A method and system for analyzing synchronous instability of a new energy base compensator

Abstract

The application discloses a new energy base phase modifier synchronous instability analysis method and system, and belongs to the technical field of power system stability analysis. The method comprises the following steps: obtaining a training data set covering multi-dimensional power grid parameters and fault scenes, calculating dominant degree factors based on the coupling dynamic index of inverters, and dividing multiple dominant degree factor intervals to represent the control dominance of different types of inverters; a risk guardrail set containing a power coupling index and a damping ratio change amount is constructed, and a differentiated threshold is set for each interval; the control parameters of the inverters are extracted and a candidate boundary line set is generated, the performance of the candidate boundary line set is evaluated through transient simulation, the priority value is calculated by comprehensively considering the deployable proportion, the time benchmark ratio and the safety coefficient, and the optimal target boundary line is selected; finally, the target boundary line parameters are mapped into adaptive control gears, and the coordinated control of the phase modifier and the inverter is realized in combination with the real-time risk state, so that the synchronous instability risk is effectively inhibited.

Description

Technical Field

[0001] This invention relates to the field of power system stability analysis technology, and more specifically, to a method and system for analyzing the synchronous instability of synchronous condensers in new energy bases. Background Technology

[0002] With the integration of large-scale renewable energy sources such as wind and solar power, the power grid is exhibiting strong DC and weak AC characteristics: the rapid growth in the scale of DC transmission projects and the increase in the equivalent short-circuit impedance of the AC grid have led to a significant decrease in the equivalent short-circuit ratio. In this weak grid environment, long-distance power transmission from large-scale renewable energy bases can easily cause problems such as voltage over-limit, wide-frequency oscillation, and even grid disconnection of renewable energy units. Synchronous condensers, as a type of synchronous motor that only outputs reactive power, has large inertia, and fast response, and has rapid voltage support and inertia support capabilities, are widely used in the vicinity of renewable energy bases to improve grid stability and renewable energy acceptance. However, unlike traditional synchronous generators, synchronous condensers do not provide active mechanical power from generators; they only receive power from the grid, and their power angle characteristics change significantly in weak grids. When synchronous condensers are connected to large-scale renewable energy bases, the impact of renewable energy power injection on the system's power angle stability is similar to the effect of wind turbines on synchronous machines in a wind-fire bundled scenario. In other words, in systems where renewable energy is the main power source, synchronous condensers may experience transient power angle instability risks, which manifest as rotor power angle loss of synchronism, excessive oscillation, and asynchrony with the grid under fault impact.

[0003] Furthermore, traditional transient stability analysis methods mainly include critical fault analysis based on time-domain simulation and the equal area criterion (EAC) method based on energy functions. Time-domain simulation can accurately reproduce the nonlinear oscillation of the motor and the dynamics of the controller, but it is extremely time-consuming for complex power grids and is only suitable for offline planning or emergency analysis requiring limited fault scenarios. The equal area criterion judges synchronous instability by comparing the acceleration area and deceleration area after a fault, which has strong physical significance under simplified models. In recent years, researchers have proposed an improved method based on reconstructing equal area from measurement signals. However, the traditional derivation of EAC assumes stable system parameters and does not consider the time-varying characteristics of power electronic control. When the proportion of new energy sources is high and the control strategy is complex, using a fixed energy area difference as the instability criterion will produce a large error.

[0004] To address the above problems, this invention proposes a solution. Summary of the Invention

[0005] In order to overcome the above-mentioned defects of the prior art, embodiments of the present invention provide a method and system for analyzing the synchronous instability of synchronous condensers in new energy bases, so as to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] A method for analyzing synchronous instability of synchronous condensers in a new energy base includes the following steps: obtaining a training dataset of the new energy base and calculating the dominance factor by calling the coupling dynamic index of the inverter in the training dataset, wherein the training dataset covers various grid parameters, fault types and inverter control parameters;

[0008] Multiple dominance factor intervals are divided based on the dominance factor, and a risk guardrail set including power coupling index and damping ratio change is defined. Risk threshold conditions are set for each dominance factor interval; the inverter includes grid-connected inverters and grid-connected inverters.

[0009] Extract the inverter control parameter range from the training dataset, determine the parameter range of the low-frequency side bandwidth control coefficient and the high-frequency side bandwidth control coefficient, and select multiple discrete points within the parameter range to generate a candidate boundary line set;

[0010] For each candidate boundary line, transient simulation is performed using the training dataset to obtain performance indicators including power coupling index and damping ratio change; the deployable ratio is calculated based on performance indicators and risk threshold conditions; the time base ratio is calculated based on the typical transient constant of the synchronous condenser and the effective time constant of the inverter; and the safety factor is calculated based on risk threshold conditions and performance indicators.

[0011] Based on the obtained deployable ratio, time base ratio, and safety factor, the priority value of each candidate boundary line is calculated; the candidate boundary line with the highest priority value is selected as the target boundary line for synchronous instability analysis of the camera.

[0012] In a preferred embodiment, the dominance factor is calculated using the following formula: ;in, As the dominant factor, To match the phase angle disturbance amplitude response of the phase-locked loop (PLL) in the grid-connected inverter, The phase angle disturbance amplitude response of the virtual synchronous machine (VSM) in a grid-connected inverter; and Obtained through system linearization model analysis or time-domain simulation.

[0013] In a preferred embodiment, dividing multiple intervals based on the dominance factor includes: dividing the theoretical range of values ​​for the dominance factor α. Divided into three consecutive intervals, with the interval boundaries including: and ,satisfy ;when When, it is defined as the dominant region of a phase-locked loop (PLL) inverter; when When, it is defined as the equalization contribution range between the phase-locked loop (PLL) inverter and the virtual synchronous machine (VSM) inverter; when When, it is defined as the dominant region of a Virtual Synchronous Machine (VSM) type inverter; where, and Based on the statistical distribution of the dominance factor α values ​​in the training dataset, the inflection point of the slope change of the cumulative density function CDF is determined.

