A branch energy-based network-configuration type converter grid-connected system transient synchronization stability discrimination method

Abstract

The present application relates to a kind of network type converter grid-connected system transient synchronization stability discrimination method based on branch energy, comprising: the influence of the control parameters of network type converter on system energy is analyzed and the distribution characteristics of branch potential energy;Construct network type converter transient characteristic model;Based on network type converter transient characteristic model, construct branch stability discrimination index, carry out transient synchronization stability discrimination.The present application solves the problem that traditional method is difficult to adapt to network type equipment and lacks quantitative criterion;The present application quantifies the stability degree of system and the severity of fault through the proposed stability discrimination index, accurately locates critical cut set branch, overcomes the limitations of traditional energy function method, such as complex calculation and inability to locate weak link, significantly improves the engineering practicability of criterion, compared with traditional stability criterion, the proposed method shows higher discrimination accuracy and adaptability in the high penetration rate scene of network type converter.

Description

Technical Field

[0001] This invention relates to the field of power system stability analysis and control technology, and in particular to a transient synchronous stability discrimination method for grid-connected systems with grid-connected converters based on branch energy. Background Technology

[0002] With the continuous increase in the penetration rate of new energy sources such as wind and solar power, the power system exhibits characteristics of "low damping and weak inertia," resulting in a significant decrease in the system's anti-interference capability. Grid-connected converters, with their advantages of independent voltage and frequency support, weak grid adaptability, and controllable virtual inertia, have become key equipment for improving system stability. Transient synchronous stability analysis after large-scale grid connection is particularly important.

[0003] Existing research on the stability analysis of grid-type converters under small disturbances is relatively mature, but it has significant shortcomings in the transient synchronous stability analysis under large disturbances, such as the inability to locate the critical branch of instability; moreover, the traditional energy function method is computationally complex and lacks a unified quantitative criterion; the equal area criterion can only make qualitative judgments and is difficult to accurately assess the degree of stability. Therefore, there is an urgent need to construct a transient synchronous stability criterion that is adapted to the characteristics of grid-type converters, quantitatively accurate, and capable of locating weak links. Summary of the Invention

[0004] This invention addresses the challenge of transient synchronous stability analysis in power systems with grid-type converters, providing a scientific, reasonable, efficient, and practical stability criterion. Through model construction, energy analysis, index design, and simulation verification, it achieves accurate stability assessment and identification of weak links. The core idea is to construct branch energy functions based on the characteristics of grid-type converters, analyze the differences in energy distribution under stable and unstable conditions, construct a quantitative discrimination index (GBTSI), and verify the effectiveness of the index through simulation.

[0005] To achieve the above objectives, the present invention provides the following solution: A transient synchronization stability determination method for grid-connected systems with grid-connected converters based on branch energy includes: Step 1. Analyze the impact of grid converter control parameters on system energy and branch potential energy distribution characteristics; wherein, the grid converter control parameters include: virtual inertia coefficient. J Damping coefficient D and reactive power droop coefficient D q ; Step 2. Construct a transient characteristic model of the grid-type converter; Step 3. Based on the transient characteristic model of the grid-type converter, construct the branch stability discrimination index and perform transient synchronous stability discrimination.

[0006] Optionally, the analysis of the impact of grid-type converter control parameters on system energy in step 1 includes: The single-parameter variable method, combined with quantization formulas, is used to analyze the impact of grid-type converter control parameters on system energy.

[0007] Optionally, the single-parameter variable method, combined with quantization formulas, is used to analyze the impact of grid-type converter control parameters on system energy, including: The virtual inertia coefficient J , used to characterize the system's ability to store kinetic energy; For the virtual inertia coefficient J The mathematical expression for the system's kinetic energy is: ; in, The total kinetic energy of the system; Let be the angular frequency of branch k, n be the total number of branches in the system with virtual inertia characteristics, and k be the branch number. The rated angular frequency; Based on the mathematical expression for the system's kinetic energy, we can deduce that the system's kinetic energy is related to its inertia coefficient. J There is a linear positive correlation; increasing the inertia coefficient... J It can enhance the system's ability to absorb disturbance energy, thereby reducing the severity of frequency fluctuations after being disturbed.

