Inverter grid-connected parameter stability domain identification method and device based on bifurcation characteristics

Abstract

The application relates to an inverter grid-connected parameter stability domain identification method and device based on bifurcation characteristics, which comprises the following steps: establishing a generalized swing equation based on the differential algebraic equation of different inverters; deriving a unified standard form and equivalent parameters suitable for bifurcation analysis; systematically analyzing the boundary conditions of generalized saddle-node bifurcation, Hopf bifurcation and homoclinic bifurcation, and constructing the area division in the parameter space with different dynamic behaviors; based on the system equilibrium point and the manifold characteristics in different areas, the stability domain of the inverter control parameters and electrical parameters is accurately identified by combining the Melnikov function analysis result. The method uses the principle of nonlinear dynamics to derive the bifurcation boundary conditions of the inverter grid-connected system, construct the typical area with different dynamic structures in the parameter space, and then identify the parameter stability domain under different operating conditions. The multi-parameter stability problem of a complex system can be reduced to the boundary judgment of a few key parameters, and the efficiency and accuracy of the stability domain identification are greatly improved.

Description

Technical Field

[0001] This application relates to the field of new energy power management technology, specifically to a method and device for identifying the stability domain of inverter grid connection parameters based on bifurcation characteristics. Background Technology

[0002] With the rapid development of renewable energy grid-connected systems, inverters, as essential tools for integrating wind and solar power, have been widely used in new power systems, and inverter-connected grid systems have become the main method for renewable energy grid connection. Therefore, ensuring the stable operation of inverter systems under various operating conditions has become a key technical issue in power system stability analysis. The stability of inverter-connected grid-connected systems depends not only on controller parameters but also on the system's operating mode and network topology. To ensure stable system operation, it is essential to effectively identify and control the system's stability domain to avoid potential system instability.

[0003] Currently, the main research methods for the stability domain of inverter grid-connected systems include eigenvalue analysis and impedance analysis.

[0004] Firstly, eigenvalue analysis, as a classic method for small-disturbance stability analysis, has advantages such as rigorous theory and clear concepts. However, the application of existing eigenvalue analysis methods in large-scale systems, especially as the system size increases, leads to a significant increase in the dimension of the state space matrix and a substantial increase in computational cost, which in turn significantly reduces the efficiency of stability region identification.

[0005] Secondly, impedance analysis analyzes the stability of a system by establishing an impedance model of the power electronic components and combining it with the generalized Nyquist stability criterion. However, this method has high computational complexity, is only applicable to small disturbance analysis, and, in order to improve computational efficiency, its boundary delineation is too conservative, resulting in reduced accuracy of the stability region results.

[0006] In summary, most existing methods for constructing stability regions focus on the stability region analysis of controller parameters, and many suffer from high computational complexity, strong conservatism, and neglect of system nonlinear characteristics. Therefore, in large-scale power electronic inverter grid-connected systems, how to quickly and accurately identify the system's stability region boundaries, and how to effectively distinguish different types of stability regions considering the interaction between operating modes and control parameters, remain pressing technical challenges. Summary of the Invention

[0007] To overcome the shortcomings of the prior art, this application provides a method and apparatus for identifying the stability domain of inverter grid-connected parameters based on bifurcation characteristics, specifically adopting the following technical solution:

[0008] A method for identifying the stability domain of inverter grid-connected parameters based on bifurcation characteristics, the method comprising the following steps:

[0009] A generalized swing equation is constructed based on the differential-algebraic equations of inverters, applicable to the stability analysis of inverter grid-connected systems; wherein the inverters include grid-connected inverters and grid-connected inverters.

[0010] Based on the derivation of the generalized rocking equation, the normalized generalized rocking equation and corresponding equivalent parameters applicable to bifurcation analysis are obtained;

[0011] The generation mechanism of Bogdanov-Takens bifurcation with codimensional 2 is analyzed, and the boundary conditions of bifurcation with codimensional 1 caused by Bogdanov-Takens bifurcation are obtained by combining the normalized generalized rocking equation and equivalent parameter derivation, and parameter regions with different dynamic modes are divided.

[0012] By analyzing the equilibrium point characteristics and manifold features corresponding to different parameter regions, adjusting the control and electrical parameters of the inverter grid-connected system, and identifying the stability domain of the inverter grid-connected parameters under different operating conditions.

[0013] Optionally: The step of constructing a generalized swing equation applicable to the stability analysis of inverter grid-connected systems based on the inverter's differential algebraic equations includes:

[0014] Analyze to obtain the inverter type in the inverter grid-connected system;

[0015] Analyze the transient characteristics of the inverter based on its type;

[0016] Based on the transient characteristics of the inverter, a generalized swing equation in the form of a set of first-order differential equations corresponding to the inverter type is constructed.

[0017] The generalized oscillation equations in the form of the constructed first-order differential equations are converted into generalized oscillation equations in the form of second-order differential equations.

[0018] Optionally: The step of deriving the standard equation and corresponding equivalent parameters applicable to bifurcation analysis based on the generalized rocking equation includes:

[0019] The generalized swing equations in the second-order differential form of different inverter grid-connected systems are modeled and parameterized to derive the normalized generalized swing equations.

[0020] The equivalent parameters of the inverter grid-connected system are obtained by equivalent merging based on the control parameters and electrical parameters of the inverter; the equivalent parameters include at least a first equivalent parameter, a second equivalent parameter, a third equivalent parameter and a fourth equivalent parameter;

[0021] The equivalent parameters of the inverter grid-connected system are constrained and verified.

[0022] Optionally: The step of deriving the boundary conditions for the codimensional 1 bifurcation caused by the Bogdanov-Takens bifurcation by combining the normalized generalized rocking equation and equivalent parameters includes:

[0023] Solve for the equilibrium point of the corresponding inverter grid-connected system based on the normalized generalized swing equation;

[0024] Based on the property that Bogdanov-Takens bifurcation occurs at zero equilibrium points with an algebraic multiplicity of 2, the function for solving the bifurcation point parameters of Bogdanov-Takens bifurcation is obtained:

[0025]

[0026] In the above formula, P I P is the second equivalent parameter. α The third equivalent parameter; P D This is the fourth equivalent parameter;

[0027] The bifurcation point parameters of Bogdanov-Takens bifurcation are obtained using a bifurcation point parameter solving function based on Bogdanov-Takens bifurcation.