[0014] In a preferred embodiment, the risk barrier set includes the power coupling index and damping ratio variation, and risk threshold conditions are set for each dominance factor interval as follows: differentiated red line conditions and yellow line conditions are set for each dominance factor interval; the red line condition is a high-level threshold condition, and the yellow line condition is a medium-level threshold condition; for the dominance interval of phase-locked loop (PLL) inverters, the equalization contribution interval of PLL inverters and virtual synchronous machine (VSM) inverters, and the dominance interval of VSM inverters, corresponding high-level thresholds are set respectively. With intermediate threshold , where x=1,2,3 correspond to the dominant region of the phase-locked loop PLL inverter, the balanced contribution region of the phase-locked loop PLL inverter and the virtual synchronous machine (VSM) inverter, and the dominant region of the virtual synchronous machine (VSM) inverter, respectively. The power coupling index is calculated by taking the ratio of the partial derivatives of different control input dimensions with respect to the active and reactive power output dimensions of the inverter, and selecting the maximum value. The damping ratio is obtained by subtracting the initial damping ratio of the oscillation mode before the fault from the subsequent damping ratio of the oscillation mode after the fault is cleared.

[0015] In a preferred embodiment, the candidate boundary set is generated by determining the low-frequency side bandwidth control coefficient. The parameter range is Used to control the proportional characteristics of the phase angle element in grid-connected inverters and the proportional characteristics of the power response in grid-connected inverters; to determine the high-frequency side bandwidth control coefficient. The parameter range is This parameter is used to control the frequency threshold of the inverter's filtering or integrating stage; the parameter range is based on the initial value range determined by typical inverter controller technical specifications; and it is also used for the low-frequency bandwidth control coefficient. and high-frequency side bandwidth control coefficient Multiple discrete value points are selected within the parameter range; the low-frequency side bandwidth control coefficient is... and high-frequency side bandwidth control coefficient The discrete points are combined in pairs to form multiple candidate boundary lines. This constitutes a set of candidate boundary lines to ensure coverage of control requirements corresponding to different dominance factor α intervals; where p is the index identifier of the candidate boundary line, representing the p-th candidate boundary line combination.

[0016] In a preferred embodiment, the deployable ratio The calculation formula is: , where 1[·] is an indicator function, Candidate dividing line The corresponding number of simulation samples, This serves as a feasibility indicator for the p-th candidate boundary line in the u-th sample; the time baseline ratio is... ,in To adjust the typical transient constant of the camera, The effective time constant of the inverter is calculated using the following formula: , The rated angular frequency of the power grid; the formula for calculating the safety factor is: ,in This means iterating through all simulation scenarios and taking the minimum value.

[0017] In a preferred embodiment, performing transient simulation using a training dataset includes: randomly sampling operating condition samples from the training dataset, the operating condition samples covering the entire dominance factor α range, short-circuit ratio, and the ratio of line resistance to reactance. And the fault type, while keeping the original power grid parameters of the sample unchanged. Calculations are performed based on the aforementioned performance metrics and risk threshold conditions, including boundary violation determination according to the following rules:

[0018] If all the aforementioned performance indicators do not exceed the yellow line threshold in the risk barrier set, then a feasibility indicator is displayed. The candidate boundary line is determined to be deployable;

[0019] If any of the performance indicators exceeds the red line threshold in the risk barrier set, then a feasibility indicator is displayed. The candidate boundary line is determined to be undeployable;

[0020] If the performance index is between the yellow line threshold and the red line threshold, the candidate boundary line is determined to be deployable but with low priority, and its conservative margin is reflected by the safety factor in the priority value calculation.

[0021] In a preferred embodiment, a priority value is calculated for each candidate boundary line; the candidate boundary line with the highest priority value is selected as the target boundary line, specifically: priority value The calculation formula is: ,in , , It is a positive proportionality coefficient, and Calculate the priority value of all candidate boundary lines. Choose to prioritize The largest candidate boundary line is taken as the target boundary line B*; if multiple candidate boundary lines exist, their priority values ​​are... If the difference is less than the preset approximate threshold, the one with the most balanced deployment ratio in each dominant factor α interval is selected as the target boundary line, and the suboptimal solution is reserved as a backup boundary line.

[0022] In a preferred embodiment, based on the control parameters corresponding to the target boundary line, combined with the dominance factor α interval obtained from real-time analysis and the current risk level determined based on the risk barrier set, the parameters are mapped to multiple preset adaptive control levels. These levels include at least three grades: low, medium, and high. The mapped control levels and their corresponding parameter sets are output to the control systems of the synchronous condenser and inverter to guide adaptive parameter adjustments, thereby suppressing the risk of synchronization instability. The switching of control levels must meet the dwell time condition determined based on the target boundary line, and the parameter sets are generated by scaling the target boundary line parameters proportionally to the current level and the dominance factor interval, while ensuring that the inverter's voltage regulation frequency band avoids the dedicated control range of the power system stabilizer. The scaling is performed using a scaling formula for the target boundary line. Discrete scaling: ; ;in, , The fixed ratio coefficient for the range from gear position to the dominant factor α; This represents the bandwidth control parameters on the low-frequency and high-frequency sides that are actually output to the control system after scaling. , BL represents the initial values ​​of the bandwidth control coefficients on the low-frequency and high-frequency sides corresponding to the target boundary line B*; BL represents the adaptive control gear obtained by mapping.

[0023] A synchronous instability analysis system for a new energy base synchronous condenser includes: an impact assessment module for acquiring a training dataset and calculating the dominance factor and dividing intervals; a baseline deformation generation module for constructing a risk barrier set and setting threshold conditions; a residual deformation learning module for generating a candidate boundary line set, performing transient simulation, and calculating the deployable ratio, time base ratio, and safety factor; and a fusion and closed-loop correction module for calculating priority values, selecting target boundary lines, and outputting synchronous instability analysis results.

[0024] The technical effects and advantages of the present invention regarding the synchronous instability analysis method and system for synchronous condensers in new energy bases are as follows:

[0025] This invention achieves precise quantitative assessment of the synchronous instability risk of synchronous condensers in power grids with a high proportion of renewable energy by constructing a set of dominance factors and risk guardrails; it adopts a candidate boundary line optimization mechanism to ensure optimal adaptability of control parameters under different operating scenarios; and finally, through adaptive control level mapping and dwell switching logic, it realizes coordinated control of synchronous condensers and multiple types of inverters. This method significantly improves the power angle stability and damping characteristics of the system in weak grid environments, effectively suppresses broadband oscillations and synchronous instability risks, and enhances the transmission reliability and acceptance capacity of renewable energy bases. Attached Figure Description

[0026] Figure 1 This is a flowchart illustrating the synchronous instability analysis method for a new energy base synchronous condenser according to the present invention.

[0027] Figure 2 This is a schematic diagram of the synchronous instability analysis system for a new energy base synchronous condenser according to the present invention. Detailed Implementation

[0028] 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.