[0008] Optionally, the single-parameter variable method, combined with quantization formulas, is used to analyze the impact of grid-type converter control parameters on system energy, including: The damping coefficient D This is used to reflect the system's ability to dissipate oscillatory energy; For the damping coefficient D The expression for the system's damping energy is: ; in, For the system damping energy, It is the difference in angular frequency. P D Damping power; Based on the expression for system damping energy, it can be concluded that system damping energy is positively correlated with the damping coefficient, and the damping coefficient... D The larger the value, the faster the system's oscillation energy dissipates.

[0009] Optionally, the single-parameter variable method, combined with quantization formulas, is used to analyze the impact of grid-type converter control parameters on system energy, including: Regarding the reactive power loop droop coefficient D q The expression for the reactive power-voltage control loop is: ; in, E For virtual internal potential, The voltage loop integral coefficient, and These are the reference reactive power and the output reactive power, respectively. This is the rated output voltage. This is the voltage reference value.

[0010] Optionally, the analysis of branch potential energy distribution characteristics in step 1 includes: A three-phase short-circuit fault is set in the branch of the grid-connected infinite bus system of the grid-type converter. By adjusting the fault clearing time, two operating conditions, namely stable and unstable, are obtained. Based on the analysis of the phase angle difference characteristics and transient potential energy distribution of each branch under the two operating conditions, the critical cut set branch of the system was determined, and it was clarified that the concentration and divergence of potential energy of the branch is the core essence of system instability. It was verified that the potential energy change of the critical cut set branch has a decisive influence on the stable state of the system.

[0011] Optionally, the construction of the transient characteristic model of the grid-type converter in step 2 includes: For a single-machine infinite bus system, based on the virtual rotor motion equation of the grid converter, the active-frequency loop and the reactive-voltage loop control mechanism, the power angle swing equation, the reactive-voltage control equation and the mathematical expression of the instantaneous output active power are derived. The equivalent inertial time constant and the equivalent damping coefficient are introduced as key parameters. Combined with the inherent correlation of the branch phase angle difference, the total system energy function including system kinetic energy, transient potential energy and damping energy is constructed. For multi-machine systems, an augmented network correlation matrix is ​​introduced to establish the transient energy function of the multi-machine system branch, which includes synchronous generators, grid-type converters and loads. The active power balance constraints of each node are taken into account to construct the transient energy function of the multi-machine system.

[0012] Optionally, the total energy function of the system is: ; in, The total energy of the system. As the system's kinetic energy, For the system's transient state energy, For the system damping energy, The phase angle difference of line k. The phase angle difference of line k under stable system conditions. For equivalent electromagnetic power, This is the steady-state value of the equivalent power. This is the equivalent damping coefficient for grid-connected grid-type converters; The equivalent electromagnetic power and its steady-state value are: ; in, To output reactive power, D The damping coefficient of the grid-type converter. For line current, The phase difference between the voltage of the GFM-VSC filter capacitor and the mains voltage. This is a reference value for active power. The equivalent inductance on the output side of the GFM-VSC; The transient energy function of the multi-machine system is: ; Where m is the number of GFM-VSCs in the multi-machine system, i is the generator unit number, l is the total number of transmission lines included in the transient energy calculation, b is the transmission line number, and n0 is the total number of synchronous generator units in the multi-machine system. E Ki Let be the transient kinetic energy of the i-th GFM-VSC. E pb The transient state performance of the i-th GFM-VSC E Kgi Let be the transient kinetic energy of the i-th synchronous generator. E pgi Let be the transient potential energy of the i-th synchronous generator. E Di Let be the damping energy of the i-th synchronous generator.

[0013] Optionally, the branch stability discrimination index is: ; in, branch road k The equivalent electromagnetic power; branch road k The equivalent power steady-state value; branch road k The change in temporary state energy.

[0014] Optionally, transient synchronization stability determination includes: The stability of the system is judged by the value of the branch stability discrimination index. The closer the value of the branch stability discrimination index is to 0, the worse the stability of the branch, indicating that the system fault is more serious. The branch closest to 0 is the critical cut set of the system. Therefore, when the branch is stable, the value of the branch stability discrimination index is not equal to 0; when the branch is unstable, the value of the branch stability discrimination index is equal to 0.