[0028] Optional: The codimensional 1 bifurcation caused by the Bogdanov-Takens bifurcation includes generalized saddle-node bifurcation, Hopf bifurcation, and homoclinic bifurcation.

[0029] Furthermore: Based on the characteristic that generalized saddle-node bifurcation occurs at one or more equilibrium points where it arises or disappears, the boundary condition B1 for generalized saddle-node bifurcation is obtained through analysis:

[0030] B1={(P I ,P D )|P I =1,P D >0}.

[0031] Furthermore: Based on the characteristic that Hopf bifurcation occurs when parameter changes cause a pair of pure imaginary conjugate eigenvalues ​​to cross the imaginary axis in the linearized Jacobian matrix at a certain equilibrium point, the boundary condition B2 of the Hopf bifurcation is obtained as follows:

[0032]

[0033] Furthermore: Based on the characteristic that homoclinic bifurcation occurs at the intersection of stable and unstable manifolds at saddle points, the Melnikov function is used to calculate the distance between the stable and unstable manifolds at the saddle point, yielding the boundary condition B3 for homoclinic bifurcation:

[0034]

[0035] Optionally: The step of identifying and obtaining the stability domain of inverter grid-connected parameters under different operating conditions includes:

[0036] Based on generalized saddle-node bifurcation, Hopf bifurcation and homologous bifurcation, the phase plane of the inverter grid-connected system is divided into homologous track region, limit loop region, unstable equilibrium region and no equilibrium point region.

[0037] Based on the mapping of the co-occurring track region and limit loop region of the phase plane of the inverter grid-connected system to the physical parameter space composed of the control parameters and electrical parameters of the inverter grid-connected system;

[0038] Using the parameter critical curves corresponding to generalized saddle-node bifurcation, Hopf bifurcation and homoclinic bifurcation as boundaries, the stable and unstable regions are divided in the physical parameter space to obtain the stable region division results.

[0039] Different operating conditions are simulated by adjusting the control and electrical parameters of the inverter grid-connected system;

[0040] Based on the stable region partitioning results of the physical parameter space, it is determined whether the corresponding parameters belong to the stable region or the unstable region under different operating conditions.

[0041] Furthermore, this application also discloses a stability domain identification device for inverter grid-connected parameters based on bifurcation characteristics, the device comprising:

[0042] The swing equation construction module is used to construct generalized swing equations applicable to the stability analysis of inverter grid-connected systems based on the differential-algebraic equations of inverters; wherein the inverters include grid-connected inverters and grid-connected inverters.

[0043] The swing equation normalization module is used to derive the normalized generalized swing equation and corresponding equivalent parameters applicable to bifurcation analysis based on the derivation of the generalized swing equation.

[0044] The parameter region partitioning module is used to analyze the generation mechanism of Bogdanov-Takens bifurcation with a codimensional of 2, and to obtain the boundary conditions of bifurcation with a codimensional of 1 caused by Bogdanov-Takens bifurcation by combining the normalized generalized rocking equation and the derivation of equivalent parameters, and to partition parameter regions with different dynamic modes.

[0045] The stability domain identification module is used to analyze the equilibrium point characteristics and manifold features corresponding to different parameter regions, adjust the control parameters and electrical parameters of the inverter grid-connected system, and identify the stability domain of the inverter grid-connected parameters under different operating conditions.

[0046] The technical solution of this application achieves the following beneficial effects:

[0047] (1) The inverter grid-connected parameter stability domain identification method of this application analyzes the BT bifurcation generation mechanism with a co-dimensional of 2, derives the boundary conditions of the resulting co-dimensional 1 bifurcation, and uses the bifurcation boundaries corresponding to different dynamic modes as the identification basis, so as to accurately identify the stability characteristics of different regions in the parameter space, which greatly improves the accuracy of parameter stability domain identification. Furthermore, this method analyzes and adjusts the control parameters and electrical parameters of the grid-connected inverter system or the grid-connected inverter system, and solves the parameter stability domain of the system under different operating conditions. By adjusting the system parameters in a targeted manner, it can cope with complex changes in operating conditions, thereby ensuring that the inverter grid-connected system can maintain good stability under a wide range of operating conditions and effectively avoid the risk of instability caused by parameter changes.

[0048] (2) The inverter grid-connected parameter stability domain identification method of this application analyzes the stability of the inverter grid-connected system by combining nonlinear dynamics principles with bifurcation theory. Compared with the traditional small-signal stability analysis method based on linearization, it can more accurately capture the nonlinear instability behavior of the system under large disturbances. By deriving the bifurcation points and their corresponding boundary conditions, the problem of excessive computation and inapplicability to large-scale systems in traditional methods is avoided, the stability analysis process is simplified, and the computational efficiency is greatly improved. Attached Figure Description

[0049] Figure 1 This is a flowchart of the inverter grid connection parameter stability domain identification method based on bifurcation characteristics in the embodiments of this application.

[0050] Figure 2 This is a topology diagram of the inverter grid-connected system in the embodiments of this application.

[0051] Figure 3 This is a schematic diagram of the balance point distribution and trajectory distribution of the inverter grid-connected system in the embodiments of this application.

[0052] Figure 4 This is a schematic diagram of the system equilibrium point distribution and trajectory distribution when the phase angle is unlimited in the embodiments of this application.

[0053] Figure 5 This is a schematic diagram of manifold evolution under different parameter conditions in the embodiments of this application.

[0054] Figure 6 This is a bifurcation diagram of a grid-connected system with a grid-type inverter, as shown in the embodiments of this application.

[0055] Figure 7 This is a phase diagram of a grid-connected system with a grid-type inverter, as shown in the embodiments of this application.

[0056] Figure 8 Different equivalent parameters P in the embodiments of this application αThe corresponding bifurcation boundary diagram.

[0057] Figure 9 This is a phase diagram of a grid-connected inverter system according to an embodiment of this application.

[0058] Figure 10 This is a graph showing the stability domain results of the inverter grid-connected system parameters in an embodiment of this application.

[0059] Figure 11 This is a structural diagram of the inverter grid connection parameter stability domain identification device based on bifurcation characteristics in the embodiments of this application.

[0060] Figure 12 This is a structural diagram of an electronic device according to an embodiment of this application. Detailed Implementation

[0061] The present application will now be further described with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solutions of the present application and should not be construed as limiting the scope of protection of the present application. It should be noted that the following detailed descriptions are exemplary and intended to provide further explanation of the present application.