[0029] For an example, please refer to... Figure 1 As shown, this invention discloses a method for analyzing the synchronization instability of synchronous condensers in new energy bases, comprising the following steps:

[0030] Step S1: Obtain the training dataset of the new energy base. The training dataset covers multiple grid operation dimensions, including: short-circuit ratios at different levels to characterize grid strength, line resistance to reactance ratios at different ranges to characterize network impedance characteristics, various types of fault events and their durations, and inverter control parameters with different configurations; call the coupling dynamic index of the inverter in the training dataset. The coupling dynamic index includes the phase angle disturbance amplitude response of the phase-locked loop corresponding to the grid-type inverter and the phase angle disturbance amplitude response of the virtual synchronous machine corresponding to the grid-connected inverter; based on the coupling dynamic index, calculate the dominance factor to quantify the relative dominance of the two types of inverters in the system;

[0031] To study the coordinated control of synchronous condensers and grid-connected converters under conditions of high renewable energy ratio, the synchronous condenser is in grid-connected mode with no prime mover at its mechanical end. The dynamic modeling model of the joint system includes three sub-parts: electromechanical oscillation equations, electromagnetic power equations, and excitation regulation equations. The rotating machinery includes the synchronous condenser, and the power electronic equipment includes two types of inverters: grid-connected type relying on phase-locked loops (PLLs), denoted as GFL, and dominant type employing control strategies such as virtual synchronous machines (VSMs), denoted as GFM. The network part uses the equivalent ratio of line resistance to reactance. Describe the characteristics of the transmission line. It can be determined by regional measurements and statistics;

[0032] The modeling objective is to construct a set of dynamic equations applicable to electromechanical transient timescales. This model should be able to simultaneously describe the synchronous condenser's inertial response, GFL / VSM control dynamics, and grid voltage phase changes. To avoid high-dimensional electromagnetic detail models, this scheme uses a second-order equivalent model to construct the synchronous condenser's dynamic model and introduces a dominance factor α to characterize the relative dominance of the grid-connected GFL and the dominant GFM control systems. Specifically, the models for each subsystem are constructed as follows:

[0033] The dynamic model of the synchronous condenser assumes that the rotor angular frequency of the synchronous condenser is... The grid / network reference frequency is The difference between the two is the relative angular velocity. The rotor power angle is defined as follows: ;in, It's adjusting the camera's internal potential angle. It is the grid potential angle; since the synchronous condenser has no mechanical input power, its mechanical power... Electromagnetic power Equivalent power loss Including stator copper loss, iron loss, windage loss and speed damping term The electromechanical oscillation equation, based on the second-order oscillation model, is expressed as: ;in, It is the equivalent inertia constant of the camera. It is the electrical damping coefficient, and this equation reflects the energy exchange of the moment of inertia during a transient process;

[0034] Electromagnetic power The phase difference between the voltage at the synchronous condenser terminal and the voltage on the grid side is determined and can be approximated by a simple power angle equation. It is worth noting that the synchronous condenser has a large inertia and reactive power support capability, and can achieve rapid reactive power regulation by controlling the excitation. Its importance increases with the increase in the proportion of new energy sources.

[0035] The electromagnetic power This can be derived from the electromagnetic power equation, which states that the synchronous condenser controls its internal electromotive force E through its excitation system; in synchronous coordinates, the internal electromotive force of the synchronous condenser is connected to the external equivalent voltage V through equivalent reactance. The connection can be approximated by a single-axis luminous electrode machine: ;in , It is transient reactance. For transformer leakage reactance, Equivalent reactance of the grid-connected line and external network; external voltage V and phase The control system of the power grid or grid-connected converter is given the following information;

[0036] The excitation system of a synchronous condenser typically consists of a fast automatic voltage regulator (AVR) and a limiter. Here, a common first-order AVR model is used to define the excitation regulation equation:

[0037] ;in This is the excitation control signal. For a given voltage reference, To adjust the voltage amplitude at the camera end, , and , For gain and time constant; considering that the OEL / UEL limiter can introduce nonlinear switching, this scheme uses a soft limiting strategy, defining the limiting coefficient. The AVR output is scaled proportionally when it approaches its limit to avoid secondary instability;

[0038] The power network can be approximated as a system of algebraic equations of impedance matrix and node voltage phase angles in the electromechanical time scale; this scheme adopts a three-node equivalent model: upstream power source node, grid interface node, and load / new energy parallel connection node; line parameters are used... To characterize the network impedance characteristics, the ratio of line resistance to reactance is used. It is the ratio of the equivalent resistance R to the equivalent reactance X of the grid-connected line;

[0039] The high proportion of new energy sources leads to a decrease in system inertia and damping, and an increase in the risk of transient stability of power angle and voltage. Transient stability analysis usually relies on the equal area theorem, EAC, and the critical fault clearing time CCT. This solution follows industry practice and uses EAC to calculate the critical cut-off angle and transient energy margin of the synchronous condenser-inverter during the mechanism analysis and acceptance phase.

[0040] For switch failures or short-circuit disturbances, mechanical and electrical power curves of the synchronous condenser are constructed. The acceleration and deceleration energy regions are solved through numerical integration; if they are equal, the system is in a critical state. The critical clearing angle is then calculated. and critical clearance time This method is used to guide the protection configuration of synchronous condensers and the labeling of simulation training data. Although EAC is only applicable to single-machine infinite bus systems, it is still valuable as a mechanistic analysis tool. In the simulation dataset preparation stage, this scheme uses the equal area theorem of EAC to determine the stability label of samples. , serving as the reference output for training the dominance factor α and the threshold;

[0041] Inverters in renewable energy grid-connected systems can be divided into grid-connected and grid-connected types. To quantitatively measure the contribution of these two types of control to frequency support under different operating conditions, this paper introduces the Coupling Dynamic Index (CDI); defined as follows: This refers to the phase angle disturbance amplitude response of a phase-locked loop (PLL) inverter. The phase angle disturbance amplitude response of a virtual synchronous machine (VSM) inverter; both can be obtained from a linearized model or simulation; then the dominance factor. Defined as: ;in, ;and , This represents the theoretical boundary value.

