponding to each short-circuit ratio operating condition based on the oscillation characteristic information; wherein, the oscillation characteristic information includes: characteristic roots and characteristic vectors of several state variables corresponding to each control link of the grid-type flexible DC converter. The second identification module 203 is used to calculate, for each state variable, a participation factor characterizing the degree of correlation between the state variable and the target oscillation mode based on the feature vector, and to identify the target control link that causes the occurrence of the target oscillation mode from the control link based on each participation factor; The third identification module 204 is used to calculate the sensitivity of the control parameter to the adjustment effect of the target oscillation mode based on the characteristic root for each control parameter of the target control link corresponding to each target oscillation mode, and to select a number of control parameters to be optimized from the control parameters based on each sensitivity. The optimization module 205 is used to determine the feasible region of each control parameter to be optimized based on the oscillation characteristic information corresponding to each short-circuit ratio condition, and to determine the optimized value of each control parameter to be optimized within the feasible region. The optimized value is then used to control the corresponding control loop to suppress power oscillations under each short-circuit ratio condition. It is understood that the above-described device embodiment corresponds to the method embodiment of this application, and can implement the power oscillation suppression method for grid-type flexible DC converters provided by any of the above-described method embodiments of this application.

[0104] Further, in some embodiments of this application, the first identification module 202 includes: an extraction unit, a first calculation unit, a second calculation unit, and a first judgment unit; the first identification module 202 is used to determine the target oscillation mode corresponding to each short-circuit ratio condition based on the oscillation feature information, including: The extraction unit is used to extract the real and imaginary parts of the characteristic roots under each short-circuit ratio condition. The first calculation unit is configured to determine the oscillation frequency of each oscillation mode based on the imaginary part of the eigenvalues; The second calculation unit is used to determine the damping ratio of each oscillation mode based on the ratio of the real part to the imaginary part of the characteristic root; The first determination unit is used to determine the oscillation mode in which the damping ratio is lower than a preset damping threshold and the oscillation frequency is in a preset power oscillation frequency range as the target oscillation mode.

[0105] Further, in some embodiments of this application, the optimization module 205 includes: a first construction unit, a second construction unit, a third calculation unit, and a superposition unit; the optimization module 205 is used to determine the feasible domain of each control parameter to be optimized based on the oscillation characteristic information corresponding to each short-circuit ratio condition, including: The first construction unit is used to construct stability constraints by constraining the real part of the eigenvalues ​​of each oscillation mode corresponding to each short-circuit ratio condition to be negative. The second construction unit is used to construct damping index constraints by constraining the damping ratio of the target oscillation mode corresponding to each short-circuit ratio condition to be not less than the preset damping threshold. The third calculation unit is used to construct a set of constraints based on the stability constraints and the damping index constraints, and for each short-circuit ratio condition, calculate the range of values ​​of each control parameter to be optimized so that the characteristic root satisfies the set of constraints in the complex plane based on the set of constraints. The superposition unit is used to superimpose the value ranges corresponding to each short-circuit ratio condition for each of the control parameters to be optimized, so as to obtain the feasible domain covering all the short-circuit ratio conditions.

[0106] Further, in some embodiments of this application, the optimization module 205 includes: a fourth construction unit, an optimization unit, and a first setting unit; the optimization module 205 is used to determine the optimized value corresponding to each of the control parameters to be optimized within the feasible domain, including: The third construction unit is used to establish an objective function with the optimization objective of improving the damping ratio of each target control oscillation mode corresponding to each short-circuit ratio condition; The optimization unit is used to take the feasible region as the optimization constraint range and use a preset evolutionary algorithm to perform iterative search within the optimization constraint range to obtain the parameter combination that makes the objective function reach the extreme value. The first setting unit is used to determine each value in the parameter combination as the optimized value corresponding to the control parameter to be optimized.