[0062] Specifically, such as Figure 1 As shown in the figure, this embodiment discloses a method for identifying the stability domain of inverter grid-connected parameters based on bifurcation characteristics. The method includes the following steps:

[0063] First, construct the generalized swing equation for the inverter grid-connected system:

[0064] This embodiment constructs a generalized swing equation applicable to the stability analysis of inverter grid-connected systems based on the differential algebraic equations of the inverter; wherein the inverter includes at least a grid-connected inverter and a grid-connected inverter.

[0065] Specifically, such as Figure 2 As shown, in this embodiment, a transient synchronization stability analysis model of the inverter grid-connected system is first constructed. The inverter is connected to the grid via a transmission line. The inverter type in the grid-connected system is obtained by combining the model analysis. In this embodiment, the grid-connected inverter uses a phase-locked loop to achieve phase synchronization, and the grid-connected inverter uses a virtual synchronous machine control strategy.

[0066] Subsequently, the transient characteristics of the corresponding inverter are analyzed based on the inverter type. In this embodiment, the phase-locked loop control structure based on the grid-connected inverter can be used to obtain the inverter output phase angle. As shown in the following formula:

[0067]

[0068] Where k ppll and k ipll These are the proportional and integral coefficients of the phase-locked loop PI control, respectively.

[0069] ω0 is the reference angular frequency; u tq θ represents the q-axis component of the grid connection point voltage; pll The phase angle output by the phase-locked loop; x pll The state variable output by the PI control loop in the phase-locked loop; The inverter output phase angle The derivative of .

[0070] The power of the DC voltage loop satisfies the following formula:

[0071]

[0072] The differential equation for the DC voltage loop is shown in the following formula:

[0073]

[0074] In the above formula, C dc For DC capacitors; u dc P represents the DC capacitor voltage; in and P e These are the input power and electromagnetic power, respectively; k ivdc This refers to the integral coefficient of the DC voltage loop in the grid-type control; u dcref This is the reference value for the DC voltage in the DC voltage loop; This is the derivative of the output state variable of the DC voltage loop integrator.

[0075] Reference value i of the d-axis current of the DC voltage loop output current loop dref As shown in the following formula:

[0076] i dref =k pdvc (u dc -u dcref )+x dvc ;

[0077] Furthermore, the reference value of the output voltage after the current loop is controlled by the PI controller is shown below:

[0078]

[0079] In the above formula, k pacc x is the proportional gain of the DC voltage loop; dvc It is the output state variable of the DC voltage loop integrator; e d and e q It is the dq-axis component of the inverter output voltage; i d and i q It is the dq-axis component of the current flowing through the AC line; k paccIt is the proportional coefficient of the current loop; i qref This is the q-axis current reference value for the q-axis current loop; i dref This is the d-axis current reference value for the d-axis current loop; k iacc It is the integral coefficient of the current loop.

[0080] Finally, the nonlinear state equations of the grid-connected inverter system are dynamically generated by combining the main circuit. Then, by solving the nonlinear state equations, the equilibrium point parameters of the corresponding system can be obtained, as shown below:

[0081]

[0082] In the above formula The inverter output phase angles are respectively Two solutions; x dv0 x is the stable value of the DC voltage loop output variable; tvc It is the state variable output by the network-type current loop; x acc1 It is the state variable output by the d-axis current loop, x acc2 It is the state variable output by the q-axis current loop; U g It is the voltage amplitude on the grid side of the transmission line; L g It is the equivalent inductance of the transmission line; L f It is a filter inductor; P in It is the rated input power; u td0 and u tq0 It is the steady-state value of the grid connection point voltage on the dq axis; i d0 and i q0 It is the steady-state value of the dq-axis component of the current flowing through the AC line.

[0083] Based on the transient characteristics of the inverter described above, a generalized swing equation in the form of a first-order differential equation system corresponding to the inverter type can be constructed. Specifically, in this embodiment, based on the equilibrium point parameters of the system described above, it is known that the key to the equilibrium point lies in the output phase angle, and the phase-locked loop plays a major role in the transient process of the grid-connected inverter. Therefore, the grid-connected inverter grid-connected system model can be simplified to the following formula, which is the generalized swing equation in the form of a first-order differential equation system:

[0084]

[0085] Based on the above generalized swing equations in the form of first-order differential equations, the grid-connected inverter system model can be written as a generalized swing equation in the form of second-order differential equations:

[0086]

[0087] In the above formula The inverter output phase angle The second derivative; M eqP represents equivalent inertia; m P represents equivalent mechanical power. e Represents equivalent electromagnetic power; D eq This represents the equivalent damping, which is related to the system state.

[0088] Similarly, analysis of grid-connected inverter systems reveals that these systems mimic the synchronization mechanism of synchronous generators, achieving phase synchronization through power input. Therefore, based on the characteristics of the virtual synchronous machine, the corresponding generalized swing equation can be obtained as follows:

[0089]

[0090] In the above formula The inverter output phase angle The derivative of, here Refers to the phase angle of the virtual synchronizer; U t It is the amplitude of the grid connection point voltage, p ref is the active power reference value, w is the angular frequency; M is the virtual inertia coefficient; D is the damping coefficient.

[0091] Correspondingly, based on the generalized swing equations in the form of the first-order differential equations of the grid-connected inverter system described above, the grid-connected inverter system model can be written as a generalized swing equation in the form of second-order differential equations:

[0092]

[0093] Similarly, in the above formula The inverter output phase angle The second derivative; M eq P represents equivalent inertia; m P represents equivalent mechanical power. e Represents equivalent electromagnetic power; D eq This represents equivalent damping.

[0094] Furthermore, in this embodiment, using droop control as synchronous control, the corresponding coefficients of the generalized swing equation for the grid-connected system of the grid-connected inverter are:

[0095]

[0096] In the above formula, ω p K represents the low-pass filter coefficients. p This is the droop coefficient.

[0097] Subsequently, the standard form of the generalized swing equation for different inverter grid-connected systems is derived:

[0098] Based on the generalized swing equations of the grid-connected inverter systems described above, it can be seen that their mathematical forms are the same. Therefore, the normalized generalized swing equations and corresponding equivalent parameters applicable to bifurcation analysis can be derived from the generalized swing equations of the different systems described above.