[0015] The beneficial effects of this invention are as follows: This invention discloses a transient synchronization stability determination method for grid-connected systems with grid-connected grid-connected converters based on branch energy. The method includes: constructing a transient characteristic model of the grid-connected converter, analyzing the transient characteristics of the grid-connected system, constructing a GBTSI transient synchronization stability criterion, and performing scenario simulation verification. This method constructs a branch energy function adapted to the characteristics of the grid-connected system by incorporating the effects of virtual inertia coefficients, damping coefficients, and reactive power loop droop coefficients. This solves the problems of traditional models not fully considering the control characteristics of grid-connected converters and the disconnect between energy analysis and actual operating conditions. This application utilizes branch potential energy distribution characteristic analysis to clarify the energy concentration and dispersion laws of critical cut-set branches, overcoming the limitations of traditional global energy methods in locating weak points and the lack of quantitative capabilities in the equal-area criterion, significantly improving the accuracy of stability determination and the efficiency of critical branch location. Simultaneously, this invention constructs a GBTSI quantitative criterion based on the difference between branch potential energy changes and equivalent power, achieving accurate assessment of system stability and fault severity based on the magnitude and trend of the index values, and has been verified in a grid-connected grid-connected system with a grid-connected converter. Compared with traditional stability analysis methods, the proposed criteria show higher adaptability and reliability in scenarios with large disturbances, power grids with high renewable energy penetration, and various types of fault conditions. It has the advantages of clear principles, simple calculation, easy data acquisition, and strong engineering applicability. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a topology diagram of an improved grid-connected converter grid-connected 3-machine 9-node system according to an embodiment of the present invention; Figure 2 This is a graph showing the potential energy curves of each branch under stable operating conditions according to an embodiment of the present invention. Figure 3 This is a graph showing the potential energy curves of each branch under the unstable working condition according to an embodiment of the present invention. Figure 4 This is a graph showing the absolute value variation of GBTSI for each branch under different fault levels according to an embodiment of the present invention. Figure 5 This is a schematic flowchart of a transient synchronization stability determination method for a grid-connected system of a grid-connected converter based on branch energy, according to an embodiment of the present invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0020] like Figure 5 As shown in the figure, this embodiment proposes a transient synchronization stability determination method for grid-connected systems with grid-connected converters based on branch energy, including: Step 1. Analyze the impact of grid converter control parameters on system energy and branch potential energy distribution characteristics; wherein, the grid converter control parameters include: virtual inertia coefficient. J Damping coefficient D and reactive power droop coefficient D q ; Step 2. Construct a transient characteristic model of the grid-type converter; Step 3. Based on the transient characteristic model of the grid-type converter, construct the branch stability discrimination index and perform transient synchronous stability discrimination.

[0021] This embodiment constructs branch energy functions by combining the control characteristics of grid-type converters, transforming the system dynamics problem into energy characteristic analysis. This solves the problems of traditional methods being difficult to adapt to grid-type equipment and lacking quantitative criteria. This embodiment quantifies the system stability and fault severity through the proposed stability discrimination index, accurately locating critical cut-set branches. The results are verified through a case study of an improved grid-type converter grid-connected 3-machine 9-node system. It overcomes the limitations of traditional energy function methods, such as complex calculations and inability to locate weak points, significantly improving the engineering practicality of the criteria. Compared to traditional stability criteria, the proposed method exhibits higher discrimination accuracy and adaptability in high-penetration scenarios of grid-type converters, providing a basis for system fault isolation and recovery, and possessing significant theoretical value and promising engineering application prospects.

[0022] Specifically, in this embodiment, the transient energy characteristics analysis of the grid-connected system of the grid-connected converter is as follows: The transient energy response characteristics of a grid-type converter are mainly determined by three types of core control parameters, namely the virtual inertia coefficient. J Damping coefficient D and reactive power droop coefficient D qThese three types of parameters directly affect the grid-connected system's disturbance rejection capability and transient recovery characteristics by altering the distribution relationship between the system's kinetic energy, damping energy, and potential energy. Therefore, this paper employs a single-parameter variable method, combined with quantitative formulas, to analyze how the control parameters of the grid-connected converter affect the system's potential energy changes.

[0023] Inertia coefficient J It is the core characteristic parameter of the system's kinetic energy storage capacity, and its relevant expression is: ; In the formula: The total kinetic energy of the system. branch road k angular frequency.

[0024] Simulation verification revealed the inertia coefficient J As the inertia coefficient increases, the maximum kinetic energy that the system can store increases, its buffering capacity against sudden disturbances is enhanced, and the amplitude of potential energy oscillations is significantly reduced; on the other hand, a larger inertia coefficient... J This leads to an increase in the accumulated kinetic energy after the disturbance, requiring a longer time to release it through damping or potential energy conversion, thus prolonging the system's transient recovery period. Therefore, the inertia coefficient... J The size selection needs to strike a balance between disturbance rejection buffering capability and recovery speed.