[0107] Further, in some embodiments of this application, the feature vector includes: a left feature vector and a right feature vector; the second identification module 203 includes: a fourth calculation unit, a sorting unit, and a second setting unit; the second identification module 203 is used to calculate, for each state variable, a participation factor characterizing the degree of correlation between the state variable and the target oscillation mode based on the feature vector, and to identify the target control link causing the occurrence of the target oscillation mode from the control link based on each participation factor, including: The fourth calculation unit is used to calculate the participation factor of each state variable under the target oscillation mode based on the Adama product of the left eigenvector and the right eigenvector. The sorting unit is used to sort the participating factors numerically and select the state variables corresponding to the participating factors whose values ​​are greater than a preset weight threshold as target state variables. The second setting unit is used to determine the control link corresponding to the target state variable as the target control link based on the physical affiliation between the target state variable and each control link in the grid-type flexible DC converter.

[0108] Further, in some embodiments of this application, the third identification module 204 includes: a fifth calculation unit and a third setting unit; the third identification module 204 is used to calculate, for each control parameter of the target control link corresponding to each target oscillation mode, the sensitivity of the control parameter to the adjustment effect of the target oscillation mode based on the eigenvalue, and to screen a number of control parameters to be optimized from the control parameters based on each sensitivity, including: The fifth calculation unit is used to calculate the partial derivatives of the characteristic roots corresponding to the target oscillation mode with respect to each of the control parameters, and to use the partial derivatives as the sensitivity. The third setting unit is used to determine the same control parameter whose sensitivity satisfies the preset target influence condition under each target oscillation mode as the control parameter to be optimized.

[0109] Furthermore, in some embodiments of this application, the data acquisition module 201 includes: a fourth construction unit, a model calling unit, and a feature decomposition unit; the data acquisition module 201 is used to acquire oscillation characteristic information corresponding to several preset short-circuit ratio conditions, including: The fourth construction unit is used to acquire a pre-constructed AC / DC coupling dynamic model and linearize the AC / DC coupling dynamic model under each short-circuit ratio condition to obtain a small-signal model that characterizes the dynamic characteristics of the corresponding short-circuit ratio condition within a preset disturbance range; wherein, the AC / DC coupling dynamic model is constructed and acquired based on the topology of the AC / DC system and each of the control links. The model calling unit is used to obtain the state space matrix corresponding to each short-circuit ratio condition through the small signal model; The feature decomposition unit is used to perform feature decomposition on each of the state space matrices, obtain the feature roots and feature vectors corresponding to each short-circuit ratio condition, and determine the feature roots and feature vectors as the oscillation feature information.

[0110] In summary, the power oscillation suppression device for grid-type flexible DC converters provided in this application has the following advantages compared to the prior art: This application obtains the oscillation characteristic information of the grid-type flexible DC converter under multiple short-circuit ratio conditions, identifies the system oscillation modes based on eigenvalues ​​and eigenvectors, further determines the state variables and their corresponding control links that are highly correlated with the target oscillation mode through participation factor analysis, and then screens the control parameters to be optimized by combining the sensitivity analysis of the control parameters with the eigenvalues. The control parameters are then optimized and tuned under multiple operating condition constraints, thereby achieving step-by-step positioning and targeted adjustment from the system oscillation mode to the control links and key parameters. Compared to existing methods that rely on empirical tuning or single-condition analysis, this application can accurately identify the key control links and their sensitive parameters that cause power oscillations under different short-circuit ratio conditions, improving the accuracy of oscillation source positioning and the targeted nature of control parameter adjustment, thereby effectively improving the accuracy and stability of power oscillation suppression in grid-type flexible DC converters.

[0111] It should be noted that the device embodiments described above are merely illustrative, and some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the device embodiments provided in this application, the connection relationships between modules indicate that they have communication connections, which can specifically be implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0112] Based on the above embodiments of the power oscillation suppression method for grid-type flexible DC converters, another embodiment of this application provides a terminal device, which includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the power oscillation suppression method for grid-type flexible DC converters according to any embodiment of this application.

[0113] For example, in this embodiment, the computer program can be divided into one or more modules, which are stored in the memory and executed by the processor to complete this application. The one or more module units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in the terminal device.