[0042] The obtained dominance factor The intervals are divided into three categories, and the interval boundary points are defined as follows: , , must meet :

[0043] when When, interval 1 is defined as the dominant interval of a phase-locked loop (PLL) inverter;

[0044] when At that time, interval 2 is defined as the equalization contribution interval between the phase-locked loop (PLL) inverter and the virtual synchronous machine (VSM) inverter;

[0045] when At that time, interval 3 is defined as the dominant interval of the Virtual Synchronous Machine (VSM) type inverter;

[0046] The interval boundary point , Based on industry experience and training data from typical scenarios, it is advisable to... , Based on the training dataset D, extract from each sample and Substitute To obtain all samples Value set;

[0047] Statistical inflection point identification: drawing Use the frequency histogram and cumulative density function (CDF) to find the inflection point where the sample proportion drops sharply. The point where the CDF slope decreases from ≥0.8 to ≤0.2 is the boundary between PLL dominance and equilibrium. The point where the CDF slope increases from ≤0.2 to ≥0.8 is the equilibrium point and the boundary between VSM dominance;

[0048] Verify the out-of-bounds rate of risk barrier indicators (PCI, Δζ) for each interval to ensure... Conforms to the characteristics of PLL-dominated weak network sensitivity. balanced, It conforms to the strong support characteristics of VSM and is fine-tuned to match. Calculated under typical scenarios... If the dataset is changed, it can be relabeled following the steps above;

[0049] It should be noted that this scheme utilizes a large amount of fault and operational scenario simulation data to calculate the Coupling Dynamic Index (CDI) value; the training data covers the following dimensions:

[0050] The short-circuit ratio (SCR) and the degree of grid weakness are determined by setting discrete values ​​from 1.5 to 10 in the simulation, covering weak, normal, and strong grids. It is used to characterize the grid strength at the grid connection point and is defined as follows: ;in, This refers to the short-circuit capacity of the power grid at the grid connection point. The equivalent rated capacity of the new energy base at the grid connection point; the short-circuit capacity of the power grid at the grid connection point. It can be obtained from the equivalent short-circuit parameters of the power grid, or from the rated line voltage at the grid connection point. With short-circuit current Calculated, for example Or, based on the Thevenin equivalent impedance of the power grid at the grid connection point. The following example is obtained through conversion. The equivalent rated capacity The sum of the rated capacities of the new energy power generation units participating in grid connection at the grid connection point can be taken, or the equivalent rated capacity obtained according to the unified conversion method.

[0051] The ratio of line resistance to reactance Selected based on actual measurement statistics of the areas where synchronous condensers are connected. The simulation considers the differences between resistive and inductive lines within the range of 0.1 to 2; fault types and durations include typical events such as single-phase grounding, three-phase short circuit, and line disconnection, with fault durations ranging from 0.05 s to 0.2 s; different line segments are selected for fault locations; the ratio of renewable energy output to synchronous condenser capacity is simulated by changing the ratio of wind power and photovoltaic power (e.g., 0%–80%) and the synchronous condenser capacity (e.g., low, medium, high); controller parameters include inverter droop coefficients selected from recommended ranges, and PLL bandwidth selected from typical values ​​of 20–100 Hz based on the technical specifications of major equipment manufacturers; VSM virtual inertia coefficients are selected based on installed capacity of 0.1–0.3 s; the set of simulation cases for all the above dimensions is denoted as training dataset D, which is used for subsequent candidate boundary line selection, proportional coefficient calibration, and parameter optimization;

[0052] For each simulation case, extract and Calculate the dominance factor ;

[0053] The Power Coupling Index (PCI) measures the degree of coupling between the active and reactive power control of an inverter. A higher value indicates stronger coupling and poorer stability. The PCI is constructed using the relative gain matrix method, and its definition can be expressed as: ;in, To control inputs such as voltage commands and power references, The inverter output power; i represents the dimension of the inverter output power, such as the i-th active power. or reactive power ;j indicates the dimension of the control input, such as the j-th voltage command, power reference, etc. In simulation, partial derivatives can be calculated using a small-signal model or by applying perturbations; when the power coupling index (PCI) value is large, active power regulation and reactive power regulation have a strong mutual influence, which can easily lead to low-frequency oscillations.

[0054] The damping ratio ζ is a dimensionless index for evaluating the degree of oscillation decay in a system. ζ=1 indicates critical damping, and ζ<1 indicates underdamping. The change in damping ratio is defined to account for the difference in system damping ratio before and after a fault. ;

[0055] Power system stabilizers (PSS) are key devices for suppressing low-frequency oscillations, and their standard operating frequency band is [missing information]. Industry standard GB / T14285-2022 stipulates This frequency band is the dedicated control range for the Power System Stabilizer (PSS). The inverter voltage regulation band must avoid this range to prevent control conflicts. Therefore, it is defined as follows: For Power System Stabilizer (PSS) no-entry zone;

[0056] Comprehensive dominance factor Interval, power coupling index Damping ratio change Construct risk barriers based on dominance factors Interval differentiation sets red and yellow line conditions, defining a risk barrier set. The corresponding red line condition is the advanced threshold condition:

[0057] when hour, or ;

[0058] when hour, or ;

[0059] when hour, or ;

[0060] The corresponding yellow line condition is the intermediate threshold condition:

[0061] when hour, or ;

[0062] when hour, or ;

[0063] when hour, or ;

[0064] If neither of the above two conditions is triggered, it is recorded as not triggered;

[0065] Furthermore, based on the red and yellow line thresholds already set in the risk barrier set C, the discrete risk color label R is defined as follows: If both are satisfied... or If the discrete risk color label is red, then denote it as red; if it does not satisfy red, but satisfies red, then it is red. or If the condition is not triggered, then the discrete risk color label R is recorded as yellow; if neither of the above two conditions is triggered, then the discrete risk color label R is recorded as not triggered, which can be simply referred to as green for ease of expression.

[0066] in, Different dominance factors Advanced and intermediate thresholds for the phase competition index within the interval. Different dominance factors The high-level threshold and medium-level threshold of the damping deficit in the interval; and x=1,2,3 correspond to the dominant, equalizing, and virtual synchronous machine (VSM) inverter intervals, respectively;

[0067] Based on different dominance factors Test data for an interval are generally taken as follows: , , , ; , , , ; , , , The guardrail set will determine the subsequent grading and parameter adjustment strategies; the selection of the threshold is based on the statistical distribution of the samples and is determined by the training data at a reliability level of over 90%.

[0068] Step S2: Based on the numerical range of the dominance factor, divide multiple continuous dominance factor intervals to represent three system characteristic modes: dominance by phase-locked loop inverters, balanced contribution of two types of inverters, and dominance by virtual synchronous machine inverters. For each dominance factor interval, define a risk guardrail set including power coupling index and damping ratio change. Set differentiated risk threshold conditions for each dominance factor interval, including a red line threshold for emergency warning and a yellow line threshold for early warning. Extract the inverter control parameter range from the training dataset, determine the parameter range of the low-frequency side bandwidth control coefficient and the high-frequency side bandwidth control coefficient, and select multiple discrete points within the parameter range for pairwise combination to generate a candidate boundary line set.

