Power grid high-resilience coordinated operation method under multi-source disturbance scenario

Abstract

The present application relates to the technical field of power grid state analysis, and in particular to a power grid high-resilience coordinated operation method under a multi-source disturbance scenario. The method constructs a frequency influence graph structure with oscillation frequency as a node, and uses a poor convergence mapping algorithm to analyze the driving influence relationship between oscillation components in the graph structure. Two nodes that meet the verification condition are taken as analysis objects, the peak significant degree is used to represent the energy transfer between frequencies, the edge weight of the graph structure is adjusted, and a verified oscillation image graph is obtained. The dominant influence path is obtained. By analyzing the propagation power on the dominant path and the change characteristics of the propagation power, combined with the above other basic power grid characteristics, the power grid oscillation state can be determined. The present application can identify the power grid state before the oscillation event occurs by analyzing the change characteristics of the propagation power of the oscillation frequency on the dominant influence path, avoiding monitoring hysteresis, and improving the real-time performance and decision efficiency of the power grid coordinated operation decision.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power grid state analysis, and in particular to a power grid high-resilience coordinated operation method under a multi-source disturbance scenario. BACKGROUND

[0002] With the rapid increase of the penetration rate of power electronic interface type new energy represented by wind power and photovoltaic power in the power system, the dynamic characteristics of the system are changing from being dominated by traditional synchronous generators to being jointly dominated by numerous grid-forming inverters. Grid-forming inverter technology is considered to be the key to supporting the stable operation of the system in the future weak power grid mode because it can simulate the external characteristics of synchronous generators. When grid-forming inverter units are connected to areas with insufficient grid strength, the complex multi-loop control system inside the units and the dynamic characteristics of the external grid are extremely likely to interact rapidly in the sub- / super-synchronous frequency band, thereby inducing millisecond-level electromagnetic oscillations. The fundamental mechanism of such oscillations is that, under certain operating conditions, the interaction between the grid-forming inverter unit and the grid is equivalent to presenting a "negative damping" characteristic, which not only cannot suppress the inherent oscillation mode of the system, but also injects energy into it, causing the oscillation to be rapidly amplified.

[0003] In the prior art, an online monitoring method can be used to alarm abnormal fluctuations in voltage, power and other electrical quantities at the grid connection point, but the essence of this method is a passive response based on the "symptoms" of oscillation. When the oscillation phenomenon is clearly measurable, the system is often in a critical state of instability, leaving a short intervention window for the operator. Therefore, the direct monitoring method has a certain lag and cannot effectively analyze the driving characteristics of the oscillation, thereby leading to poor implementation effect of the coordinated operation decision of the power grid. SUMMARY

[0004] In order to solve the technical problem that the existing monitoring method has a certain lag and cannot effectively analyze the driving characteristics of the oscillation, thereby leading to poor implementation effect of the coordinated operation decision of the power grid, the purpose of the present application is to provide a power grid high-resilience coordinated operation method under a multi-source disturbance scenario, and the technical solution adopted is as follows:

[0005] The present application provides a power grid high-resilience coordinated operation method under a multi-source disturbance scenario, which comprises the following steps:

[0006] The voltage complex signal and the current complex signal at the grid connection point of the grid-forming inverter station are jointly analyzed to screen out an oscillation frequency set; the injected active power of each oscillation frequency is obtained, and the oscillation component of each oscillation frequency in the voltage complex signal is obtained;

[0007] constructing a frequency-to-frequency influence graph structure with the oscillation frequencies as nodes, obtaining a one-way influence coefficient between two oscillation components by using a convergent cross mapping algorithm, the one-way influence coefficient being used as an edge weight in the frequency-to-frequency influence graph structure; traversing each edge in the frequency-to-frequency influence graph structure, and if the frequency difference between the two nodes corresponding to the edge satisfies a verification condition, obtaining a peak significance of the two nodes in a bispectrum of a current complex signal, adjusting the edge weight according to the peak significance, and obtaining a verified oscillation influence graph;

[0008] adjusting an injected active power of each node according to the edge weight in the verified oscillation influence graph, and obtaining a propagation power; finding a dominant influence path in the verified oscillation influence graph according to the propagation power; comparing an overall propagation power in the dominant influence path with the propagation power at a starting node of the dominant influence path, and obtaining a propagation path amplification coefficient;

[0009] determining a power grid oscillation state according to the injected active power of the oscillation frequency, the propagation path amplification coefficient, and the structural complexity of the verified oscillation influence graph, and coordinating operation according to the power grid oscillation state.

