An equivalent inertia evaluation method and system considering anti-damping-frequency modulation interference

Abstract

The application discloses an equivalent inertia evaluation method and system considering anti-damping-frequency modulation interference, and the method comprises the following steps: collecting frequency data and device port active power data of each node before and after system disturbance, determining the disturbance time based on frequency information entropy in a sliding window; carrying out interpolation, filtering and per-unit pre-processing on subsequent data; obtaining the frequency change rate and active power response quantity through adaptive fitting, calculating the damping-frequency modulation capability characteristic factor, and then separating the pure inertia component from the device power response; combining the device power-frequency response model and sliding window variance optimization to identify the inertia time constant of power electronic devices and synchronous machines; finally, aggregating the power supply node inertia, and distributing the non-power supply node equivalent inertia according to the frequency change rate difference between nodes. The application effectively overcomes the interference of device damping and frequency modulation on inertia evaluation, and is suitable for new power systems with increasingly intensified power electronics.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of power system analysis and control technology, in particular to an equivalent inertia evaluation method and system considering anti-damping-frequency modulation interference. BACKGROUND

[0002] Inertia is a key physical quantity to measure the ability of power system to resist frequency changes, usually represented by inertia time constant. In the traditional power system dominated by synchronous machines, when power disturbance occurs, the kinetic energy stored in the rotor of synchronous machines will be released spontaneously, providing inertia support to buffer the rapid change of frequency and gain time for frequency modulation action. However, with the increasing proportion of power electronic converters connected to the grid by wind power, photovoltaic and other power generation equipment, the overall inertia level of the system presents a downward trend. This is because such devices do not have rotating masses or their rotating parts are decoupled from the grid through converters, and cannot provide inertia like synchronous machines. Although some new energy devices simulate inertia response characteristics through control algorithms, their support capacity is limited and the characteristics are different from traditional synchronous machines.

[0003] The decrease of system inertia significantly increases the risk of frequency instability after large power disturbance. Therefore, accurately evaluating the actual inertia provided by various types of devices in the system and the equivalent inertia of each network node is of great significance for mastering the frequency safety situation of the system, optimizing the dispatching and control strategy.

[0004] The existing inertia evaluation methods mainly have the following shortcomings: at the device level, the highly simplified power-frequency first-order model is generally used, ignoring the inherent damping effect and the rapid response of active frequency modulation function. This leads to the error of counting the power response that should belong to damping or primary frequency modulation into inertia response when identifying the inertia time constant, resulting in the identification result being too high and misleading the safety evaluation. For synchronous machines, the detailed structure of the prime mover and the governor is not considered, which makes the model deviate greatly from the actual dynamics. At the node level, the existing methods either rely on simplified models without considering the interference of device dynamics or need the theoretical value of system inertia, which is difficult to obtain, and the practicality is not strong. Therefore, there is an urgent need for a method and system that can effectively strip the interference of damping and frequency modulation, so as to achieve high-precision and high-confidence evaluation of the equivalent inertia of devices and nodes. SUMMARY

[0005] The present application proposes an equivalent inertia evaluation method and system considering anti-damping-frequency modulation interference, which can effectively strip the interference of damping and frequency modulation, accurately separate the pure inertia response component of the device from the measurement data, significantly improve the accuracy of inertia evaluation, and is suitable for new type of power system containing high proportion of power electronic devices.

[0006] Firstly, a method for evaluating equivalent inertia considering damped-frequency interference includes:

[0007] S1. Real-time acquisition of frequency measurement signals from each node of the power system; calculation of frequency information entropy based on the distribution characteristics of the frequency measurement signals within a sliding time window; determination of the moment when the system power disturbance occurs based on the abrupt change in the frequency information entropy.

[0008] S2. Starting from the time when the disturbance occurs, preprocess the subsequent frequency signal and the subsequent port active power signal to obtain the preprocessed time series data.

[0009] S3. Based on the preprocessed time-series data, the instantaneous rate of change of node frequency and the active power response of each power generation device are obtained respectively; by calculating the adjustment parameters used to characterize and compensate for the damping and frequency regulation dynamics of the power generation device, and based on the adjustment parameters, the rate of change of frequency and the active power response, the power-frequency dynamic relationship model of the power generation device is used to solve the problem and obtain the corresponding initial value sequence of inertial time constant; the initial value sequence of inertial time constant is subjected to sliding window filtering with the minimum statistical variance as the optimization objective to determine the inertial time constant of each power generation device;

[0010] S4. Based on the inertial time constant of each power generation device, the inertial time constants of each power generation device connected to the same power node are aggregated to obtain the equivalent inertia of each power node; according to the relative relationship of the frequency change rate between non-power nodes and associated power nodes in the region, and in combination with the equivalent inertia of the associated power nodes, the equivalent inertia of the non-power nodes is calculated.