[0099] Since the differential-algebraic equations of grid-connected and grid-coupled inverter systems have similar mathematical structures in describing electrical dynamic behavior, this embodiment unifies and standardizes the generalized swing equations for different inverter types to facilitate nonlinear dynamic studies such as bifurcation analysis.

[0100] In this embodiment, based on the second-order differential form of the generalized swing equations for different inverter grid-connected systems, the model is rearranged and the parameters are equivalentized to derive the normalized generalized swing equations:

[0101]

[0102] In the above formula The time variable represents the normalized value. The above equations not only preserve the dynamic characteristics of the original system, but also remain completely equivalent to the original system in terms of topology and physical mechanism.

[0103] Based on the above-mentioned normalized generalized swing equation, the control parameters and electrical parameters of the inverter can be equivalently merged to obtain the equivalent parameters of the inverter grid-connected system; the equivalent parameters in this embodiment include at least a first equivalent parameter, a second equivalent parameter, a third equivalent parameter, and a fourth equivalent parameter.

[0104] For grid-connected inverters, the corresponding equivalent coefficient is expressed as follows:

[0105]

[0106] For grid-connected inverters, the corresponding equivalent coefficient is expressed as:

[0107]

[0108] In the above formula, t is the first equivalent parameter; P I P is the second equivalent parameter. α The third equivalent parameter; P D This is the fourth equivalent parameter. This embodiment describes the combined influence of control parameters and electrical parameters on the nonlinear behavior of the system through the above-mentioned independent equivalent parameters.

[0109] Furthermore, to ensure the model's consistency with actual engineering applications, the aforementioned equivalent coefficients must also meet certain physical constraints. This embodiment verifies the constraints on the equivalent parameters of the inverter grid-connected system: P D ≥0, P α ≥0, P I≥0. This constraint process ensures the correctness and feasibility of the derived normalized generalized swing equation in a practical physical sense. Furthermore, this normalized generalized swing equation lays the foundation for subsequent bifurcation condition derivation and parameter stability domain identification, simplifying the analysis of the system's nonlinear characteristics and improving the convenience of comparing and analyzing the inverter's grid-connected behavior under different control strategies.

[0110] Then, the Bogdanov-Takens bifurcation is used for analysis and derivation:

[0111] This embodiment analyzes the generation mechanism of Bogdanov-Takens bifurcation with a codimensional of 2, and derives the boundary conditions for bifurcations with a codimensional of 1 caused by Bogdanov-Takens bifurcation by combining the normalized generalized rocking equation and equivalent parameter derivation, thereby dividing parameter regions with different dynamic modes. In this embodiment, the codimensional 1 bifurcations caused by the aforementioned Bogdanov-Takens bifurcation include generalized saddle-node bifurcation, Hopf bifurcation, and homoclinic bifurcation.

[0112] Specifically, this embodiment derives the boundary conditions for a bifurcation with a codimensional of 1 caused by the Bogdanov-Takens bifurcation, and solves for the equilibrium point of the corresponding inverter grid-connected system based on the normalized generalized rocking equation. It is evident from the normalized generalized swing equation that, in P I When PI ≥ 1, the system has no equilibrium point; however, when PI < 1, the system typically has two equilibrium points in (-2π, π), defined as follows: and The distribution and trajectory of the system equilibrium points are as follows: Figure 3 As shown. It should be noted that, as... Figure 4 As shown, when the phase angle is unrestricted, the inverter grid-connected system has an infinite number of equilibrium points.

[0113] This embodiment takes the equilibrium point within (-2π, π) as an example to analyze the transient synchronization stability of the inverter grid-connected system. The analysis is conducted by solving the system at the equilibrium point. Nearby Jacobian matrix J:

[0114]

[0115] Solving for the Jacobian matrix J above, we can obtain the corresponding eigenvalues ​​λ1 and λ2 of the Jacobian matrix:

[0116]

[0117] The eigenvalues ​​of the Jacobian matrix determine the convergence or divergence behavior of the trajectory near the equilibrium point. According to the Hartmann-Grobmann theorem, the phase trajectory of a nonlinear system in the neighborhood of the equilibrium point is homeomorphic to its linearized system. Therefore, in this embodiment, the stability of the inverter grid-connected system in the equilibrium point and its vicinity can be determined by the aforementioned eigenvalues.

[0118] Furthermore, this embodiment analyzes the global dynamic behavior of the inverter grid-connected system based on the evolution process of the attraction domain at two equilibrium points. Firstly, the aforementioned Jacobian matrix has a zero eigenvalue with an algebraic multiplicity of 2, corresponding to the merging of the two equilibrium points of the system, i.e. At this point, the system corresponds to a Bogdanov-Takens bifurcation with a codimension of 2, meaning that this bifurcation is controlled by two independent bifurcation parameters. According to Bogdanov bifurcation theory, three typical codimension 1 bifurcation branches converge near the Bogdanov bifurcation point of the inverter grid-connected system: a generalized saddle-node bifurcation with a codimension of 1, a Hopf bifurcation, and a homoclinic bifurcation. These three curves divide the parameter plane into several regions, representing the transitions between different modes of system dynamics: from a stable equilibrium point to an unstable equilibrium point, from a stable equilibrium point to a periodic limit cycle, and from a limit cycle to the generation of complex homoclinic orbits.

[0119] Based on the characteristic that Bogdanov-Takens bifurcation occurs at zero equilibrium points with an algebraic multiplicity of 2, we can substitute the Jacobian matrix J mentioned above for the solution. In this case, the function for solving the bifurcation parameters of the Bogdanov-Takens bifurcation must satisfy the following conditions:

[0120]

[0121] In the above formula, P I P is the second equivalent parameter. α The third equivalent parameter; P D This is the fourth equivalent parameter;

[0122] By solving the above conditions, the bifurcation point parameters (P) for obtaining the Bogdanov-Takens bifurcation can be obtained. I ,P D ) = (1,0).

[0123] Furthermore, in order to reveal the bifurcation generation conditions with a codimensional of 1 near the BT bifurcation point, it is necessary to introduce small perturbations on the critical bifurcation parameters and study the system characteristics within the neighborhood of the bifurcation point.

[0124] The settings include:

[0125]

[0126] The aforementioned ε1 and ε2 are sufficiently small first-order parameter offsets (|μ|,|v|<<1). Based on this, by performing central manifold reduction and normal form expansion of the system at the BT point, the following simplified model can be obtained:

[0127]

[0128] By locating and coupling each bifurcation curve in the (ε1,ε2) plane, the dynamic structure near the BT point can be fully characterized, thereby analyzing the abrupt change in equilibrium point when the parameters are close to the saddle-knot curve and the periodic trajectory generated by the Hopf bifurcation.