[0010] Further, the screening condition of the oscillation frequency is:

[0011] performing peak value searching on the voltage complex signal and the current complex signal respectively within a preset frequency band, and if a certain frequency corresponds to a peak value on both the voltage complex signal and the current complex signal, and the amplitude of the peak value is greater than a preset energy threshold, the frequency is taken as the oscillation frequency.

[0012] Further, the formula for obtaining the injected active power includes:

[0013] ; wherein is the injected active power of the kth oscillation frequency , Re{} represents taking the real part of a complex number, is a frequency spectrum complex value corresponding to the kth oscillation frequency on the voltage complex signal, is a frequency spectrum complex value corresponding to the kth oscillation frequency on the current complex signal, represents taking the conjugate.

[0014] Further, the method for obtaining the one-way influence coefficient includes:

[0015] obtaining a correlation coefficient change curve between a predicted value and an actual value generated by two oscillation components in the convergent cross mapping algorithm; and taking an average value of the last preset number of correlation coefficients in the curve as the one-way influence coefficient.

[0016] Further, the method for obtaining the verified oscillation influence graph includes:

[0017] For two nodes satisfying the verification condition, multiplying the peak salience degree by the original edge weight value to obtain an adjusted edge weight value;

[0018] For two nodes not satisfying the verification condition, setting the adjusted edge weight value to 0;

[0019] If the adjusted edge weight value is less than a preset edge weight threshold value, removing the corresponding edge to obtain the verification oscillation influence graph.

[0020] Further, the method for obtaining the propagation power comprises:

[0021] For a node, if the injected active power is not a positive value, setting the propagation power to 0; if the injected active power is a positive value, taking the product of the injected active power and the edge weight value as the propagation power.

[0022] Further, the method for obtaining the dominant influence path comprises:

[0023] Taking any one node with a non-0 propagation power as a starting point and ending at any one node, traversing all paths, and screening out a path with the largest propagation power cumulative value on the path as the dominant influence path.

[0024] Further, the method for obtaining the propagation path amplification coefficient comprises:

[0025] Taking the propagation power cumulative value of all nodes on the dominant influence path as a numerator and the propagation power of the starting node as a denominator to obtain the propagation path amplification coefficient.

[0026] Further, the method for judging the structural complexity comprises:

[0027] If there is more than one dominant influence path or the difference between the propagation power cumulative values of other paths and the dominant influence path is less than a preset difference threshold value, judging that the verification oscillation influence graph has a structural complexity.

[0028] Further, the power grid oscillation state is judged level by level according to a multi-level judgment mechanism, comprising:

[0029] The first-level judgment mechanism is used to, after obtaining the injected active power of each oscillation frequency in the oscillation frequency set, count the cumulative value of all positive injected active powers as a first judgment value, and if the first judgment value is less than a preset safety threshold value, judging that the power grid oscillation state is a stable state and ending the multi-level judgment; otherwise, entering the next level of judgment.

[0030] The second-level judgment mechanism is used to judge the structural complexity of the verification oscillation influence graph, and if the structural complexity exists, judging that the power grid oscillation state is a system coupling conflict state; otherwise, entering the next level of judgment.

[0031] The third level judging mechanism is used for judging whether the propagation path amplification coefficient is less than a preset coefficient threshold value, and if yes, judging that the power grid oscillation state is a latent source state, otherwise, a path dominant instability state.

[0032] The present application has the following advantages:

[0033] In order to analyze the frequency characteristics of the power grid oscillation, the present application takes the direct current complex signals of the current and the voltage as the analysis objects, and then uses the existing frequency analysis algorithm such as the Fourier algorithm to screen out the oscillation frequency set producing the synchronous oscillation in the two signals. Further, the active power injected by the oscillation frequency can be used to judge whether it belongs to the "negative damping" feature. In order to analyze the driving characteristics between the oscillations, the present application takes the oscillation frequency as the node to construct the frequency influence graph structure, and uses the poor convergence mapping algorithm to analyze the driving influence relationship between the oscillation components in the graph structure. For the power system, the energy will be transferred between different frequencies, and if the oscillation line is produced, the similar sideband components will be produced in the current for a certain frequency. Therefore, the present application further verifies the frequency relationship in the graph structure, takes the two nodes meeting the verification condition as the analysis objects, uses the peak value significance to represent the energy transfer between the frequencies, adjusts the edge weight value of the graph structure, and obtains the verification oscillation image graph. The verification oscillation image graph has undergone the one-way driving analysis and the energy conduction analysis between the frequencies, and can effectively represent the frequency driving conditions of the oscillation event. Therefore, the path analysis is performed on the verification oscillation image graph to obtain the dominant influence path. By analyzing the propagation power on the dominant path and the change characteristics of the propagation power, and combining the above other basic power grid characteristics, the power grid oscillation state can be determined. Through the one-way driving analysis and the energy conduction analysis between the oscillation frequencies, the present application obtains the dominant influence path representing the driving trend of the oscillation event, and then analyzes the propagation power change characteristics of the oscillation frequency on the dominant influence path, so that the power grid state can be identified before the oscillation event occurs, the monitoring lag is avoided, and the real-time performance and the decision efficiency of the power grid coordinated operation decision are improved. BRIEF DESCRIPTION OF DRAWINGS

[0034] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, and the advantages thereof, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained from these drawings without creative labor.

[0035] Figure 1 A power grid high-resilience coordinated operation method flow chart under a multi-source disturbance scenario is provided for an embodiment of the present application. DETAILED DESCRIPTION

[0036] In order to further clarify the technical means and effects taken by the present application to achieve the predetermined inventive purpose, the following describes in detail the specific implementation, structure, features and effects of a power grid high-resilience coordinated operation method in a multi-source disturbance scenario according to the present application, in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0037] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs.

[0038] The specific scheme of the power grid high-resilience coordinated operation method in a multi-source disturbance scenario provided by the present application is described in detail below in combination with the accompanying drawings.

[0039] Please refer to Figure 1 which shows a flow chart of a power grid high-resilience coordinated operation method in a multi-source disturbance scenario provided by an embodiment of the present application. The method comprises:

[0040] Step S1: jointly analyze the voltage complex signal and the current complex signal at the grid-connected point of the grid-forming inverter station, and screen out a set of oscillation frequencies; obtain the injected active power of each oscillation frequency, and obtain the oscillation component of each oscillation frequency in the voltage complex signal.

[0041] Since the dynamic interaction between the grid-forming inverter and the weak power grid occurs in the electromagnetic time scale of milliseconds, its oscillation frequency covers a wide frequency band from subsynchronous to super-synchronous, and the conventional steady-state measurement system cannot capture its complete dynamic process. Therefore, the high-frequency electrical quantities of the grid-connected point are continuously processed in the embodiment of the present application, and the voltage data and current data at the grid-connected point are jointly analyzed. Considering that the data collected directly are all alternating current signals, and are three-phase alternating current signals, i.e. the data collected directly by the sensor are three-phase voltage signals and three-phase current signals, it is not convenient to directly analyze the dynamic state of the three-phase alternating current signals, therefore, the Park transformation in the power system can be used to convert the three-phase alternating current signals into direct current quantities under the base frequency steady state, i.e. voltage complex signals and current complex signals, which contain all the dynamic information in the original three-phase alternating current signals, and can be used as the data basis for frequency spectrum analysis.

[0042] It should be noted that the synchronous reference phase angle required by the Park transformation can be obtained by a phase-locked loop in real time tracking the power grid fundamental voltage, and the specific transformation method is a technical means known to those skilled in the art. The sampling frequency of the three-phase alternating current signal in the embodiment of the application is set to 5 kHz, the signal in the embodiment of the application is segmented by a fixed sliding window, the sliding window length is 2 seconds, that is, the signal length is 2 seconds, in order to realize quasi-online continuous monitoring, an overlap is set between adjacent sliding windows, the embodiment of the application sets an overlap of 1.5 seconds, that is, the sliding step of the sliding window is 0.5 seconds, the processes described subsequently in the embodiment of the application are realized in a sliding window, that is, the final obtained power grid oscillation state is in a sliding window. The sub / super synchronous frequency band concerned in the embodiment of the application is 5 Hz to 150 Hz.

[0043] For the oscillation frequency to be screened out, the first condition to be met is that the frequency is in the sub / super synchronous frequency band, and the second condition to be met is that the oscillation frequency can simultaneously affect the voltage and the current and produce a large impact, which indicates that the screening of the oscillation frequency concerns the dynamic interaction of both the inverter and the power grid, rather than the unilateral internal disturbance. Therefore, the embodiment of the application can screen out the oscillation frequency set by jointly analyzing the voltage complex signal and the current complex signal at the grid connection point of the grid-connected inverter station.