[0011] Preferably, step S1 specifically includes:

[0012] S11. The obtained node frequency data is segmented by a sliding time window with a length of n and a step size of 1, and the frequency sample distribution probability after removing the base value component in each window is calculated.

[0013] S12. Calculate the frequency information entropy for each sliding time window based on the frequency sample distribution probability.

[0014] S13. Set the frequency information entropy threshold to ε. When the frequency information entropy of two adjacent sliding time windows satisfies the condition that the entropy value of the previous window is less than ε and the entropy value of the current window is greater than or equal to ε, the end time of the current window is determined as the time when the system disturbance occurs.

[0015] Preferably, in step S2, the preprocessing includes: interpolating the missing data using Newton interpolation and filtering out high-frequency noise from the node frequency data using a low-pass Butterworth filter, wherein the cutoff frequency of the low-pass Butterworth filter is set to 0.667Hz.

[0016] Preferably, step S3 specifically includes:

[0017] S31. Adaptive variable-order polynomial fitting is used to fit the node frequency curve and the active power curve at the device port respectively, so as to obtain the frequency change rate and the instantaneous change of the active power at the device port.

[0018] S32. For synchronous generators, select the lowest frequency point after disturbance as a special operating point, and calculate the reheat time constant and the first damping-frequency regulation capability characterization factor.

[0019] S33. For power electronic equipment, select two short-time operating points after the disturbance and before the first frequency regulation action of the power electronic equipment, and calculate the damping-frequency regulation capability characterization factor of the power electronic equipment according to the power-frequency response equation and the difference calculation method.

[0020] S34. For synchronous generators, select two operating points after disturbance and with non-zero frequency change rate, and calculate the second characterization factor of damping-frequency regulation capability based on the power-frequency response equation of the synchronous machine.

[0021] S35. Substitute the characterization factors and parameters obtained in steps S32, S33, and S34 into the corresponding device power-frequency response model, and calculate the inertial time constant within the set identification time window.

[0022] S36. Calculate the variance of all inertial time constant samples within the identification time window, slide the identification time window and repeat the variance calculation, and determine the average value of the inertial time constant within the identification time window corresponding to the minimum sample variance as the final identification result of the equipment inertial time constant.

[0023] Preferably, in step S31, the method for determining the order of the adaptive variable-order polynomial fitting is as follows: set a fitting deviation tolerance, start fitting from the initial order, and if the deviation between the fitting results after increasing the order is greater than the fitting deviation tolerance, then continue to increase the order until the deviation between the fitting results obtained by increasing the order is less than or equal to the fitting deviation tolerance.

[0024] Preferably, step S4 specifically includes:

[0025] S41. Power node inertia aggregation: The device inertia time constant obtained in step S3 is weighted and aggregated to obtain the inertia of each power node.

[0026] S42. Non-power node inertia allocation: For any non-power node, obtain the equivalent inertia of the nearest power node in the electrical area where the non-power node is located and the frequency change rate of the two. Based on the difference in the frequency change rate of the two, calculate the equivalent inertia of the non-power node.

[0027] Secondly, the present invention provides an equivalent inertia evaluation system considering damped-frequency interference, comprising:

[0028] Data acquisition and disturbance detection module: used to collect frequency measurement signals from each node of the power system in real time; calculate frequency information entropy based on the distribution characteristics of the frequency measurement signals within a sliding time window; and determine the time when the system power disturbance occurs based on the abrupt change in the frequency information entropy.

[0029] Data preprocessing module: used to preprocess the subsequent frequency signal and the subsequent port active power signal starting from the time of the disturbance to obtain preprocessed time series data;

[0030] Equipment inertial time constant identification module: Based on the preprocessed time series data, it acquires the instantaneous rate of change of node frequency and the active power response of each power generation device; by calculating adjustment parameters used to characterize and compensate for the damping and frequency regulation dynamics of the power generation device, and based on the adjustment parameters, the rate of change of frequency, and the active power response, it solves the power-frequency dynamic relationship model of the power generation device to obtain the corresponding initial value sequence of inertial time constants; and performs sliding window filtering processing on the initial value sequence of inertial time constants with the minimum statistical variance as the optimization objective to determine the inertial time constant of each power generation device.