[0129] Furthermore, to obtain the normal form of the BT bifurcation analysis, the nonlinear terms in the simplified model above need to be graded, and a first-order Taylor expansion is performed at the BT bifurcation point, resulting in the system equations as shown below:

[0130]

[0131] In the above formula Δω represents the phase perturbation, Δω represents the angular frequency perturbation, and α is the cross term coefficient.

[0132] Furthermore, generalized saddle-node bifurcation generally occurs when one or more equilibrium points in the system in the parameter space merge and disappear. This typically manifests as some equilibrium points changing from two to one, or from one to zero, at which point the system's dynamic structure changes. Therefore, based on the characteristic in this embodiment that generalized saddle-node bifurcation occurs at the location where one or more equilibrium points arise or disappear, it can be known that when the system parameters are close to the BT bifurcation point, generalized saddle-node bifurcation usually occurs when the stability of the equilibrium points changes drastically. Therefore, solving for the system equilibrium points yields:

[0133]

[0134] Analysis of the above equilibrium conditions shows that when ε1 is less than 0, the original coordinates... There exist two equilibrium points at a given point that are symmetrical to each other. The equilibrium points can be written as: and By analyzing the parameter conditions corresponding to the two equilibrium points, we can see that: when ε1>0, there is no equilibrium point in the system; when ε1=0, the two equilibrium points merge and the BT point appears at π / 2; when ε1 changes from positive to negative after crossing zero, the system generates two equilibrium points.

[0135] Therefore, based on the above system equilibrium point, the boundary condition B1 for the generalized saddle-node bifurcation can be obtained as follows:

[0136] B1={(P I ,P D )|P I =1,P D>0}.

[0137] Furthermore, Hopf bifurcation typically manifests as the appearance or disappearance of periodic orbits, signifying a change in the system's behavior from steady to periodic. Hopf bifurcation occurs when parameter variations cause a pair of purely imaginary conjugate eigenvalues ​​to cross the imaginary axis in the linearized Jacobian matrix at a certain equilibrium point. The system will generate or disappear a small-amplitude limiting cycle near the equilibrium point.

[0138] Specifically, a limiting cycle is an isolated closed orbit in an autonomous system. It possesses either attraction or repulsion, meaning that no other closed orbit in phase space is "continuously" connected to it. If a trajectory starts from an initial point, as time progresses, it either tends towards this closed orbit (stable limiting cycle) or moves away from it (unstable limiting cycle). In the phase plane, the limiting cycle divides the phase space into inner and outer parts. During the evolution of time, if the trajectory's initial value is within the attraction domain of the stable limiting cycle, it will eventually be attracted by the limiting cycle and move in a loop, exhibiting continuous periodic oscillations; if it is outside the unstable limiting cycle, it will be pushed away from the cycle.

[0139] More specifically, Hopf bifurcation can be divided into supercritical Hopf bifurcation and subcritical Hopf bifurcation. Supercritical Hopf bifurcation generates a stable limit cycle at the bifurcation point, eventually resulting in periodic motion with small amplitude. When the equilibrium point becomes unstable, the trajectory with initial values ​​very close to the equilibrium point will first be pushed away, and then attracted by the limit cycle; the attraction region of the stable limit cycle is the area near the center. Subcritical Hopf bifurcation, on the other hand, generates an unstable limit cycle with large amplitude at the bifurcation point. Subcritical Hopf bifurcation poses a serious threat to system stability, potentially causing parameters to change slowly until a sudden large oscillation occurs at the bifurcation point, and when parameters change in the opposite direction, they need to return to a lower value to restore equilibrium.

[0140] Therefore, in this embodiment, the necessary condition for the occurrence of Hopf bifurcation is that the eigenvalues ​​of the Jacobian matrix at the equilibrium point become conjugate imaginary numbers. Thus, this embodiment analyzes and obtains the boundary conditions of Hopf bifurcation based on the characteristic that Hopf bifurcation occurs when parameter changes cause a pair of pure imaginary conjugate eigenvalues ​​to cross the imaginary axis in the linearized Jacobian matrix at a certain equilibrium point.

[0141] The corresponding Jacobian matrix is ​​shown below:

[0142]

[0143] In the above formula Represents phase perturbation The derivative of It represents the derivative of the angular frequency perturbation Δω.

[0144] The indicators for the transition of the eigenvalues ​​of the Jacobian matrix from the real axis to the imaginary axis are: tr(J) = 0, det(J) > 0. Therefore, the boundary condition B2 for the Hopf bifurcation can be expressed as:

[0145]

[0146] Furthermore, homoclinic bifurcation involves the system's trajectory simultaneously approaching both attractors and repulsors at the equilibrium point, forming homoclinic orbits. Near BT bifurcation, the system's parameters may lead to homoclinic orbits near the equilibrium point, which are typically associated with limit cycles or complex dynamical behaviors (such as chaotic behavior), signifying drastic changes in the system's dynamics in certain regions. Therefore, homoclinic bifurcation usually occurs when a stable manifold intersects an unstable manifold at a saddle point. This embodiment uses the Melnikov function to calculate the distance between the stable and unstable manifolds at the saddle point. When the Melnikov function is zero, the stable and unstable manifolds intersect, forming homoclinic orbits and triggering homoclinic bifurcation. Therefore, based on the characteristic that homoclinic bifurcation occurs at the intersection of a stable and unstable manifold at a saddle point, the Melnikov function can be used to calculate the distance between the stable and unstable manifolds at the saddle point, obtaining the boundary conditions for homoclinic bifurcation.

[0147] Specifically, the prerequisite for constructing the Melnikov function in this embodiment is to transform the original system into a Hamiltonian form. Therefore, this embodiment transforms the original inverter grid-connected system into a Hamiltonian form:

[0148]

[0149] In the above formula,

[0150]

[0151] By solving the Hamiltonian function of the above inverter grid-connected system, we can obtain:

[0152]

[0153] In the above equation, x and y are two differential variables in the Hamiltonian system. λ represents an infinitesimal disturbance; λ represents the disturbance parameter.