[0114] The terminal device may be a desktop computer, laptop, handheld computer, or cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0115] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the terminal device, connecting all parts of the terminal device via various interfaces and lines.

[0116] Based on the above-described method embodiments, another embodiment of this application provides a computer-readable storage medium including a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to execute the power oscillation suppression method for grid-type flexible DC converters described in any of the above-described method embodiments of this application.

[0117] The modules / units integrated in the device / terminal equipment, if implemented as software functional units and sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

Claims

1. A method for suppressing power oscillations in a grid-type flexible DC converter, characterized in that, include: Obtain oscillation characteristic information corresponding to several preset short-circuit ratio conditions; wherein, the oscillation characteristic information includes: feature vectors and feature roots corresponding to several oscillation modes; the feature vectors include: feature values ​​corresponding to several preset state variables, each state variable corresponding to a control loop; For each short-circuit ratio condition, a target oscillation mode that satisfies the preset oscillation condition is determined from the corresponding oscillation modes based on the oscillation characteristic information of the short-circuit ratio condition. For each state variable, a participation factor characterizing the degree of correlation between the state variable and the target oscillation mode is calculated based on the feature vector. The target control link that causes the occurrence of the target oscillation mode is identified from the control link based on each participation factor. For each control parameter of the target control loop corresponding to each target oscillation mode, the sensitivity of the control parameter to the adjustment effect of the target oscillation mode is calculated based on the characteristic root, and several control parameters to be optimized are selected from the control parameters based on the sensitivity of each parameter. Based on the oscillation characteristic information corresponding to each short-circuit ratio condition, the feasible region of each control parameter to be optimized is determined, and the optimized value of each control parameter to be optimized is determined within the feasible region. The corresponding control loop is controlled by each optimized value to suppress power oscillation under each short-circuit ratio condition.

2. The power oscillation suppression method for a grid-type flexible DC converter as described in claim 1, characterized in that, The step of determining the target oscillation mode that satisfies the preset oscillation conditions from the corresponding oscillation modes based on the oscillation characteristic information of the short-circuit ratio condition includes: Extract the real and imaginary parts of the eigenvalues ​​corresponding to each oscillation mode, and determine the oscillation frequency of each oscillation mode based on the imaginary part of the eigenvalues; The damping ratio of each oscillation mode is determined based on the ratio of the real part to the imaginary part of the characteristic root. The oscillation mode with a damping ratio lower than a preset damping threshold and an oscillation frequency within a preset power oscillation frequency range is identified as the target oscillation mode.

3. The power oscillation suppression method for a grid-type flexible DC converter as described in claim 2, characterized in that, The step of determining the feasible region of each control parameter to be optimized based on the oscillation characteristic information corresponding to each short-circuit ratio condition includes: Stability constraints are constructed by constraining the real part of the eigenvalues ​​of each oscillation mode corresponding to each short-circuit ratio condition to be negative. Damping index constraints are constructed by constraining the damping ratio of the target oscillation mode corresponding to each short-circuit ratio condition to be no less than the preset damping threshold. Based on the stability constraints and the damping index constraints, a set of constraints is constructed. For each short-circuit ratio condition, the range of values ​​of each control parameter to be optimized is calculated based on the set of constraints so that the characteristic root satisfies the set of constraints in the complex plane. For each of the control parameters to be optimized, the corresponding value ranges under each short-circuit ratio condition are superimposed to obtain the feasible region covering all short-circuit ratio conditions.

4. The power oscillation suppression method for a grid-type flexible DC converter as described in claim 2, characterized in that, Determining the optimized value for each of the control parameters to be optimized within the feasible domain includes: An objective function is established with the optimization objective of increasing the damping ratio of each target control oscillation mode corresponding to each short-circuit ratio condition; The feasible region is used as the optimization constraint range, and a preset evolutionary algorithm is used to perform iterative search within the optimization constraint range to obtain the parameter combination that makes the objective function reach the extreme value. Each value in the parameter combination is determined as the optimized value corresponding to the control parameter to be optimized.