[0031] The node equivalent inertia calculation module is used to aggregate the inertia time constants of each power generation device connected to the same power node based on the inertia time constant of each power generation device to obtain the equivalent inertia of each power node; and to calculate the equivalent inertia of the non-power node based on the relative relationship of the frequency change rate between the non-power node and the associated power node in the region, combined with the equivalent inertia of the associated power node.

[0032] This invention proposes an equivalent inertia assessment method and system considering damping-frequency modulation interference. By calculating the damping-frequency modulation capability characterization factor, the non-inertial components in the power response of the equipment are effectively removed, fundamentally overcoming the problem of inflated inertia assessment caused by neglecting damping and frequency modulation effects in traditional methods. For synchronous machines, a detailed model considering the prime mover reheat process and governor structure is adopted, significantly improving the accuracy of synchronous machine inertia identification. Using the equipment-level inertia results corrected for interference as input, high-precision inertia assessment is achieved across the entire chain from equipment to nodes. This method does not rely on prior system information and is directly based on wide-area measurement data, providing a more accurate and reliable quantitative basis for frequency security analysis and control of new power systems with a high proportion of power electronic equipment. Attached Figure Description

[0033] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0034] Figure 1 This is a flowchart of the equivalent inertia evaluation method considering damped-frequency modulation interference provided by the present invention;

[0035] Figure 2 This is a schematic diagram of the overall scheme of the equivalent inertia evaluation method considering damping-frequency modulation interference provided by the present invention;

[0036] Figure 3 This is a flowchart of the inertial time constant identification method of the equivalent inertia evaluation method considering damping-frequency modulation interference provided by the present invention.

[0037] Figure 4 This is a modular framework diagram of the equivalent inertia evaluation system considering damping-frequency modulation interference provided by the present invention. Detailed Implementation

[0038] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0039] Combination Figure 1 The present invention provides a method for evaluating equivalent inertia considering damped-frequency modulation interference, comprising:

[0040] S1. Real-time acquisition of frequency measurement signals from each node of the power system; calculation of frequency information entropy based on the distribution characteristics of the frequency measurement signals within a sliding time window; determination of the moment when the system power disturbance occurs based on the abrupt change in the frequency information entropy.

[0041] S2. Starting from the time when the disturbance occurs, preprocess the subsequent frequency signal and the subsequent port active power signal to obtain the preprocessed time series data.

[0042] S3. Based on the preprocessed time-series data, the instantaneous rate of change of node frequency and the active power response of each power generation device are obtained respectively; by calculating the adjustment parameters used to characterize and compensate for the damping and frequency regulation dynamics of the power generation device, and based on the adjustment parameters, the rate of change of frequency and the active power response, the power-frequency dynamic relationship model of the power generation device is used to solve the problem and obtain the corresponding initial value sequence of inertial time constant; the initial value sequence of inertial time constant is subjected to sliding window filtering with the minimum statistical variance as the optimization objective to determine the inertial time constant of each power generation device;

[0043] S4. Based on the inertial time constant of each power generation device, the inertial time constants of each power generation device connected to the same power node are aggregated to obtain the equivalent inertia of each power node; according to the relative relationship of the frequency change rate between non-power nodes and associated power nodes in the region, and in combination with the equivalent inertia of the associated power nodes, the equivalent inertia of the non-power nodes is calculated.

[0044] Combination Figure 2 The overall scheme of the equivalent inertia assessment method considering damped-frequency interference provided by the present invention includes four main stages: disturbance time determination, data preprocessing, equipment inertia identification, and node equivalent inertia calculation.

[0045] Further, step S1, determining the disturbance time, specifically includes: using a synchronous phasor measurement device (PMU) to collect the frequency of each node and the active power of the equipment port; applying a sliding window technique to the frequency measurement data, with a detection time window length of n and a sliding step size of 1; and calculating the frequency distribution probability p(k) after removing the base value component from the frequencies within the detection time window.

[0046]

[0047] Where f(k) is the sampling frequency after removing the base value component, and k is the sample number of the sampling frequency within the detection time window;

[0048] Then calculate the frequency information entropy S within the detection time window. i :

[0049]

[0050] where \(i\) is the number of the detection time window;

[0051] Since the occurrence of the disturbance is a process of increasing entropy and the frequency chaos increases, the threshold of the frequency information entropy is set as \(\varepsilon\). When continuously sliding the detection time window, when \(S\) i-1 \(<\varepsilon\) and \(S\) i \(\geq\varepsilon\), the sampling moment of the last frequency point in the \(i\)-th detection time window is regarded as the occurrence moment of the disturbance, and it is defined as \(t = 0\).