[0154] In the Hamiltonian form, different values ​​of H correspond to different closed orbits in the Hamiltonian system, with the maximum value corresponding precisely to a homoclinic orbit crossing a saddle point. Combined with... Figure 5 The evolution of the manifold under different parameters is shown, among which Figure 5 In (a), we set λ = 0 and μ = 0; Figure 5 In (b), λ is set to 1.1 and μ to 0.1; Figure 5 In (c), λ = 0.9 and μ = 0; Figure 5 In (d), λ = 5 / 7 and μ = 0.1 are set. When the perturbation parameter μ = 0, a homoclinic trajectory Γ0 exists in the system. With the introduction of small perturbations (i.e., μ > 0), the homoclinic trajectory generally disappears. However, if the stable manifold W at the saddle point... s With unstable manifold W u If they intersect again, they will regenerate a homoclinic orbit, which will then trigger a homoclinic bifurcation.

[0155] This embodiment utilizes the Melnikov function to measure the distance or separation between two manifolds on the phase plane after perturbation. If at a certain point the Melnikov function M(μ) is equal to zero, and that point is a simple zero, it means that a stable manifold and an unstable manifold intersect, thereby generating homoclinic orbits.

[0156] Therefore, in this embodiment, when μ = 0, homoclinic bifurcation occurs, the stable manifold of the saddle point becomes the attractive domain of the system, and the analytical solution of the homoclinic orbit is shown below:

[0157]

[0158] At this point, the homoclinic orbits, starting from and returning to the saddle point, become the stable manifold at the saddle point and thus the attraction domain of the system. Since different level sets of H represent different orbits, when H is small, the orbits are a series of closed curves around the center point; when H increases to a certain critical value, the orbits become special curves that start from and return to the saddle point, i.e., homoclinic orbits, at which point H is 2 / 3. At this point, the Melnikov function of the system can be further obtained:

[0159]

[0160] When the perturbation parameter λ = 5 / 7, the Melnikov function is zero. As λ gradually decreases, W... s With W u W gradually decreases until λ = 5 / 7. s With W u Intersections generate homoclinic orbits, which signifies the occurrence of homoclinic bifurcation. Therefore, the boundary condition B3 for homoclinic bifurcation can be obtained as follows:

[0161]

[0162] Finally, the stability region is solved based on different parameter regions:

[0163] It should be noted that, in this embodiment, the transient synchronization stability of the inverter grid-connected system is related to the initial state of the system and the state of the system after fault clearance, and is determined by the system equilibrium point and the attraction domain of the equilibrium point. Therefore, this embodiment analyzes the equilibrium point characteristics and manifold features corresponding to different parameter regions, adjusts the control parameters and electrical parameters of the inverter grid-connected system, and identifies the stability domain of the inverter grid-connected parameters under different operating conditions.

[0164] Combination Figure 6 and Figure 7 As shown, the three bifurcations with a codimensional of 1 (generalized saddle-node bifurcation, Hopf bifurcation, and homologous bifurcation) divide the phase plane of the inverter grid-connected system into four regions: homologous track region, limiting loop region, unstable equilibrium region, and no equilibrium point region. The homologous track region and the limiting loop region each have two equilibrium points, and the system's small-signal is stable. The limiting loop region contains a limiting loop generated by the Hopf bifurcation, which is equivalent to the boundary of the attraction domain of the equilibrium point. In the unstable equilibrium region, when the limiting loop gradually contracts inward and eventually coincides with the stable equilibrium point, a Hopf bifurcation occurs, the limiting loop disappears, and the stable equilibrium point becomes an unstable equilibrium point; at this point, the small-signal of the equilibrium point is unstable. In the no equilibrium point region, due to P... I When the value is 1, a saddle-node bifurcation occurs, resulting in the loss of the equilibrium point.

[0165] Combination Figure 7 The distribution of equilibrium points and trajectories in the middle of the trajectory verified the above analysis results: the region without equilibrium points corresponds to Figure 7 The phase diagram in (a) shows that the system has no equilibrium point. The unstable equilibrium region corresponds to... Figure 7 In phase diagram (b), the system has two equilibrium points, but both are unstable, and their trajectories diverge from these equilibrium points. The limit cycle region corresponds to... Figure 7 The phase diagram in (c) shows an unstable limit cycle within the system, where all trajectories converge to an internal equilibrium point. The homoclinic orbital region corresponds to... Figure 7 The phase diagram in (d) shows the trajectory after the homoclinic bifurcation, which also has an unstable equilibrium point and a stable equilibrium point.

[0166] because Figure 6 and Figure 7 The average fixed parameter P α =1.3, to further verify the universality of the regional division, such as Figure 8 As shown, it demonstrates different P α The corresponding bifurcation diagram. Combined with... Figure 8 It can be seen that regardless of P α Regardless of the value of P, the system always exhibits three bifurcations with a codimensional of 1. Simultaneously, for smaller P values... α Generally speaking, the closer the homoclinic bifurcation boundary is to the Hopf bifurcation boundary, the better. Furthermore, from... Figure 8It can be seen from this that all three bifurcations originate from the same parameter (P) I P D Starting from (1, 0), it was further proved that there exists a Bogdanov-Takens bifurcation with a codimensional of 2 at that point.

[0167] For grid-connected inverter systems, P α =0, at this point the Hopf bifurcation and the homoclinic bifurcation boundary coincide, meaning the limiting cycle coincides with the homoclinic orbit. Only the homoclinic bifurcation remains, such as... Figure 9 As shown, this is the phase diagram of a grid-connected inverter system. Therefore, the nonlinear dynamic characteristics of a grid-connected inverter are similar to those of a grid-connected inverter system, and their mathematical essence is P... α A special case of the generalized rocking equation with 0.

[0168] According to the bifurcation characteristics, a stable equilibrium point exists in the system if and only if the parameters satisfy the conditions of the limit loop region and the homologous track region, thus satisfying the stability condition. Therefore, in this embodiment, the homologous track region and limit loop region of the inverter grid-connected system phase plane are mapped to the physical parameter space composed of the control parameters and electrical parameters of the inverter grid-connected system;

[0169] Using the parameter critical curves corresponding to generalized saddle-node bifurcation, Hopf bifurcation, and homoclinic bifurcation as boundaries, the physical parameter space is divided into stable and unstable regions to obtain the stable region division results. That is, the area between Hopf bifurcation curve B2 and saddle-node bifurcation curve B1, and outside the saddle-node bifurcation, belongs to the outside of the stable region, while the area between homoclinic bifurcation curve B3 and Hopf bifurcation curve B2, and inside the homoclinic bifurcation curve B3, belongs to the stable region. Therefore, parameters belonging to the stable region and parameters outside the stable region are marked and filled respectively, thereby realizing the identification of parameter stability regions.