[0025] Damping coefficient D The ability to dissipate oscillatory energy by generating damping power reflects the system's capacity to dissipate oscillatory energy, and its relevant expression is: ; The visible damping coefficient was verified through simulation. D Increasing the damping power directly improves the rate of energy dissipation. The larger the amplitude of the damping power, the faster the system's oscillating energy is consumed, and the peak value and fluctuation amplitude of the potential energy will decrease, shortening the time for the system to recover to steady state after a fault. However, it should be noted that the damping coefficient... D It's not always better to have a larger damping. Excessive damping can lead to sluggish system response and affect the ability to quickly adjust voltage and frequency.

[0026] The core of reactive power droop control is to simulate the reactive power droop characteristics of a synchronous generator, indirectly influencing the potential energy distribution of branches by regulating the virtual internal potential. Its relevant expression is: ; In the formula: The voltage loop integral coefficient; and These are the reference reactive power and the output reactive power, respectively. This is the reactive power loop droop coefficient; This is the rated output voltage.

[0027] The sag coefficient was obtained through simulation verification. D q The larger the droop coefficient, the stronger its ability to withstand voltage changes, and therefore the smaller the amplitude of potential energy changes. However, the droop coefficient should not be too small or too large. If it is too small, the system will not be able to withstand voltage fluctuations, and the potential energy will fluctuate violently; if it is too large, it may cause branch overcurrent risks. The three parameters work together to regulate the system's energy storage, dissipation and distribution, and jointly determine the transient stability performance of the grid-connected system of the grid-connected converter.

[0028] After analyzing the influence of control parameters on the system potential energy, the distribution characteristics of branch potential energy are analyzed. After a system failure, transient energy concentrates in the critical branches, and its distribution characteristics directly determine the system stability: Under stable conditions, the phase angle difference and potential energy of each branch fluctuate within a limited range, and the potential energy change amplitude of the critical branch is significantly greater than that of other branches; under unstable conditions, the phase angle difference and potential energy of some branches will show an oscillating divergence trend. At this time, the branch becomes the critical cut set of the system "tear", and its potential energy concentration and divergence are the essential characteristics of system instability, while the phase angle difference and potential energy of other branches maintain bounded changes.

[0029] More specifically, the characteristic analysis of the branch potential energy distribution includes: A three-phase short-circuit fault was introduced into a branch of a grid-connected infinite bus system using a grid-connected converter. By adjusting the fault clearing time, two operating conditions were obtained: stable and unstable. Based on this condition, the phase angle difference characteristics and transient potential energy distribution of each branch were analyzed to determine the critical cut-set branch of the system. It was clarified that the concentration and divergence of potential energy in the branch is the core essence of system instability, and it was verified that the potential energy change of the critical cut-set branch has a decisive influence on the system's stable state.

[0030] Furthermore, step 2, constructing the transient characteristic model of the grid-type converter, includes: For a single-machine infinite bus system, based on the virtual rotor motion equations, active-frequency loop, and reactive-voltage loop control mechanisms of the grid-type converter, the power angle swing equation, reactive-voltage control equation, and mathematical expressions for instantaneous output active power are derived. Key parameters such as the equivalent inertia time constant and equivalent damping coefficient are introduced, and combined with the inherent correlation of branch phase angle differences, a total system energy function is constructed, encompassing system kinetic energy, transient potential energy, and damping energy. In other words, detailed modeling is performed on the single-machine infinite bus system, and the modeling results are extended to multi-machine systems through the single-machine infinite bus system.

[0031] For multi-machine systems, an augmented network correlation matrix is ​​introduced to establish the transient energy function of the multi-machine system branch, which includes synchronous generators, grid-type converters and loads. The active power balance constraints of each node are taken into account to construct the transient energy function of the multi-machine system.

[0032] Specifically, in this embodiment, step 2, the construction of the transient model of the grid-type converter, includes: Based on the grid-connected infinite bus system of grid-type converter, the core of this study is to simulate the rotor motion and excitation characteristics of synchronous generators. By quantifying the coupling relationship between key control parameters and system energy, the fundamental equations of energy characteristics are established.