[0044] Preferably, in the embodiment of the application, the screening condition of the oscillation frequency is:

[0045] In the preset frequency band, the peak value of the voltage complex signal and the current complex signal is searched respectively, if a certain frequency corresponds to a peak value on both the voltage complex signal and the current complex signal, and the amplitude of the peak value is greater than a preset energy threshold, the frequency is taken as the oscillation frequency. In the embodiment of the application, the setting of the energy threshold can be set according to the specific power grid power performance, which is not described and limited in the embodiment of the application.

[0046] It should be noted that before the oscillation frequency screening, the voltage complex signal and the current complex signal need to be subjected to fast Fourier transform, and then the voltage frequency and the current spectrum are obtained, and each frequency in the spectrum can be screened. In order to reduce the influence of spectrum leakage, the FFT of the window function (such as the Hamming window) or the improved spectrum estimation algorithm such as Welch's method can be used in the embodiment of the application.

[0047] Further, in order to measure the damping characteristics of each oscillation frequency, the injected active power of each oscillation frequency is obtained, that is, the injected active power is a positive number, which indicates that at the corresponding oscillation frequency, the inverter is positively injecting energy into the power grid, showing a negative damping characteristic, and the oscillation frequency is an energy source of the oscillation event.

[0048] In order to analyze the causal inference of the oscillation event in the subsequent step, the dynamic waveform corresponding to the screened oscillation frequency needs to be separated from the mixed signal, that is, the embodiment of the present application needs to obtain the oscillation component of each oscillation frequency in the voltage complex signal.

[0049] In the embodiment of the present application, for a certain oscillation frequency , a narrow-band digital band-pass filter with a center frequency of can be designed, and a Butterworth filter or a finite impulse response (FIR) filter can be selected; a small passband width is further set, and the embodiment of the present application is set to 1 Hz. The original voltage complex sequence is taken as the input of the filter, and the output is the isolated oscillation component containing only the dynamic oscillation near the oscillation frequency .

[0050] Preferably, in the embodiment of the present application, because the obtained signals are complex signals, in order to quantify the injected active power, the obtained formula of the injected active power includes:

[0051] ; wherein is the injected active power of the kth oscillation frequency , Re{} represents taking the real part of a complex number, is the corresponding spectral complex value of the kth oscillation frequency on the voltage complex signal, is the corresponding spectral complex value of the kth oscillation frequency on the current complex signal, represents taking the conjugate. It should be noted that the formula is the application of the active power formula on the complex number, which is a well-known technical feature to those skilled in the art, and will not be described and limited here. The injected active power is greater than 0, indicating that the grid point outputs active power to the power grid at the frequency , for example, the inverter sends power to the power grid at the fundamental frequency; the injected active power is less than 0, indicating that the power grid absorbs active power from the grid point at the frequency , for example, the grid-connected converter absorbs energy from the power grid as a load, or energy flows from the power grid to the grid point at a certain harmonic frequency.

[0052] Step S2: constructing a frequency-to-frequency influence graph structure with the oscillation frequency as a node, obtaining a one-way influence coefficient between two oscillation components by using a convergent cross mapping algorithm, the one-way influence coefficient serving as an edge weight value in the frequency-to-frequency influence graph structure; traversing each edge in the frequency-to-frequency influence graph structure, if the frequency difference between the corresponding two nodes meets a verification condition, obtaining the peak prominence of the two nodes in the bispectrum of the current complex signal, adjusting the edge weight value according to the peak prominence, and obtaining a verified oscillation influence graph.

[0053] In order to analyze the oscillation event causally, the embodiment of the present application analyzes the oscillation propagation path in the form of a graph structure. The oscillation propagation path first exists in the information level, that is, there is one-way driving influence from one oscillation frequency to another oscillation frequency. Secondly, in the energy level, the influence must pass through the nonlinear modulation process of the power electronic switch to generate energy transfer between frequencies that can be verified. Therefore, the embodiment of the present application uses two analysis methods of one-way driving analysis and energy conduction analysis respectively in step S2 to construct an effective graph structure for subsequent propagation path analysis.