[0170] Different operating conditions are simulated by adjusting the control and electrical parameters of the inverter grid-connected system; such as... Figure 10 As shown, this illustrates the distribution of the parameter stability domain under different operating conditions: Figure 10 In (a), the proportional gain of the fixed phase-locked loop is 100, and the current reference value is 0.8 pu; Figure 10 In (b), the integral coefficient of the fixed phase-locked loop is 50, and the current reference value is 0.2 pu; Figure 10 In (c), the proportional coefficient of the fixed phase-locked loop is 50, and the integral coefficient is 200. Figure 10 In section (d), the proportional gain of the fixed phase-locked loop is 5, and the integral gain is 10. (Combined with...) Figure 10 From a to d, it can be seen that as the electrical distance increases (L... gAs the integral coefficient of the phase-locked loop (PLL) increases, the parameter stability region gradually shrinks. As the proportional coefficient of the PLL decreases, the parameter stability region gradually shrinks. As the reference current value increases, the parameter stability region gradually shrinks.

[0171] Therefore, based on the results of the stable region partitioning of the physical parameter space, it can be determined whether the corresponding parameters belong to the stable region or the unstable region under different operating conditions.

[0172] In addition, such as Figure 11 As shown, this application also discloses a device for identifying the stability domain of inverter grid-connected parameters based on bifurcation characteristics, the device comprising:

[0173] The swing equation construction module is used to construct generalized swing equations applicable to the stability analysis of inverter grid-connected systems based on the differential-algebraic equations of inverters; wherein the inverters include grid-connected inverters and grid-connected inverters.

[0174] The swing equation normalization module is used to derive the normalized generalized swing equation and corresponding equivalent parameters applicable to bifurcation analysis based on the derivation of the generalized swing equation.

[0175] The parameter region partitioning module is used to analyze the generation mechanism of Bogdanov-Takens bifurcation with a codimensional of 2, and to obtain the boundary conditions of bifurcation with a codimensional of 1 caused by Bogdanov-Takens bifurcation by combining the normalized generalized rocking equation and the derivation of equivalent parameters, and to partition parameter regions with different dynamic modes.

[0176] The stability domain identification module is used to analyze the equilibrium point characteristics and manifold features corresponding to different parameter regions, adjust the control parameters and electrical parameters of the inverter grid-connected system, and identify the stability domain of the inverter grid-connected parameters under different operating conditions.

[0177] The apparatus provided in this application embodiment can achieve... Figure 1 To avoid repetition, the various processes implemented in the method embodiments will not be described again here.

[0178] like Figure 12 As shown in the illustration, this application also provides an electronic device, including a processor and a memory, and a program or instructions stored in the memory and executable on the processor, which, when executed by the processor, implement as follows: Figure 1 The various processes of the method embodiments shown are all capable of achieving the same technical effect, and will not be described again here to avoid repetition.

[0179] This application embodiment also provides a readable storage medium storing a program or instructions that, when executed by a processor, implement the above-described functionality. Figure 1The various processes described in the embodiments of the method described herein can achieve the same technical effect, and will not be repeated here to avoid repetition.

[0180] This application also provides a computer program product, including computer instructions, which, when executed by a processor, implement the above-described... Figure 1 The various processes described in the embodiments of the method described herein can achieve the same technical effect, and will not be repeated here to avoid repetition.

[0181] It should be understood that the phrase "one embodiment" or "an embodiment" throughout the specification means that a specific feature, structure, or characteristic related to the embodiment is included in at least one embodiment of this application. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. It should be understood that in the various embodiments of this application, the sequence numbers of the above-described processes do not imply a sequential order of execution; the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application. The sequence numbers of the above-described embodiments are merely descriptive and do not represent the superiority or inferiority of the embodiments.

[0182] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0183] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components may be combined, or integrated into another device, or some features may be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0184] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units. They may be located in one place or distributed across multiple network units. Some or all of the units may be selected to achieve the purpose of this embodiment according to actual needs.

[0185] In addition, each functional unit in the various embodiments of this application can be integrated into one processing unit, or each unit can be a separate unit, or two or more units can be integrated into one unit; the integrated unit can be implemented in hardware or in the form of hardware plus software functional units.

[0186] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media that can store program code, such as mobile storage devices, read-only memory (ROM), magnetic disks, or optical disks.

[0187] Alternatively, if the integrated units described above are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this application, or the parts that contribute to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a device (which may be a terminal or platform, etc.) to execute all or part of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROMs, magnetic disks, or optical disks.

[0188] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for identifying the stability domain of inverter grid-connected parameters based on bifurcation characteristics, characterized in that, The method includes the following steps: A generalized swing equation is constructed based on the differential-algebraic equations of inverters, applicable to the stability analysis of inverter grid-connected systems; wherein the inverters include grid-connected inverters and grid-connected inverters. Based on the derivation of the generalized rocking equation, the normalized generalized rocking equation and corresponding equivalent parameters applicable to bifurcation analysis are obtained; The generation mechanism of Bogdanov-Takens bifurcation with codimensional 2 is analyzed, and the boundary conditions of bifurcation with codimensional 1 caused by Bogdanov-Takens bifurcation are obtained by combining the normalized generalized rocking equation and equivalent parameters. The parameter regions with different dynamic modes are divided. The bifurcation with codimensional 1 caused by Bogdanov-Takens bifurcation includes generalized saddle-node bifurcation, Hopf bifurcation, and homoclinic bifurcation. Analyze the equilibrium point characteristics and manifold features corresponding to different parameter regions, adjust the control and electrical parameters of the inverter grid-connected system, and identify the stability domain of the inverter grid-connected parameters under different operating conditions: Based on generalized saddle-node bifurcation, Hopf bifurcation and homologous bifurcation, the phase plane of the inverter grid-connected system is divided into homologous track region, limit loop region, unstable equilibrium region and no equilibrium point region. Based on the mapping of the co-occurring track region and limit loop region of the phase plane of the inverter grid-connected system to the physical parameter space composed of the control parameters and electrical parameters of the inverter grid-connected system; Using the parameter critical curves corresponding to generalized saddle-node bifurcation, Hopf bifurcation and homoclinic bifurcation as boundaries, the stable and unstable regions are divided in the physical parameter space to obtain the stable region division results. Different operating conditions are simulated by adjusting the control and electrical parameters of the inverter grid-connected system; Based on the stable region partitioning results of the physical parameter space, it is determined whether the corresponding parameters belong to the stable region or the unstable region under different operating conditions.