[0033] The phase difference between the filter capacitor voltage of the grid converter and the grid voltage is defined as the power angle. The grid voltage phase angle is used as the reference phase angle, and its dynamic relationship with the angular velocity is as follows: ; In the formula: and These are the angular velocities of the grid-connected converter and the power grid, respectively. .

[0034] The power angle swing equation reflects the motion characteristics of a virtual rotor, describing the dynamic relationship between active power balance and angular velocity and power angle. It is the core equation for energy characteristic analysis. ; In the formula: For virtual inertia coefficient, The rated angular frequency, For the angular velocity of the grid-type converter, For reference active power, To output active power, is the damping coefficient.

[0035] The reactive power-voltage control equation characterizes the regulation law of the virtual internal potential, reflects the coupling relationship between reactive power and voltage, and directly affects the power and potential energy distribution of the branch: ; Unlike grid-connected converters, which indirectly affect the grid through current, grid-connected converters can directly control the amplitude and phase of the voltage at the grid connection point. Therefore, it is necessary to construct a branch transient model specifically to highlight its inherent grid-connected characteristics. Assuming that line resistance and current loop dynamics are ignored, and a unity power factor control mode is adopted, the q-axis components of the voltage at each node in the grid-connected converter system do not need to consider current coupling terms, and their expressions are as follows: ; In the formula: Let be the line inductance from node m-1 to node m.

[0036] Combining the q-axis component expressions of the voltages at each node with the instantaneous power equation, the instantaneous output active power of the grid-type converter can be obtained as follows: ; Substituting into the swing equation, it can be expressed as: ; Therefore, the energy function is constructed as follows: ; In the formula: The total energy of the system. As the system's kinetic energy, For the system's transient state energy, For the system damping energy, For the line k The phase angle difference, For the line in the stable state of the system k The phase angle difference, For equivalent electromagnetic power, This is the steady-state value of the equivalent power. This represents the equivalent damping coefficient for grid-connected grid-type converters. The specific expressions for the equivalent electromagnetic power and its steady-state value are shown below: ; From the above expression, it can be seen that in a grid-connected converter system, the branch... k The transient state energy is mainly related to the phase angle difference of the branch.

[0037] To adapt to complex power system scenarios, the single-machine infinite bus system model is extended to a multi-machine system, taking into account the coordinated effects of multiple grid-connected converters, synchronous generators, and loads. It is assumed that the power system augmentation network includes... n Each node m Taiwan-type grid converter l A network branch, m+1 arrive m+n 0 The nodes are connected to synchronous generators, which employ a classic second-order model. Based on topological relationships and power flow equations, the state-space representation of the multi-machine system is established: ; In the formula: The equivalent inertial time constant matrix, For the angular velocity vector of the grid-type converter, It is the identity matrix. The equivalent electromagnetic power of each branch, The equivalent power steady-state value for each branch is given. The damping coefficient is the damping coefficient of the grid-type converter.

[0038] Taking the branch phase angle difference at the time of fault clearing as the reference point, and considering the energy components of the synchronous generator, the transient energy function of the multi-machine system is: ; This multi-machine system model retains the grid-connected characteristics of grid-connected converters while also being compatible with the dynamic behavior of traditional synchronous generators, providing a general framework for transient stability analysis of large-scale renewable energy grid-connected systems.

[0039] Specifically, in this embodiment, step 3, the construction of the GBTSI transient synchronization stability discrimination method, includes: Based on the energy characteristics of grid-forming converters, a branch stability discrimination index GBTSI (Grid-Forming Converter Branch Transient Stability Index) is defined. ; In the formula: branch road k The equivalent electromagnetic power; branch road k The equivalent power steady-state value; branch road k The change in temporary state energy has .

[0040] This discrimination method quantifies the energy balance state of a branch by comparing the equivalent power difference with the change in transient potential energy. Its core characteristic is that when a branch is stable, GBTSI ≠ 0, indicating stable branch potential energy; when a branch is unstable, GBTSI = 0, indicating divergent branch potential energy. Furthermore, the closer the absolute value of GBTSI is to 0, the worse the branch stability; the branch closest to 0 is the critical cutset of the system. Simultaneously, its absolute value decreases as the fault severity increases, enabling a quantitative assessment of fault severity. The criterion inherits the core logic of Lyapunov's direct method, overcoming the limitations of complex global energy function calculations. It only requires easily obtainable data such as branch phase angle difference and power, making it suitable for engineering applications.