[0069] In grid-connected inverter control, κ1 and κ2 represent the bandwidth control coefficients on the low-frequency and high-frequency sides, respectively; for example, in phase-locked loop (PLL) inverter control, the proportional gain of the low-frequency side control... The frequency threshold that determines the phase angle element's proportional gain and the high-frequency side bandwidth. Dynamic control of filtering or integration stages; in the control of virtual synchronous machine (VSM) type inverters, both factors jointly affect the speed and stability of power response; selecting appropriate κ1 and κ2 can balance tracking accuracy and anti-interference capability, and must adapt to the characteristics of the dominance factor α interval divided in step S1, that is, the dominance interval of phase-locked loop (PLL) type inverters needs to strengthen phase angle tracking dynamics, the dominance interval of virtual synchronous machine (VSM) type inverters needs to optimize power support response, and the balance interval needs to balance the characteristics of both; this scheme does not solve for the optimal parameters for specific operating conditions, but extracts the dividing coefficients κ1 and κ2 as target boundaries based on the training data in step S1, providing a unified reference for the subsequent selection of three gear levels; the left side of the dividing line corresponds to low-frequency control, i.e., adapting to the PLL-dominant scenario, and the right side corresponds to high-frequency control, i.e., adapting to the VSM-dominant scenario. The intermediate transition area will be given the gear level meaning of adapting to the balance interval in the next step, specifically:

[0070] Based on the inverter control parameter range extracted from the training dataset D in step S1, the proportional coefficient of the low-frequency side control is set. Frequency threshold of high-frequency side bandwidth ;in 2, , , The value is determined by combining typical inverter controller manuals with training data statistics; within the above interval, multiple discrete points, such as 10–20, are selected and combined in pairs to generate a set of candidate boundary lines. This ensures coverage of control requirements corresponding to different dominance factor α intervals; where p is the index identifier of the candidate boundary line, representing the p-th candidate boundary line combination;

[0071] For each pair of candidate boundary lines Randomly sample intervals covering the full dominance factor α, short-circuit ratio, and other parameters from the training dataset D. The simulation samples included fault type operating condition samples. The original grid parameters were kept unchanged, only the inverter bandwidth parameters were replaced, and transient simulations were run. The simulation outputs power angle stability, frequency stability, and power coupling index. Damping ratio change For indicators such as the guardrail threshold determined in step S1, boundary crossing is directly used for judgment, and a binary feasibility identifier is recorded. The rule for determining the boundary is that if all indicators do not exceed the intermediate threshold... Then feasibility indicator The corresponding candidate boundary line is defined as deployable; if any metric exceeds the advanced threshold... Then feasibility indicator The corresponding candidate boundary line is marked as non-deployable; if the case is between the intermediate threshold and the high threshold, it is considered deployable but has a lower priority, which is reflected by the safety factor in the priority value calculation.

[0072] For candidate boundary line Its deployable ratio is defined as: ;in, Candidate dividing line The corresponding number of simulation samples, u represents the number of simulation samples. The u-th simulation sample corresponding to each candidate boundary line, the indicator function The ratio is 1 when the deployable condition is met; this ratio needs to be calculated separately for its compliance rate in the three dominant factor α intervals. The higher the overall ratio and the more balanced the distribution in each interval, the stronger the adaptability of the boundary line and the higher the priority.

[0073] To ensure that the boundary line matches the time scale of the power grid and the synchronous condenser, the typical transient constants of the synchronous condenser implicit in the training data are used. As a benchmark; this value is based on the equivalent inertia constant of the camera in step S1. Its typical industry value is 0.5-2.0s and the time constant of the excitation system. The typical value is obtained by weighted average of 0.05-0.2s, or by directly referring to the typical equipment parameters in GB / T7064-2017 "Technical Requirements for Salient Pole Synchronous Generators";

[0074] The effective time constant of a certain candidate inverter below the dividing line is approximately: ;in The rated angular frequency of the power grid. and Let these represent the low-frequency bandwidth control coefficient and the high-frequency bandwidth control coefficient of the p-th candidate boundary line, respectively. The first term... The rise time of the filtering stage, the second term For phase angle or power response time; calculate the time-base ratio. The larger the ratio, the faster the inverter response. It also needs to meet the response requirements of different dominance factor α ranges. That is, the dominance range of Virtual Synchronous Machine (VSM) type inverters requires a larger ratio, while the dominance range of Phase Locked Loop (PLL) type inverters can be appropriately reduced. In actual calculations, this ratio is normalized and the upper and lower limits are set to 10 and 0.1, respectively, to avoid the influence of extreme values.

[0075] To quantify the safety margin of all deployable candidate boundaries within the intervals of each dominance factor α, a high-level threshold based on the risk guardrail set is used. Calculate the safety factor ;in, The outermost layer takes the minimum value, which means traversing all simulation scenarios and taking the minimum safety margin for all scenarios. Under the same simulation scenario, the minimum safety margin of the two guardrail indicators is taken. First, within a single simulation scenario, the minimum margin of two guardrail indicators is determined to ensure safety in that scenario. Then, across all simulation scenarios, the minimum value of these indicators is taken as the conservative safety margin, denoted as the safety factor. ; , The advanced threshold is defined for each dominant factor α interval, and the numerator is the difference between the advanced threshold and the actual index. The safety factor ranges from 0 to 1. The larger the value, the higher the safety margin. It is necessary to ensure that the minimum safety requirements are met in all three dominant factor α intervals to avoid potential risks in a single interval.