[0052] Furthermore, in step \(S2\), data preprocessing specifically includes: performing data preprocessing on the node frequency and the active power of the device port after the occurrence moment of the disturbance. First, the Newton interpolation method is used to interpolate the missing data. After interpolation, the node frequency and the active power of the device port are regarded as continuous. Then, a low-pass Butterworth filter is used to filter the frequency. Generally, the simulated inertia time constant is usually in the range of \(1.5 - 6.0s\), and the inertia time constant of the synchronous machine is generally greater than \(2.0s\). Therefore, the cut-off frequency of the low-pass Butterworth filter is set to \(0.667Hz\) to weaken the influence of high-frequency noise on the identification of the inertia time constant.

[0053] Furthermore, in combination with Figure 3 , step \(S3\), device inertia time constant identification, specifically includes:

[0054] S31. Perform adaptive variable-order polynomial fitting on the frequency response curves of each node and the active power curves of the device ports:

[0055]

[0056] where a 0, b 0, a 1, b 1, …, a n , b n are polynomial coefficients, P meas is the active power of the device port; np is the power fitting order, nf is the frequency fitting order.

[0057] S32. According to the power-frequency response equation of the synchronous machine, use the special point method to calculate the first characterization factor \(\lambda\) of the synchronous machine damping-frequency modulation ability SG1 and the reheat time constant \(T\) of the prime mover R :

[0058]

[0059]

[0060] Among them, the synchronous machine is taken as an example of a reheat thermal power unit, K m R is the mechanical power gain coefficient, and D is the droop coefficient of the speed governor. SG f is the damping coefficient of the synchronous machine. c f is the frequency of the equipment's grid-connected bus node. c,nadir P is the point of lowest frequency. meas,nadir t represents the active power of the device port corresponding to the lowest frequency point. nadir This corresponds to the lowest point time;

[0061] S33. Based on the power-frequency response equation of the power electronic equipment, select two operating points A and B shortly after the disturbance occurs, where the simulated primary frequency regulation of the power electronic equipment has not yet activated. Calculate the damping-frequency regulation capability characterization factor λ of the power electronic equipment using the difference calculation method. v :

[0062]

[0063] Among them, power electronic equipment refers to equipment that simulates synchronous machine control to a certain extent and is connected to the grid through a power electronic converter, K f D is the primary frequency regulation coefficient of the power electronic equipment; D is the damping coefficient of the power electronic equipment.

[0064] S34. Select two operating points E and F where the rate of frequency change is not zero after the disturbance occurs. The second characterization factor λ of the synchronous machine's damping-frequency modulation capability can be calculated from the synchronous machine's power-frequency response equation. SG2 :

[0065]

[0066]

[0067]

[0068] Among them, F H The power ratio of the high-pressure cylinder of the prime mover, t E t is the corresponding time at operating point E; F The corresponding time for operating point F; C, X E X F To calculate λ SG2 Intermediate variables;

[0069] S35. Substitute the parameters obtained from steps S32, S33, and S34 into the power-frequency response equation of the device, set the identification time window length L and the upper limit of the identification time window length, and calculate the inertial time constant H of the power electronic equipment simulation within the identification time window. vand the inertial time constant H of the synchronous machine SG :

[0070]

[0071]

[0072] Among them, P ini This represents the active power at the device port when no disturbance occurs.

[0073] S36. Calculate the variance S of all inertial time constant samples within the identification time window. j 2 :

[0074]

[0075] Among them, H j,l To identify the inertial time constant of the device within a time window, j is the identification time window number, l is the inertial time constant sample number within the identification time window, and H... a,j To identify the average value of the inertial time constant samples within the time window;

[0076] The identification time window is slid until the variance of the samples is minimized. The average inertial time constant within this identification time window is the final identification result H. equip .

[0077] Using the above method, the damping-frequency modulation capability characterization factor of the equipment can be determined, thereby overcoming the interference caused by damping and frequency modulation coefficients in the calculation of inertial time constant and improving the accuracy of inertial time constant identification. At the same time, the application of sliding window technology further eliminates the influence of individual outliers of inertial time constant on the identification results.