[0041] The value of the branch stability discrimination index determines the stability of the system. The closer the value of the branch stability discrimination index is to 0, the worse the stability of the branch, indicating that the system fault is more serious. The branch closest to 0 is the critical cut set of the system. Therefore, when the branch is stable, the value of the branch stability discrimination index is not equal to 0; when the branch is unstable, the value of the branch stability discrimination index is equal to 0.

[0042] This embodiment presents a transient synchronization stability determination method for grid-connected systems with grid-connected grid-connected converters based on branch energy. The method includes: constructing a transient characteristic model of the grid-connected converter, analyzing the transient characteristics of the grid-connected system, constructing a GBTSI transient synchronization stability criterion, and performing scenario simulation verification. By incorporating the effects of virtual inertia coefficients, damping coefficients, and reactive power loop droop coefficients, this method constructs a branch energy function adapted to the characteristics of the grid-connected system, solving the problems of traditional models not fully considering the control characteristics of grid-connected converters and the disconnect between energy analysis and actual operating conditions. This application utilizes branch potential energy distribution characteristic analysis to clarify the energy concentration and dispersion laws of critical cut-set branches, overcoming the limitations of traditional global energy methods in locating weak points and the lack of quantitative capabilities in the equal-area criterion, significantly improving the accuracy of stability determination and the efficiency of critical branch location. Simultaneously, this invention constructs a GBTSI quantitative criterion based on the difference between branch potential energy changes and equivalent power, achieving accurate assessment of system stability and fault severity based on the magnitude and trend of the index values, and has been verified in a grid-connected grid-connected system with a grid-connected converter. Compared with traditional stability analysis methods, the proposed criteria show higher adaptability and reliability in scenarios with large disturbances, power grids with high renewable energy penetration, and various types of fault conditions. It has the advantages of clear principles, simple calculation, easy data acquisition, and strong engineering applicability.

[0043] This embodiment proposes a transient synchronization stability determination method for grid-connected systems with grid-connected converters based on branch energy, such as... Figures 1-4 As shown, it includes the following steps: (1) Based on the actual power grid topology, construct a simulation model including grid-type converters, synchronous generators, lines and loads, and determine key parameters such as virtual inertia coefficient J, damping coefficient D, and reactive power loop droop coefficient Dq; (2) Based on the power angle swing equation, reactive power-voltage control equation and system energy function of the grid-type converter, clarify the influence law of each parameter on the energy characteristics and construct the transient characteristic model of the grid-type converter; (3) Obtain key data such as branch phase angle difference, active power, reactive power, and voltage amplitude in steady state and after a fault in the system; (4) Calculate the change in transient potential energy and the difference in equivalent power of each branch based on the measurement data, and calculate the branch potential energy and GBTSI index. (5) Based on the magnitude, sign and trend of the GBTSI index, determine whether the system is stable, quantify the severity of the fault, and locate the critical cut set branch; (6) Analyze the output results to clarify the transient synchronous stable state, fault level and critical branch location of the system, so as to provide a basis for system fault isolation and recovery.

[0044] To verify the effectiveness of the stability determination method proposed in this embodiment, an improved grid-connected converter system with 3 generators and 9 nodes was selected as the verification object based on the DIgSILENT / PowerFactory simulation platform. Its system topology diagram is shown below. Figure 1 As shown; where the system base capacity is 250MVA, the base voltage is 230kV, the system synchronous angular velocity is 314rad / s, the grid-type converter 1 has a rated active power of 80MW, J=500, D=10, the grid-type converter 2 has a rated active power of 120MW, J=400, D=10, the synchronous machine G2 has an inertial time constant of 6.667s and an apparent power of 192MVA, the inductance of critical lines 2-7 is 38.088H, the inductance of line 5-7 is 10.165H, and the inductance of line 7-8 is 20.088H.

[0045] In the stable operating condition verification, a three-phase short-circuit fault lasting 0.2s was set at 1s on line 7-8 to simulate the system's return to stability after the fault was cleared. The potential energy change trend of each branch was obtained using data such as phase angle difference and active power, and the GBTSI value was calculated. The potential energy curves of each branch under stable operating conditions are shown below. Figure 2 As shown, the potential energy curves of each branch did not diverge, and the GBTSI values ​​of each branch were not 0. However, the GBTSI value of branch 5-7 was the lowest at 6.91, followed by branches 2-7 at 16.35 and 4-5 at 22.21. Therefore, these three branches were identified as potential weak links in the system, which echoed the results of subsequent instability tests and verified the critical branch prediction capability of the criterion.