[0054] First, one-way driving analysis between oscillation frequencies is performed. Since the control system (such as phase-locked loop, power loop, current loop) of the grid-connected inverter has a cascade structure, the dynamic of the outer loop will one-way and nonlinearly affect the dynamic of the inner loop. In order to capture this directed driving relationship, the embodiment uses the convergent cross mapping method to analyze the one-way driving influence between oscillation frequencies. The embodiment of the present application takes the oscillation frequency as the node. For any two nodes, the one-way influence coefficient between the corresponding two oscillation components is obtained by the convergent cross mapping algorithm, and the one-way influence coefficient is taken as the edge weight between the two nodes.

[0055] It should be noted that the convergent cross mapping algorithm is a well-known technical means to those skilled in the art, and will not be described in detail. The embodiment of the present application takes the oscillation frequency to the oscillation frequency as an example to analyze the one-way influence between the two nodes, the oscillation frequency corresponding oscillation component and the oscillation frequency corresponding oscillation component perform convergent cross mapping algorithm analysis:

[0056] (1) State space reconstruction: Since the one-way influence driving between the oscillation frequency to the oscillation frequency is analyzed, if the dynamic of the oscillation frequency has a causal effect on the oscillation frequency , the evolution information of the oscillation frequency will be imprinted in the dynamic of the oscillation frequency , so the state space manifold is reconstructed by time delay embedding of the oscillation frequency . The process is completed by selecting a suitable embedding dimension and time delay. In the embodiment of the present application, the embedding dimension can be an integer between 3 and 5, and the time delay can be determined by calculating the autocorrelation function or the average mutual information function of the oscillation frequency . It should be noted that the reconstruction length of the state space manifold in the convergent cross mapping algorithm is gradually increased, and finally the length of the entire can be increased, and multiple reconstruction length state space manifolds are gradually obtained.

[0057] (2) Cross mapping and prediction: using the reconstructed state-space manifold predict The value, to obtain and Predicted sequences of the same length, the predicted sequences are also in There is a corresponding real sequence above.

[0058] (3) Calculation of one-way influence coefficient: Calculate the correlation coefficient between the predicted sequence and the true sequence, and record the curve of the correlation coefficient change as the reconstruction length increases. If the correlation coefficient gradually increases and converges as the reconstruction length increases, a one-way influence coefficient can be quantified. The larger the one-way influence coefficient, the higher the oscillation frequency. To the oscillation frequency The stronger the unidirectional driving relationship between two nodes, the better. In this embodiment of the invention, the correlation coefficient can be the Pearson correlation coefficient, which is a well-known technique among those skilled in the art and will not be described in detail here.

[0059] The frequency influence diagram structure in this embodiment of the invention can be further converted into a matrix form, where the length and width of the matrix are both the number of oscillation frequencies. Each element in the matrix represents the unidirectional influence coefficient between the oscillation frequency represented by the corresponding row and the oscillation frequency represented by the corresponding column.

[0060] Preferably, in this embodiment of the invention, the method for obtaining the one-way influence coefficient includes:

[0061] Obtain the correlation coefficient change curve between the predicted and actual values ​​generated by the two oscillating components in the convergent cross-mapping algorithm; take the average of the last preset number of correlation coefficients on the curve as the one-way influence coefficient. In this embodiment of the invention, the preset number can be set to 10.

[0062] The frequency influence diagram, which includes the unidirectional driving effect between oscillation frequencies, only reflects the information flow relationship of the time series at the statistical level. In power electronic systems, any control-level influence must ultimately be realized through the nonlinear process of high-frequency switching of power semiconductors, in the form of energy transfer between different frequencies. For example, a low-frequency oscillation... Modulating the fundamental frequency component will inevitably generate a current. The sideband components, of which This is the fundamental frequency of the power grid. Therefore, it is also necessary to perform energy transfer analysis between oscillation frequencies to propose pseudo-transfer relationships without an energy basis.

[0063] This invention employs bispectral analysis as a verification tool, a technique that can effectively detect three-wave coupling phenomena caused by second-order nonlinear effects in signals. Bispectral analysis uses complex current signals as the analysis object, first calculating their bispectrum, which is then plotted at a certain coordinate point. the magnitude of the three frequency components, directly quantifies the strength of the nonlinear phase coupling between the three frequency components , and . For each edge in the inter-frequency influence graph structure, i.e. each element after the embodiment of the present application is converted into a matrix form, if the frequency difference of the corresponding two nodes meets the verification condition, the peak prominence of the two nodes in the bispectrum of the current complex signal is obtained, and the greater the peak prominence is, the more the corresponding two oscillation frequencies meet the verification. Therefore, the edge weight value can be adjusted according to the peak prominence, and the verified oscillation influence graph is obtained.