[0078] Further, step S4, the calculation of the equivalent inertia of the nodes, specifically includes:

[0079] To ensure that the equivalent inertia of the nodes also undergoes inertia correction considering damping and frequency modulation, the inertia H of each power node is first calculated by aggregating the identified equipment inertia time constants. source :

[0080]

[0081] Where m is the device number connected to the same power node, and S m For the installed capacity of the equipment;

[0082] Then, since the equivalent inertia of all nodes essentially originates from the energy of the power nodes, the equivalent inertia H of the non-power nodes in each region is calculated based on the difference in the rate of frequency change between the node to be identified and the power nodes within the region. bus :

[0083]

[0084] Among them, f bus f is the frequency of the node to be identified. source,bus H is the frequency of the power node in the region that is electrically closest to the node to be identified. source,bus This is the inertia of the power node;

[0085] Because the nearest power nodes to each non-power node are different, the reference selected for calculating the equivalent inertia of the nodes is different. To facilitate comparison, the equivalent inertia of all nodes is reduced to a unified standard capacity S. base Down:

[0086]

[0087] H bus-std This represents the equivalent inertia of each node after reduction.

[0088] Combination Figure 4 The equivalent inertia evaluation system considering damped-frequency interference provided by this invention includes:

[0089] Data acquisition and disturbance detection module: used to collect frequency measurement signals from each node of the power system in real time; calculate frequency information entropy based on the distribution characteristics of the frequency measurement signals within a sliding time window; and determine the time when the system power disturbance occurs based on the abrupt change in the frequency information entropy.

[0090] Data preprocessing module: used to collect the subsequent frequency signals of each node and the subsequent port active power signals of each power generation device, starting from the time when the disturbance occurs, and to preprocess the subsequent frequency signals and the subsequent port active power signals to obtain preprocessed time series data.

[0091] Equipment inertial time constant identification module: Based on the preprocessed time series data, it acquires the instantaneous rate of change of node frequency and the active power response of each power generation device; by calculating adjustment parameters used to characterize and compensate for the damping and frequency regulation dynamics of the power generation device, and based on the adjustment parameters, the rate of change of frequency, and the active power response, it solves the power-frequency dynamic relationship model of the power generation device to obtain the corresponding initial value sequence of inertial time constants; and performs sliding window filtering processing on the initial value sequence of inertial time constants with the minimum statistical variance as the optimization objective to determine the inertial time constant of each power generation device.

[0092] The node equivalent inertia calculation module is used to aggregate the inertia time constants of each power generation device connected to the same power node based on the inertia time constant of each power generation device to obtain the equivalent inertia of each power node; and to calculate the equivalent inertia of the non-power node based on the relative relationship of the frequency change rate between the non-power node and the associated power node in the region, combined with the equivalent inertia of the associated power node.

[0093] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for evaluating equivalent inertia considering damped-frequency modulation interference, characterized in that, include: S1. Real-time acquisition of frequency measurement signals from each node of the power system; calculation of frequency information entropy based on the distribution characteristics of the frequency measurement signals within a sliding time window; determination of the moment when the system power disturbance occurs based on the abrupt change in the frequency information entropy. S2. Starting from the time when the disturbance occurs, preprocess the subsequent frequency signal and the subsequent port active power signal to obtain the preprocessed time series data. S3. Based on the preprocessed time-series data, the instantaneous rate of change of node frequency and the active power response of each power generation device are obtained respectively; by calculating the adjustment parameters used to characterize and compensate for the damping and frequency regulation dynamics of the power generation device, and based on the adjustment parameters, the rate of change of frequency and the active power response, the power-frequency dynamic relationship model of the power generation device is used to solve the problem and obtain the corresponding initial value sequence of inertial time constant; the initial value sequence of inertial time constant is subjected to sliding window filtering with the minimum statistical variance as the optimization objective to determine the inertial time constant of each power generation device; Step S3 specifically includes: S31. Adaptive variable-order polynomial fitting is used to fit the node frequency curve and the active power curve at the device port respectively, so as to obtain the frequency change rate and the instantaneous change of the active power at the device port. S32. For synchronous generators, select the lowest frequency point after disturbance as the special operating point, and calculate the reheat time constant and the first characterization factor of damping-frequency regulation capability. S33. For power electronic equipment, select two short-time operating points after the disturbance and before the first frequency regulation action of the power electronic equipment, and calculate the damping-frequency regulation capability characterization factor of the power electronic equipment according to the power-frequency response equation and the difference calculation method. S34. For synchronous generators, select two operating points after disturbance and with non-zero frequency change rate, and calculate the second characterization factor of damping-frequency regulation capability based on the power-frequency response equation of the synchronous machine. S35. Substitute the characterization factors and parameters obtained in steps S32, S33, and S34 into the corresponding device power-frequency response model, and calculate the inertial time constant within the set identification time window. S36. Calculate the variance of all inertial time constant samples within the identification time window, slide the identification time window and repeat the variance calculation, and determine the average value of the inertial time constant within the identification time window corresponding to the minimum sample variance as the final identification result of the equipment inertial time constant. S4. Based on the inertial time constant of each power generation device, the inertial time constants of each power generation device connected to the same power node are aggregated to obtain the equivalent inertia of each power node; according to the relative relationship of the frequency change rate between non-power nodes and associated power nodes in the region, and in combination with the equivalent inertia of the associated power nodes, the equivalent inertia of the non-power nodes is calculated.