[0076] To comprehensively evaluate the merits of candidate boundary lines, a priority value is constructed using a multiplicative approach based on the three core requirements of deployment adaptability, response matching, and security margin. ;in , , It is a positive proportionality coefficient, satisfying This is used to adjust the relative importance of the three factors; considering the interval characteristics of the dominance factor α, initial values ​​are recommended. That is, focusing on the adaptability of deployment across the entire range, That is, focusing on response time matching, This approach emphasizes safety margin. Its logic involves selecting typical samples from D, fine-tuning single coefficients to observe the impact of the priority value YQp on the selection of the boundary line, and retaining the coefficient range that ensures the optimal boundary line's out-of-bounds rate is ≤ γ1. Parameter verification involves substituting values ​​within the interval into the formula to verify that DRp ≥ 85% and Styp ≥ 0.7 for each α interval, ultimately setting b1 = 0.4, b2 = 0.4, and b3 = 0.2. This can be fine-tuned according to actual application scenarios. Priority values... The larger the value, the better the overall performance of the boundary line;

[0077] Calculate the priority value of all deployable candidate boundaries. Take the candidate boundary line corresponding to the maximum value. As the target dividing line If multiple priority values ​​exist If the difference is less than a preset approximate threshold, the deployable candidate boundary line with the most balanced deployment ratio in each dominant factor α interval is selected as the target boundary line, while the suboptimal solution is reserved as a backup boundary line in case of abnormal scenario switching; wherein, the preset approximate threshold can be 5%;

[0078] The training dataset D is stratified into K folds according to the dominance factor α interval, and the target boundary line is calculated for each fold using the above procedure. Furthermore, the deployable proportion and the rate of index out-of-bounds were verified in other contexts; it was required that the rate of out-of-bounds for each dominant factor α interval be lower than the rate of out-of-bounds control threshold. And different compromise targets dividing line The parameter fluctuation does not exceed the parameter fluctuation control threshold. To ensure its generalization ability is adapted to all scenarios; if the out-of-bounds rate of a certain dominant factor α exceeds the standard, the parameter scanning range or proportional coefficients b1, b2, b3 of the candidate boundary line need to be readjusted.

[0079] Preferably, the effective time constant already used in the feasibility assessment and priority value calculation is used. The target dividing line for selection Corresponding effective time constant Length of stay: ;

[0080] It should be noted that the aforementioned out-of-bounds rate control threshold Based on the statistical distribution of index out-of-bounds behavior determined using training data with a reliability level of over 90%, it is necessary to ensure that the risk exposure probability of the target boundary line in each α interval is within an acceptable engineering range. Initial values ​​can refer to industry risk control standards, such as 5%; parameter fluctuation control thresholds. The statistical determination of parameter stability based on cross-fold verification of training data requires ensuring that the differences in target boundary parameters trained from different data subsets are within the tolerance range of the system's control accuracy and robustness requirements. The initial value can refer to the parameter engineering deviation threshold, such as 10%.

[0081] In step S3: For each candidate boundary line in the candidate boundary line set, samples covering all operating conditions are randomly selected from the training dataset for transient simulation to obtain performance indicators including power coupling index and damping ratio changes; based on the performance indicators and the risk threshold condition, boundary crossing judgment is performed, and the deployable proportion of the candidate boundary line in all simulation samples is calculated; based on the typical transient constant of the synchronous condenser and the inverter effective time constant calculated according to the candidate boundary line parameters, the time base ratio is calculated to evaluate the control response matching degree; based on the risk threshold condition and the performance indicators, the safety factor is calculated to quantify the safety margin under the worst operating condition; based on the obtained deployable proportion DR_p, time base ratio, and safety factor, the comprehensive priority value of each candidate boundary line is calculated in a multiplicative form combined with a positive proportionality coefficient; the candidate boundary line with the highest comprehensive priority value is selected as the final target boundary line for synchronous instability analysis;

[0082] Based on the discrete risk color label R, a level mapping is performed. When the discrete risk color label R is red, it corresponds to a low bandwidth level. ;

[0083] When the discrete risk color label R is yellow, it corresponds to the medium bandwidth level. ;

[0084] When the discrete risk color label R is not triggered, it corresponds to the high bandwidth level. ;

[0085] Furthermore, regarding gear shifting, it only applies if the discrete risk color label R remains continuously for a duration not less than the output of step S2. The gear shift only takes effect when the dwell time is met; otherwise, the original gear is maintained; shifting must strictly follow the specified rules. Adjacent-level rules;

[0086] Furthermore, based on the target boundary line Corresponding low-frequency side bandwidth control coefficient and high-frequency side bandwidth control coefficient In conjunction with the dominance factor α, a scaling formula is used to determine the target boundary line. Discrete scaling: ; ;in, , The fixed ratio coefficients for the gear position to the dominance factor α range are determined offline using the training dataset D from step S2. This involves iterating through different combinations of ratio coefficients and selecting combinations with a deployable ratio DR ≥ 90% and a safety factor Sty ≥ 0.8. An example of the initial values ​​is shown below:

[0087] When the dominance factor α is in the PLL dominance range, gear correspond Initial value example ;

[0088] When the dominance factor α is in the equilibrium range, the gear position correspond Initial value example ;

[0089] When the dominance factor α is in the VSM dominance range, gear correspond Initial value example ;

[0090] PSS no-entry zone based on step S1 Set according to the fixed offset rule of gear position:

[0091] When in When filing, Pick Upward bias Example of its initial value , Example of its initial value ;

[0092] When in When filing, Pick Upward bias Example of its initial value , Example of its initial value ;

[0093] When in When filing, Pick Upward bias Example of its initial value , Example of its initial value ;

[0094] This setting ensures that the higher the risk, the farther and narrower the voltage regulation window is from the PSS band. No new parameters are added; only the PSS stopband is reused. With gears; among which, for Compared to the PSS no-access zone limit The upward bias is used to avoid the PSS operating frequency band. It is calibrated offline by the training dataset D in step S2. The system stability under different bias values ​​is verified by simulation. The value with no oscillation risk is selected, and the initial value range is 0.2-0.6Hz. Virtual voltage bandwidth The calibration value is determined based on the system damping requirements and the inverter's anti-interference capability. The safety factor verification in step S2 ensures that the bandwidth matches the damping margin, with an initial value range of 0.6-1.0Hz.

[0095] Generated by the above scaling formula , and , constitute Then, if its corresponding PLL allows the inclusion of... If an overlap occurs, it means that the feasibility constraint of step S2 is not met. At this time, maintain the original gear position until the input of steps S1 and S2 changes. Output is only available after the gear change is completed and the device has been in a lingering state; the output includes side and boundary frequencies, which are used in step four for threshold recalibration and online grayscale control.

[0096] In step S4: Based on the control parameters corresponding to the target boundary line, combined with the dominance factor α interval assignment and risk level obtained from real-time analysis, the parameters are mapped to three preset bandwidth control levels: low, medium, and high. The control levels and their corresponding parameter sets are output to the control system of the synchronous condenser and inverter to achieve adaptive parameter adjustment in order to suppress the risk of synchronous instability.