[0064] Specifically, the energy transfer analysis specific steps of the embodiment of the present application include:

[0065] (1) Construct a verification hypothesis: for the path in the inter-frequency influence graph structure, the energy transfer hypothesis is that the oscillation with the frequency nonlinearly couples with a known, energy significant frequency in the system, thereby generating an oscillation component with the frequency . The known frequency is usually the power grid fundamental frequency, which is usually 50 Hz.

[0066] (2) Test the frequency relationship: under the above verification hypothesis, it is further tested whether there is a frequency such that the sum or difference of and is within a certain tolerance. That is, or . The tolerance set by the embodiment of the present application is 0.5 Hz, i.e. the sum or difference of and is within 0.5 Hz of , which means that the verification condition is met.

[0067] (3) Check the bispectrum evidence: if the above relationship is established, further obtain the bispectrum amplitude of the corresponding position of the current bispectrum, and determine the peak prominence of the amplitude. It should be noted that the quantification method of the peak prominence in the embodiment of the present application can select a method based on statistics and local background, i.e. the peak prominence can be accurately quantified by combining the local signal-to-noise ratio with the Z standard molecule. In the embodiment of the present application, it is further normalized by range standardization, and the value range is limited to 0 to 1.

[0068] It should be noted that the edge weight value to be adjusted in the present application should be the edge weight value of the edge with non-zero value in the inter-frequency influence graph structure, and if there is no energy transmission between two nodes after the bispectrum verification, the corresponding edge can be eliminated. Specifically, in the embodiment of the present application, the method for verifying the oscillation influence graph comprises:

[0069] For two nodes satisfying the verification condition, the peak significance degree is multiplied by the original edge weight value to obtain an adjusted edge weight value;

[0070] For two nodes not satisfying the verification condition, the adjusted edge weight value is set to 0;

[0071] If the adjusted edge weight value is less than a preset edge weight threshold, the corresponding edge is removed to obtain the verified oscillation influence graph.

[0072] That is, through the processing of the above method, the edges with original edge weight value of 0 and the edges that fail the energy verification are all removed, so that each edge in the verified oscillation influence graph simultaneously has the one-way driving direction in the information layer and the transmission evidence in the energy layer. In the embodiment of the present application, the edge weight threshold can be set to 0.05.

[0073] Step S3: adjusting the injected active power of each node according to the edge weight value in the verified oscillation influence graph to obtain a propagation power; finding out a dominant influence path in the verified oscillation influence graph according to the propagation power; and comparing the overall propagation power in the dominant influence path with the propagation power at the starting node of the dominant influence path to obtain a propagation path amplification coefficient.

[0074] The overall instability of the power grid system is usually caused by an initial energy injection source, which is amplified along one or more influence paths and eventually leads to instability. Therefore, in order to effectively determine the oscillation state of the power grid, it is necessary to analyze the dominant influence path in the verified oscillation influence graph.

[0075] Firstly, it is necessary to assign a clear power attribute to each node and edge in the verified oscillation influence graph, that is, to adjust the injected active power of each node according to the edge weight value in the verified oscillation influence graph to obtain a propagation power. That is, each node corresponds to a propagation power. It should be noted that only the oscillation frequency showing negative damping can be used as the starting point of the oscillation propagation chain, so for the oscillation frequency showing negative injected active power, the propagation power can be directly set to 0.

[0076] Preferably, in the embodiment of the present application, the method for obtaining the propagation power comprises:

[0077] For each node, if the injected active power is not positive, the propagation power is set to 0; if the injected active power is positive, the product of the injected active power and the edge weight is taken as the propagation power. That is, the propagation power represents the propagation power generated by one node to another node, which is expressed by a formula as ; wherein is the propagation power of node to node , is the injected active power of node , is the adjusted edge weight of node to node .

[0078] Based on the propagation power, the dominant influence path in the verification oscillation influence graph can be found, that is, on the dominant influence path, through the propagation among multiple nodes, a larger propagation power is generated.