2. The inverter grid-connected parameter stability domain identification method according to claim 1, characterized in that, The steps for constructing a generalized swing equation applicable to the stability analysis of inverter grid-connected systems based on the inverter's differential-algebraic equations include: Analyze to obtain the inverter type in the inverter grid-connected system; Analyze the transient characteristics of the inverter based on its type; Based on the transient characteristics of the inverter, a generalized swing equation in the form of a set of first-order differential equations corresponding to the inverter type is constructed. The generalized oscillation equations in the form of the constructed first-order differential equations are converted into generalized oscillation equations in the form of second-order differential equations.

3. The inverter grid-connected parameter stability domain identification method according to claim 2, characterized in that, The steps for deriving the standard equation and corresponding equivalent parameters applicable to bifurcation analysis based on the generalized rocking equation include: The generalized swing equations in the second-order differential form of different inverter grid-connected systems are modeled and parameterized to derive the normalized generalized swing equations. The equivalent parameters of the inverter grid-connected system are obtained by equivalent merging based on the control parameters and electrical parameters of the inverter; the equivalent parameters include at least a first equivalent parameter, a second equivalent parameter, a third equivalent parameter and a fourth equivalent parameter; For grid-connected inverters, the corresponding equivalent coefficient is expressed as: ； For grid-connected inverters, the corresponding equivalent coefficient is expressed as: ； In the above formula t This is the first equivalent parameter; P I This is the second equivalent parameter; This is the third equivalent parameter; This is the fourth equivalent parameter; k ppll and k ipll These are the proportional and integral coefficients of the phase-locked loop PI control, respectively. i dref yes d shaft current loop d Shaft current reference value; U g It is the voltage amplitude on the grid side of the transmission line; L g It is the equivalent inductance of the transmission line; ω 0 is the reference angular frequency; M This is the virtual inertia coefficient; D The damping coefficient; p ref This is the active power reference value; U t It is the amplitude of the voltage at the grid connection point; The time variable represents normalization; The equivalent parameters of the inverter grid-connected system are constrained and verified.

4. The inverter grid-connected parameter stability domain identification method according to claim 3, characterized in that, The steps for deriving the boundary conditions for the codimensional 1 bifurcation caused by the Bogdanov-Takens bifurcation by combining the normalized generalized rocking equation and equivalent parameters include: Solve for the equilibrium point of the corresponding inverter grid-connected system based on the normalized generalized swing equation; Based on the property that Bogdanov-Takens bifurcation occurs at zero equilibrium points with an algebraic multiplicity of 2, the function for solving the bifurcation point parameters of Bogdanov-Takens bifurcation is obtained: ； In the above formula This is the second equivalent parameter; This is the third equivalent parameter; This is the fourth equivalent parameter; The bifurcation point parameters of Bogdanov-Takens bifurcation are obtained using a bifurcation point parameter solving function based on Bogdanov-Takens bifurcation.

5. The inverter grid-connected parameter stability domain identification method according to claim 4, characterized in that, Based on the characteristic that generalized saddle-node bifurcation occurs at one or more equilibrium points where it arises or disappears, the boundary conditions for generalized saddle-node bifurcation are analyzed and obtained. B 1 is: 。 6. The inverter grid-connected parameter stability domain identification method according to claim 4, characterized in that, Based on the property that Hopf bifurcation occurs when parameter changes cause a pair of pure imaginary conjugate eigenvalues ​​to cross the imaginary axis in the linearized Jacobian matrix at a certain equilibrium point, the boundary conditions of Hopf bifurcation are analyzed. B 2 is: 。 7. The inverter grid-connected parameter stability domain identification method according to claim 4, characterized in that, Based on the characteristic that homoclimate bifurcation occurs at the intersection of stable and unstable manifolds at saddle points, the Melnikov function is used to calculate the distance between the stable and unstable manifolds at the saddle point, thus obtaining the boundary conditions for homoclimate bifurcation. B 3 is: 。 8. A device for identifying the stability domain of inverter grid-connected parameters based on bifurcation characteristics, characterized in that, The device includes: The swing equation construction module is used to construct generalized swing equations applicable to the stability analysis of inverter grid-connected systems based on the differential-algebraic equations of inverters; wherein the inverters include grid-connected inverters and grid-connected inverters. The swing equation normalization module is used to derive the normalized generalized swing equation and corresponding equivalent parameters applicable to bifurcation analysis based on the derivation of the generalized swing equation. The parameter region partitioning module is used to analyze the generation mechanism of Bogdanov-Takens bifurcation with a codimensional of 2, and to obtain the boundary conditions of bifurcation with a codimensional of 1 caused by Bogdanov-Takens bifurcation by combining the normalized generalized rocking equation and equivalent parameter derivation, and to partition parameter regions with different dynamic modes; the codimensional 1 bifurcation caused by Bogdanov-Takens bifurcation includes generalized saddle-node bifurcation, Hopf bifurcation, and homoclinic bifurcation; The stability domain identification module is used to analyze the equilibrium point characteristics and manifold features corresponding to different parameter regions, adjust the control and electrical parameters of the inverter grid-connected system, and identify the stability domain of the inverter grid-connected parameters under different operating conditions. Based on generalized saddle-node bifurcation, Hopf bifurcation and homologous bifurcation, the phase plane of the inverter grid-connected system is divided into homologous track region, limit loop region, unstable equilibrium region and no equilibrium point region. Based on the mapping of the co-occurring track region and limit loop region of the phase plane of the inverter grid-connected system to the physical parameter space composed of the control parameters and electrical parameters of the inverter grid-connected system; Using the parameter critical curves corresponding to generalized saddle-node bifurcation, Hopf bifurcation and homoclinic bifurcation as boundaries, the stable and unstable regions are divided in the physical parameter space to obtain the stable region division results. Different operating conditions are simulated by adjusting the control and electrical parameters of the inverter grid-connected system; Based on the stable region partitioning results of the physical parameter space, it is determined whether the corresponding parameters belong to the stable region or the unstable region under different operating conditions.

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