[0097] This step is the final stage of the entire chain analysis, based on the three bandwidth levels output in step S3. and gear parameter group Combined with the dominance factor in step S1 Sections, risk barrier sets, and PSS no-entry zones Meanwhile, the target boundary line determined in step S2 is reused to realize direct mapping from gear to control strategy, safe release and closed-loop feedback;

[0098] Based on the principle of positive correlation between risk level and control conservatism, the mapping between the gear position and the synchronous condenser excitation, inverter bandwidth, virtual voltage frequency band and monitoring threshold is realized: the synchronous condenser excitation gain decreases as the gear risk increases, and the adjustment range is determined based on the interval characteristics of the fixed proportional coefficient in step S3.

[0099] Inverter bandwidth parameters Calculate according to the scaling rules in step S3. The value of varies The range gradually increases from PLL-dominated to VSM-dominated;

[0100] Virtual voltage band : PSS no-entry band upper limit based on step S1 Upward bias, The bias decreases as the risk level increases, and the bias and bandwidth values ​​refer to the frequency band setting logic in step S3.

[0101] Core monitoring threshold, power angle difference , The risk level increases with each gear, and the adjustment ratio is based on the higher-level risk barrier threshold in step S1. and the determination of industry benchmark values;

[0102] The strategy triggering and execution logic is as follows:

[0103] Real-time acquisition of PMU / SCADA measurement data such as synchronous condenser power angle, grid frequency, power coupling index, damping ratio change, and the current gear position BL and parameter group output in step S3. No new redundant data collection dimensions will be added.

[0104] The real-time measured values ​​are compared with the core monitoring thresholds mapped above. If the synchronous condenser power angle exceeds the limit, the synchronous condenser PSS gain adjustment is triggered. If the change in power coupling index or damping ratio exceeds the limit, the inverter bandwidth parameter adaptation is triggered. of The execution and comparison logic are consistent with the risk barrier determination rules in step S1.

[0105] Strategy execution: All control actions are preset parameter adjustment commands, such as reducing the excitation gain of the synchronous condenser by 15% and the inverter... according to The scaling process remains consistent with the parameter group logic in step S3 and does not involve weighted summation or fuzzy decision-making.

[0106] To avoid system oscillations caused by a one-time parameter adjustment, a simplified tiered release mechanism is adopted:

[0107] The control parameters and monitoring thresholds corresponding to each gear are gradually approximated in increments of 5% of the difference between the target value and the current value. For example, starting from the current value... To the target The adjustment is performed in 20 steps, with a 1-minute interval between each step. The step division logic refers to the discrete point selection rule for the candidate boundary line in step S2.

[0108] After each tier is executed, only the risk barrier indicators defined in step S1 are monitored. and If the indicator exceeds the limit, immediately roll back to the previous level of parameters and record the abnormal condition; when all levels have been executed and the guardrail indicator does not exceed the limit for 5 consecutive minutes, it is determined to be fully online; if there are 3 consecutive rollbacks, maintain the previous stable level state until the gear input in step S3 or An update has occurred.

[0109] This step outputs the following core data, which is used for offline optimization of previous steps, forming a closed-loop chain:

[0110] Gear shift log: includes gear shift time, BL value before and after shift, and parameter In comparison, the parameter format is consistent with the output of step S3;

[0111] Strategy execution log: Records threshold exceeding trigger conditions, executed control actions, and subsequent metric changes. The log dimensions cover step S1. Range and risk status indicators;

[0112] Guardrail indicator trend: Statistics at 10-minute intervals , The mean and fluctuation range are used to generate a stability assessment report. The statistical method refers to the calculation logic of the deployable proportion in step S2.

[0113] Please see Figure 2 As shown, this invention discloses a synchronous instability analysis system for synchronous condensers in new energy bases, comprising the following modules:

[0114] The impact assessment module is used to acquire the training dataset and calculate the dominance factor and divide the interval; the baseline deformation generation module is used to construct the risk guardrail set and set the threshold conditions; the residual deformation learning module is used to generate the candidate boundary line set, perform transient simulation and calculate the deployable ratio, time base ratio and safety factor; the fusion and closed-loop correction module is used to calculate the priority value, select the target boundary line and output the synchronous instability analysis results.

[0115] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0116] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, in the form of a computer program product.

[0117] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and inventive constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0118] In addition, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0119] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0120] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for analyzing the synchronous instability of synchronous condensers in a new energy base, characterized in that, Includes the following steps; The training dataset of the new energy base is obtained, and the coupling dynamic index of the inverter in the training dataset is used to calculate the dominance factor. The training dataset covers various grid parameters, fault types and inverter control parameters. The inverters include grid-connected inverters and grid-connected inverters. Based on the dominance factor, multiple dominance factor intervals are divided, and a risk guardrail set including the power coupling index and the damping ratio change is defined. Risk threshold conditions are set for each dominance factor interval. Extract the inverter control parameter range from the training dataset, determine the parameter range of the low-frequency side bandwidth control coefficient and the high-frequency side bandwidth control coefficient, and select multiple discrete points within the parameter range to generate a candidate boundary line set; For each candidate boundary line, transient simulations are performed using the training dataset to obtain performance metrics including power coupling index and damping ratio change. The deployable ratio is calculated based on performance indicators and risk threshold conditions; the time base ratio is calculated based on the typical transient constant of the synchronous condenser and the effective time constant of the inverter; and the safety factor is calculated based on risk threshold conditions and performance indicators. Based on the obtained deployable ratio, time base ratio, and safety factor, the priority value of each candidate boundary line is calculated; the candidate boundary line with the highest priority value is selected as the target boundary line for synchronous instability analysis of the camera.

2. The method for analyzing the synchronous instability of synchronous condensers in a new energy base according to claim 1, characterized in that, The formula for calculating the dominance factor is: ;in, As the dominant factor, To match the phase angle disturbance amplitude response of the phase-locked loop (PLL) in the grid-connected inverter, The phase angle disturbance amplitude response of the virtual synchronous machine (VSM) in a grid-connected inverter; and Obtained through system linearization model analysis or time-domain simulation.

3. The method for analyzing the synchronous instability of synchronous condensers in a new energy base according to claim 2, characterized in that, Dividing the data into multiple intervals based on the dominance factor includes: defining the theoretical range of values ​​for the dominance factor α. Divided into three consecutive intervals, with the interval boundaries including: and ,satisfy ;when When, it is defined as the dominant region of a phase-locked loop (PLL) inverter; when When, it is defined as the equalization contribution range between the phase-locked loop (PLL) inverter and the virtual synchronous machine (VSM) inverter; when When, it is defined as the dominant region of a Virtual Synchronous Machine (VSM) type inverter; where, and Based on the statistical distribution of the dominance factor α values ​​in the training dataset, the inflection point of the slope change of the cumulative density function CDF is determined.