[0079] Preferably, in the embodiment of the present application, the method for obtaining the dominant influence path comprises:

[0080] Taking any node with a non-0 propagation power as a starting point and ending at any node, all paths are traversed, and the path with the largest propagation power cumulative value on the path is selected as the dominant influence path. It should be noted that, since the verification oscillation influence graph is a directed acyclic graph, this process can be solved using a dynamic programming algorithm for a directed acyclic graph, which is a well-known technical means to those skilled in the art, and will not be described here.

[0081] For the dominant influence path, the overall propagation power in the dominant influence path can be compared with the propagation power at the starting node of the dominant influence path to obtain a propagation path amplification coefficient. That is, the larger the path amplification coefficient, the more serious the oscillation hidden danger.

[0082] Preferably, in the embodiment of the present application, the method for obtaining the propagation path amplification coefficient comprises:

[0083] The propagation power cumulative value of all nodes on the dominant influence path is taken as the numerator, and the propagation power of the starting node is taken as the denominator to obtain the propagation path amplification coefficient.

[0084] It should be noted that in the process of dominant influence path identification, the final obtained dominant influence path can be more than one, or the difference between the propagation power accumulation value of other paths and the dominant influence path is less than the preset difference threshold, which indicates that the structure of the verified oscillation image is complex, resulting in that a unique dominant path cannot be identified. This situation indicates that the problem is no longer limited to a single source or a clear propagation chain, but a wideband, diffuse coupling conflict between multiple control links, a fragile system structure and a low resilience level.

[0085] Step S4: determining the power grid oscillation state according to the injection active power size of the oscillation frequency, the propagation path amplification coefficient, and the structural complexity of the verified oscillation influence graph, and coordinating operation according to the power grid oscillation state.

[0086] The embodiment of the present application aims to improve the high resilience of the power grid by effectively identifying the power grid oscillation state and feeding back reasonable coordination decisions, so that the power grid can not only maintain stability when facing disturbances, but also predict and suppress potential instability risks. The root of this ability lies in the clear understanding of the source and development mechanism of the risk. The coordination operation means that when the risk occurs, the control measures should be the coordinated actions between multiple subjects (such as inverter stations and power grid dispatchers) with basis, rather than single and isolated responses. The existing power grid operation cannot timely distinguish whether it is a single control link parameter drift, a coupling amplification between multiple links, or a systematic structural conflict when facing oscillation phenomena formed by multiple source disturbances, and can only adopt universal and exploratory adjustment strategies, the effect of which is difficult to guarantee. The embodiment of the present application provides a set of qualitative and quantitative identification features of unstable oscillation risks according to the injection active power size of the oscillation frequency, the propagation path amplification coefficient, and the structural complexity of the verified oscillation influence graph, so the oscillation state of the power grid can be effectively determined according to the performance of the set of features. Then, the coordination operation is performed according to the power grid oscillation state.

[0087] The power grid oscillation state is not a single dimension, but is jointly determined by the strength of the oscillation source, the clarity and amplification effect of the propagation path, so in the embodiment of the present application, the power grid oscillation state is judged step by step according to a multi-level judgment mechanism, which specifically includes:

[0088] The first level judgment mechanism is used to, after obtaining the injection active power of each oscillation frequency in the oscillation frequency set, count the accumulation value of all positive injection active powers as a first judgment value, if the first judgment value is less than a preset safety threshold, the power grid oscillation state is judged to be a stable state and the multi-level judgment is ended, which indicates that there is no significant negative damping source in the power grid system, the internal disturbance can resist the power grid system itself, and the power grid system runs to the stable region; otherwise, the next level judgment is entered.

[0089] The second-level judgment mechanism is used to judge the structural complexity of the oscillation influence diagram. If the structure is complex, the power grid oscillation state is judged to be a systemic coupling conflict state. This state indicates that the oscillation is no longer limited to a single source or a clear propagation chain, but that a wide-bandwidth, diffuse coupling conflict has occurred between multiple control links. The system structure is fragile and has a low resilience level. Otherwise, it proceeds to the next level of judgment.

[0090] The third-level judgment mechanism is used to determine whether the propagation path amplification factor is less than a preset threshold. If it is less, the power grid oscillation state is judged to be a latent source state. This state corresponds to the early budding stage of instability risk. A specific control link has begun to exhibit negative damping characteristics, but the unstable energy it generates has not yet found an effective amplification and propagation channel in the system. Otherwise, it is a path-dominated instability state. This state indicates that there is already a clear and significant oscillation propagation path in the power grid system. For example, the oscillation of the phase-locked loop affects the current loop through nonlinear coupling and is eventually amplified.