2. The equivalent inertia evaluation method considering damped-frequency modulation interference according to claim 1, characterized in that, Step S1 specifically includes: S11. The obtained node frequency data is segmented by a sliding time window with a length of n and a step size of 1, and the frequency sample distribution probability after removing the base value component in each window is calculated. S12. Calculate the frequency information entropy for each sliding time window based on the frequency sample distribution probability. S13. Set the frequency information entropy threshold to ε. When the frequency information entropy of two adjacent sliding time windows satisfies the condition that the entropy value of the previous window is less than ε and the entropy value of the current window is greater than or equal to ε, the end time of the current window is determined as the time when the system disturbance occurs.

3. The equivalent inertia evaluation method considering damped-frequency modulation interference according to claim 1, characterized in that, In step S2, the preprocessing includes: interpolating the missing data using Newton interpolation and filtering out high-frequency noise from the node frequency data using a low-pass Butterworth filter, wherein the cutoff frequency of the low-pass Butterworth filter is set to 0.667Hz.

4. The equivalent inertia evaluation method considering damped-frequency modulation interference according to claim 1, characterized in that, In step S31, the method for determining the order of the adaptive variable-order polynomial fitting is as follows: set a fitting deviation tolerance, start fitting from the initial order, and if the deviation between the fitting results after increasing the order is greater than the fitting deviation tolerance, continue to increase the order until the deviation between the fitting results obtained by increasing the order is less than or equal to the fitting deviation tolerance.

5. The equivalent inertia evaluation method considering damped-frequency modulation interference according to claim 1, characterized in that, Step S4 specifically includes: S41. Power node inertia aggregation: The device inertia time constant obtained in step S3 is weighted and aggregated to obtain the inertia of each power node. S42. Non-power node inertia allocation: For any non-power node, obtain the equivalent inertia of the nearest power node in the electrical area where the non-power node is located and the frequency change rate of the two. Based on the difference in the frequency change rate of the two, calculate the equivalent inertia of the non-power node.

6. An equivalent inertia evaluation system considering damped-frequency interference, applicable to the method of claim 1, characterized in that, include: Data acquisition and disturbance detection module: used to collect frequency measurement signals from each node of the power system in real time; calculate frequency information entropy based on the distribution characteristics of the frequency measurement signals within a sliding time window; and determine the time when the system power disturbance occurs based on the abrupt change in the frequency information entropy. Data preprocessing module: used to preprocess the subsequent frequency signal and the subsequent port active power signal starting from the time of the disturbance to obtain preprocessed time series data; Equipment inertial time constant identification module: Based on the preprocessed time series data, it acquires the instantaneous rate of change of node frequency and the active power response of each power generation device; by calculating adjustment parameters used to characterize and compensate for the damping and frequency regulation dynamics of the power generation device, and based on the adjustment parameters, the rate of change of frequency, and the active power response, it solves the power-frequency dynamic relationship model of the power generation device to obtain the corresponding initial value sequence of inertial time constants; and performs sliding window filtering processing on the initial value sequence of inertial time constants with the minimum statistical variance as the optimization objective to determine the inertial time constant of each power generation device. The node equivalent inertia calculation module is used to aggregate the inertia time constants of each power generation device connected to the same power node based on the inertia time constant of each power generation device to obtain the equivalent inertia of each power node; and to calculate the equivalent inertia of the non-power node based on the relative relationship of the frequency change rate between the non-power node and the associated power node in the region, combined with the equivalent inertia of the associated power node.

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