[0046] The instability verification kept the fault type unchanged, but extended the fault clearing time to 0.25s to simulate the system losing stability after fault clearing, and repeated the above process. The potential energy curves of each branch under the instability condition are shown below. Figure 3 As shown, the potential energy of branches 2-7, 4-5, and 5-7 exhibits a monotonically divergent trend, with GBTSI values ​​of 0.98, 3.96, and 4.13, respectively. The GBTSI of branch 2-7 is closest to 0, so it is determined to be the critical cut set of the system. Further analysis of the relative phase angles of each generator reveals that G2 loses synchronization with other generators, and the system is "torn apart" at branch 2-7, which is completely consistent with the GBTSI criterion result.

[0047] In the fault severity quantification verification, fault clearing times were set to 0.2s, 0.21s, 0.22s, 0.23s, 0.24s, and 0.25s to simulate faults of different severity, and the absolute values ​​of GBTSI for each branch under different fault severity were calculated. For example... Figure 4 As shown, as the fault severity increases, the absolute value of GBTSI of branch 2-7 continuously decreases from 16.35 to 0.98, showing a significant linear decreasing relationship, which fully verifies the criterion's ability to quantify the fault severity.

[0048] A comparison between the traditional equal-area criterion and the global energy function method reveals that the equal-area criterion can only qualitatively determine stability and instability, but cannot quantify the degree of fault or locate critical branches. The global energy function method has high computational complexity, requiring the solution of high-order matrices, and struggles to distinguish branch energy differences, easily misidentifying non-critical branches as weak points. In contrast, the discrimination method proposed in this invention only requires easily obtainable data such as branch phase angle difference and power, has low computational load, and simultaneously achieves stability discrimination, fault quantification, and critical location, significantly outperforming traditional methods in terms of adaptability and practicality.

[0049] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Various modifications and improvements made to the technical solutions of the present invention by those skilled in the art without departing from the spirit of the present invention should fall within the protection scope defined by the claims of the present invention.

Claims

1. A method for determining transient synchronization stability in a grid-connected system of a grid-connected converter based on branch energy, characterized in that, include: Step 1. Analyze the impact of grid converter control parameters on system energy and branch potential energy distribution characteristics; wherein, the grid converter control parameters include: virtual inertia coefficient. J Damping coefficient D and reactive power droop coefficient D q ; Step 2. Construct a transient characteristic model of the grid-type converter; Step 3. Based on the transient characteristic model of the grid-type converter, construct the branch stability discrimination index and perform transient synchronous stability discrimination.

2. The transient synchronization stability determination method for grid-connected systems with grid-connected converters based on branch energy according to claim 1, characterized in that, Step 1 analyzes the impact of grid-type converter control parameters on system energy, including: The single-parameter variable method, combined with quantization formulas, is used to analyze the impact of grid-type converter control parameters on system energy.

3. The transient synchronization stability determination method for grid-connected systems of grid-connected converters based on branch energy according to claim 2, characterized in that, Using the single-parameter variable method combined with quantization formulas, the impact of grid-type converter control parameters on system energy is analyzed, including: The virtual inertia coefficient J , used to characterize the system's ability to store kinetic energy; For the virtual inertia coefficient J The mathematical expression for the system's kinetic energy is: ； in, The total kinetic energy of the system; Let be the angular frequency of branch k, n be the total number of branches in the system with virtual inertia characteristics, and k be the branch number. The rated angular frequency; Based on the mathematical expression for the system's kinetic energy, we can deduce that the system's kinetic energy is related to its inertia coefficient. J There is a linear positive correlation; increasing the inertia coefficient... J It can enhance the system's ability to absorb disturbance energy, thereby reducing the severity of frequency fluctuations after being disturbed.

4. The transient synchronization stability determination method for grid-connected systems of grid-connected converters based on branch energy according to claim 2, characterized in that, Using the single-parameter variable method combined with quantization formulas, the impact of grid-type converter control parameters on system energy is analyzed, including: The damping coefficient D This is used to reflect the system's ability to dissipate oscillatory energy; For the damping coefficient D The expression for the system's damping energy is: ； in, For the system damping energy, It is the difference in angular frequency. P D Damping power; Based on the expression for system damping energy, it can be concluded that system damping energy is positively correlated with the damping coefficient, and the damping coefficient... D The larger the value, the faster the system's oscillation energy dissipates.