4. The method for analyzing the synchronous instability of synchronous condensers in a new energy base according to claim 3, characterized in that, The risk guardrail set includes the power coupling index and damping ratio variation, and sets risk threshold conditions for each dominance factor interval as follows: Differentiated red line and yellow line conditions are set for each dominance factor interval; the red line condition is a high-level threshold condition, and the yellow line condition is an intermediate-level threshold condition; for the dominance interval of phase-locked loop (PLL) inverters, the equalization contribution interval of PLL inverters and virtual synchronous machine (VSM) inverters, and the dominance interval of VSM inverters, corresponding high-level thresholds are set respectively. With intermediate threshold , where x=1,2,3 correspond to the three intervals: the dominant interval of the phase-locked loop PLL inverter, the balanced contribution interval of the phase-locked loop PLL inverter and the virtual synchronous machine (VSM) inverter, and the dominant interval of the virtual synchronous machine (VSM) inverter, respectively. The power coupling index is calculated by taking the ratio of the partial derivatives of different control input dimensions with respect to the active and reactive power output dimensions of the inverter, and selecting the maximum value. The damping ratio is obtained by subtracting the initial damping ratio of the oscillation mode before the fault from the subsequent damping ratio of the oscillation mode after the fault is cleared.

5. The method for analyzing the synchronous instability of synchronous condensers in a new energy base according to claim 1, characterized in that, The candidate boundary set is generated by determining the low-frequency side bandwidth control coefficient. The parameter range is Used to control the proportional characteristics of the phase angle element in grid-connected inverters and the proportional characteristics of the power response in grid-connected inverters; to determine the high-frequency side bandwidth control coefficient. The parameter range is This parameter is used to control the frequency threshold of the inverter's filtering or integrating stage; the parameter range is based on the initial value range determined by typical inverter controller technical specifications; and it is also used for the low-frequency bandwidth control coefficient. and high-frequency side bandwidth control coefficient Multiple discrete value points are selected within the parameter range; the low-frequency side bandwidth control coefficient is... and high-frequency side bandwidth control coefficient The discrete points are combined in pairs to form multiple candidate boundary lines. This constitutes a set of candidate boundary lines to ensure coverage of control requirements corresponding to different dominance factor α intervals; where p is the index identifier of the candidate boundary line, representing the p-th candidate boundary line combination.

6. The method for analyzing the synchronous instability of synchronous condensers in a new energy base according to claim 1, characterized in that, Deployable ratio The calculation formula is: ,in For indicator functions, Candidate dividing line The corresponding number of simulation samples, This serves as a feasibility indicator for the p-th candidate boundary line in the u-th sample; the time baseline ratio is... ,in To adjust the typical transient constant of the camera, The effective time constant of the inverter is calculated using the following formula: , The rated angular frequency of the power grid; The formula for calculating the safety factor is: ,in This means iterating through all simulation scenarios and taking the minimum value.

7. The method for analyzing the synchronous instability of synchronous condensers in a new energy base according to claim 6, characterized in that, Transient simulation using the training dataset includes: randomly sampling operating condition samples from the training dataset, the operating condition samples covering the entire dominance factor α range, short-circuit ratio, and the ratio of line resistance to reactance. The fault type is determined while keeping the original grid parameters unchanged. The short-circuit ratio is the ratio of the grid short-circuit capacity at the grid connection point to the equivalent rated capacity of the new energy base, used to characterize the grid strength at the grid connection point. Calculations are performed based on the aforementioned performance indicators and risk threshold conditions, including boundary judgment according to the following rules: If all the aforementioned performance indicators do not exceed the yellow line threshold in the risk barrier set, then a feasibility indicator is displayed. The candidate boundary line is determined to be deployable; If any of the performance indicators exceeds the red line threshold in the risk barrier set, then a feasibility indicator is displayed. The candidate boundary line is determined to be undeployable; If the performance index is between the yellow line threshold and the red line threshold, the candidate boundary line is determined to be deployable but with low priority, and its conservative margin is reflected by the safety factor in the priority value calculation.

8. The method for analyzing the synchronous instability of synchronous condensers in a new energy base according to claim 1, characterized in that, Calculate the priority value for each candidate boundary line; select the candidate boundary line with the highest priority value as the target boundary line, specifically: priority value The calculation formula is: ,in , , It is a positive proportionality coefficient, and Calculate the priority value of all candidate boundary lines. Choose to prioritize The largest candidate boundary line is taken as the target boundary line B*. If there are multiple candidate boundary values If the difference is less than the preset approximate threshold, the one with the most balanced deployment ratio in each dominant factor α interval is selected as the target boundary line, and the suboptimal solution is reserved as a backup boundary line.

9. The method for analyzing the synchronous instability of synchronous condensers in a new energy base according to claim 1, characterized in that, Based on the control parameters corresponding to the target boundary line, combined with the dominance factor α interval obtained from real-time analysis and the current risk level determined based on the risk barrier set, the parameters are mapped to multiple preset adaptive control levels. These levels include at least three grades: low, medium, and high. The mapped control levels and their corresponding parameter sets are output to the control systems of the synchronous condenser and inverter to guide adaptive parameter adjustments, thereby suppressing the risk of synchronization instability. The switching of control levels must meet the dwell time condition determined based on the target boundary line, and the parameter sets are generated by scaling the target boundary line parameters proportionally to the current level and the dominance factor interval, while ensuring that the inverter's voltage regulation frequency band avoids the dedicated control range of the power system stabilizer. The scaling is performed using a scaling formula for the target boundary line. Discrete scaling: ; ;in, , The fixed ratio coefficient for the range from gear position to the dominant factor α; This represents the bandwidth control parameters on the low-frequency and high-frequency sides that are actually output to the control system after scaling. , BL represents the initial values ​​of the bandwidth control coefficients on the low-frequency and high-frequency sides corresponding to the target boundary line B*; BL represents the adaptive control gear obtained by mapping.

10. A synchronous instability analysis system for a new energy base synchronous condenser, used to implement the synchronous instability analysis method for a new energy base synchronous condenser as described in any one of claims 1-9, characterized in that, Includes the following modules: The influence assessment module is used to obtain the training dataset and calculate the dominance factor and divide the intervals; The baseline deformation generation module is used to construct a risk barrier set and set threshold conditions; The residual deformation learning module is used to generate a set of candidate boundary lines, perform transient simulations, and calculate the deployable scale, time base ratio, and safety factor; the fusion and closed-loop correction module is used to calculate priority values, select target boundary lines, and output synchronous instability analysis results.

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