5. The power oscillation suppression method for a grid-type flexible DC converter as described in claim 1, characterized in that, The feature vector includes a left feature vector and a right feature vector; for each state variable, based on the feature vector, a participation factor characterizing the degree of correlation between the state variable and the target oscillation mode is calculated, and the target control link causing the occurrence of the target oscillation mode is identified from the control link based on each participation factor, including: The participation factor of each state variable under the target oscillation mode is calculated based on the Adama product of the left eigenvector and the right eigenvector. The participating factors are numerically sorted, and the state variables corresponding to the participating factors whose values ​​are greater than a preset weight threshold are selected as the target state variables. Based on the physical affiliation between the target state variable and each control element in the grid-type flexible DC converter, the control element corresponding to the target state variable is determined as the target control element.

6. The power oscillation suppression method for a grid-type flexible DC converter as described in claim 1, characterized in that, For each control parameter of the target control loop corresponding to each target oscillation mode, the sensitivity of the control parameter to the adjustment effect of the target oscillation mode is calculated based on the eigenvalues, and several control parameters to be optimized are selected from the control parameters based on the sensitivities, including: Calculate the partial derivatives of the eigenvalues ​​corresponding to the target oscillation mode with respect to each of the control parameters, and use the partial derivatives as the sensitivity; The same control parameter whose sensitivity satisfies the preset target influence condition under each target oscillation mode is determined as the control parameter to be optimized.

7. The power oscillation suppression method for a grid-type flexible DC converter as described in claim 1, characterized in that, The acquisition of oscillation characteristic information corresponding to several preset short-circuit ratio conditions includes: A pre-constructed AC / DC coupling dynamic model is obtained, and the AC / DC coupling dynamic model is linearized under each short-circuit ratio condition to obtain a small-signal model that characterizes the dynamic characteristics of the corresponding short-circuit ratio condition within a preset disturbance range; wherein, the AC / DC coupling dynamic model is constructed and obtained based on the topology of the AC / DC system and each control element. The state space matrix corresponding to each short-circuit ratio condition is obtained through the small-signal model. Eigenvalue decomposition is performed on each state space matrix to obtain the eigenvalue and eigenvector corresponding to each short-circuit ratio condition, and the eigenvalue and eigenvector are determined as the oscillation characteristic information.

8. A power oscillation suppression device for a grid-type flexible DC converter, characterized in that, include: The system includes a data acquisition module, a first identification module, a second identification module, a third identification module, and an optimization module. The data acquisition module is used to acquire oscillation characteristic information corresponding to several preset short-circuit ratio conditions; wherein, the oscillation characteristic information includes: feature vectors and feature roots corresponding to several oscillation modes; the feature vectors include: feature values ​​corresponding to several preset state variables, each of the state variables corresponding to a control loop; The first identification module is used to determine, for each short-circuit ratio condition, a target oscillation mode that meets the preset oscillation conditions from the corresponding oscillation modes based on the oscillation characteristic information of the short-circuit ratio condition; The second identification module is used to calculate, for each state variable, a participation factor characterizing the degree of correlation between the state variable and the target oscillation mode based on the feature vector, and to identify the target control link that causes the occurrence of the target oscillation mode from the control link based on each participation factor; The third identification module is used to calculate the sensitivity of the control parameter to the adjustment effect of the target oscillation mode based on the characteristic root for each control parameter of the target control link corresponding to each target oscillation mode, and to select a number of control parameters to be optimized from the control parameters based on each sensitivity. The optimization module is used to determine the feasible region of each control parameter to be optimized based on the oscillation characteristic information corresponding to each short-circuit ratio condition, and to determine the optimized value of each control parameter to be optimized within the feasible region. The optimized value is used to control the corresponding control loop to suppress power oscillation under each short-circuit ratio condition.

9. A terminal device, characterized in that, The device includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor, when executing the computer program, implements the power oscillation suppression method for a grid-type flexible DC converter as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored computer program, wherein, when the computer program is executed, it controls the device containing the computer-readable storage medium to perform the power oscillation suppression method for a grid-type flexible DC converter as described in any one of claims 1 to 7.

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