5. The transient synchronization stability determination method for grid-connected systems with grid-connected converters based on branch energy according to claim 2, characterized in that, Using the single-parameter variable method combined with quantization formulas, the impact of grid-type converter control parameters on system energy is analyzed, including: Regarding the reactive power loop droop coefficient D q The expression for the reactive power-voltage control loop is: ； in, E For virtual internal potential, The voltage loop integral coefficient, and These are the reference reactive power and the output reactive power, respectively. This is the rated output voltage. This is the voltage reference value.

6. The transient synchronization stability determination method for grid-connected systems with grid-connected converters based on branch energy according to claim 1, characterized in that, Step 1 analyzes the branch potential energy distribution characteristics, including: A three-phase short-circuit fault is set in the branch of the grid-connected infinite bus system of the grid-type converter. By adjusting the fault clearing time, two operating conditions, namely stable and unstable, are obtained. Based on the analysis of the phase angle difference characteristics and transient potential energy distribution of each branch under the two operating conditions, the critical cut set branch of the system was determined, and it was clarified that the concentration and divergence of potential energy of the branch is the core essence of system instability. It was verified that the potential energy change of the critical cut set branch has a decisive influence on the stable state of the system.

7. The transient synchronization stability determination method for grid-connected systems with grid-connected converters based on branch energy according to claim 1, characterized in that, Step 2 involves constructing the transient characteristic model of the grid-type converter, including: For a single-machine infinite bus system, based on the virtual rotor motion equation of the grid converter, the active-frequency loop and the reactive-voltage loop control mechanism, the power angle swing equation, the reactive-voltage control equation and the mathematical expression of the instantaneous output active power are derived. The equivalent inertial time constant and the equivalent damping coefficient are introduced as key parameters. Combined with the inherent correlation of the branch phase angle difference, the total system energy function including system kinetic energy, transient potential energy and damping energy is constructed. For multi-machine systems, an augmented network correlation matrix is ​​introduced to establish the transient energy function of the multi-machine system branch, which includes synchronous generators, grid-type converters and loads. The active power balance constraints of each node are taken into account to construct the transient energy function of the multi-machine system.

8. The transient synchronization stability determination method for grid-connected systems with grid-connected converters based on branch energy according to claim 7, characterized in that, The total energy function of the system is: ； in, The total energy of the system. As the system's kinetic energy, For the system's transient state energy, For the system damping energy, The phase angle difference of line k. The phase angle difference of line k under stable system conditions. For equivalent electromagnetic power, This is the steady-state value of the equivalent power. This is the equivalent damping coefficient for grid-connected grid-type converters; The equivalent electromagnetic power and its steady-state value are: ； in, To output reactive power, D The damping coefficient of the grid-type converter. For line current, The phase difference between the voltage of the GFM-VSC filter capacitor and the mains voltage. This is a reference value for active power. The equivalent inductance on the output side of the GFM-VSC; The transient energy function of the multi-machine system is: ； Where m is the number of GFM-VSCs in the multi-machine system, i is the generator unit number, l is the total number of transmission lines included in the transient energy calculation, b is the transmission line number, and n0 is the total number of synchronous generator units in the multi-machine system. E Ki Let be the transient kinetic energy of the i-th GFM-VSC. E pb The transient state performance of the i-th GFM-VSC E Kgi Let be the transient kinetic energy of the i-th synchronous generator. E pgi Let be the transient potential energy of the i-th synchronous generator. E Di Let be the damping energy of the i-th synchronous generator.

9. The transient synchronization stability determination method for grid-connected systems with grid-connected converters based on branch energy according to claim 1, characterized in that, The stability criterion for the branch is: ； in, branch road k The equivalent electromagnetic power; branch road k The equivalent power steady-state value; branch road k The change in temporary state energy.

10. The transient synchronization stability determination method for grid-connected systems with grid-connected converters based on branch energy according to claim 1, characterized in that, The transient synchronization stability determination includes: The stability of the system is judged by the value of the branch stability discrimination index. The closer the value of the branch stability discrimination index is to 0, the worse the stability of the branch, indicating that the system fault is more serious. The branch closest to 0 is the critical cut set of the system. Therefore, when the branch is stable, the value of the branch stability discrimination index is not equal to 0; when the branch is unstable, the value of the branch stability discrimination index is equal to 0.

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