[0091] In this embodiment of the invention, the preset coefficient threshold can be set to 1.5, and the safety threshold can be specifically set according to parameters such as power grid performance. This embodiment of the invention will not limit or elaborate further.

[0092] The power grid system can implement effective collaborative control strategies based on the power grid state feedback determined above. Specifically, in this embodiment of the invention, these strategies include:

[0093] (1) If the power grid oscillation is a latent source, it indicates that the oscillation risk source is singular and has not spread. A targeted elimination strategy should be adopted, focusing on the source. The strategy could include suggestions such as "fine-tuning the parameters of the power station." Based on the diagnosis, the oscillation source is... This is related to the dynamic characteristics of the specific control element, such as the phase-locked loop (PLL). It is recommended to adjust the control parameters of this element appropriately (e.g., reduce the PLL bandwidth) to eliminate oscillation sources. This refers to the oscillation frequency corresponding to the starting node of the dominant influence path. This decision only needs to be executed at the power station side and has a relatively small impact on the power grid.

[0094] (2) If the grid oscillation is path-dominant instability, it indicates that the oscillation risk has formed a clear propagation chain. Intervention at both the source and the path is necessary to achieve coordinated control between the power station and the grid, or within multiple links within the power station. Decision-making may include "Recommendation to adopt source-grid coordinated control." Diagnosis reveals that... The dominant power propagation path of the drive. Recommendation: 1. (Site-side - fundamental solution) Adjust the frequency of the oscillation source. The relevant control parameters are eliminated to eliminate the risk source. 2. (station side or grid side-break link) At the same time, additional damping control is put into the frequency of the end of the path or the key intermediate node, or the relevant link parameters are adjusted to block the energy propagation path. For example, if the frequency at the end of the path is related to the current loop, the current loop parameters are adjusted.

[0095] (3) If the grid oscillation state is a systemic coupling conflict state, it means that the system is on the edge of structural instability, and fine adjustment may fail, so a conservative and system-level risk reduction strategy should be taken to prioritize grid safety. The decision content can include "suggesting to take a system-level emergency protection strategy. Diagnose the systemic control conflict of multiple points or wide frequency band. Suggestion: 1. (station side-mode switching) To resolve complex dynamic interaction, immediately switch the main control mode of XX station from network construction type (GFM) to network following type (GFL). 2. (grid side-enhanced network) If the conditions allow, the dispatching side adjusts the grid operation mode (such as putting in the nearby synchronous generator set) to enhance the strength of the grid in this area and change the boundary conditions of oscillation occurrence.

[0096] Through the above diagnosis of the grid oscillation state and the feedback of the collaborative decision, the grid operation resilience is effectively improved in the complex scenario of high proportion of new energy penetration.

[0097] To sum up, the application takes the direct current complex signal of current and voltage as the analysis object, and screens out the oscillation frequency set generating synchronous oscillation in the two signals. The oscillation frequency is taken as a node to construct a frequency influence graph structure, and a poor convergence mapping algorithm is used to analyze the driving influence relationship between the oscillation components in the graph structure. Two nodes that meet the verification condition are taken as the analysis object, the peak significant degree is used to represent the energy transfer between frequencies, and then the edge weight of the graph structure is adjusted to obtain a verified oscillation image. The dominant influence path is obtained. By analyzing the propagation power on the dominant path and the change characteristics of the propagation power, combined with the above other basic grid characteristics, the grid oscillation state can be determined. The application obtains the dominant influence path that can represent the driving trend of the oscillation event through the one-way driving analysis and energy conduction analysis between the oscillation frequencies, and then analyzes the propagation power change characteristics of the oscillation frequencies on the dominant influence path to identify the grid state before the oscillation event occurs, avoiding monitoring lag and improving the real-time and decision efficiency of the grid coordinated operation decision.

[0098] It should be noted that the above-mentioned order of the embodiments of the application is only for description, and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or can be advantageous.

[0099] The various embodiments described in this specification are presented by way of example, and each embodiment is not inherently more important than any other embodiment.

Claims

1. A method for highly resilient coordinated operation of a power grid under multi-source disturbance scenarios, characterized in that, The method includes: We jointly analyze the complex voltage and complex current signals at the grid connection point of the grid-connected inverter power station to select the set of oscillation frequencies; obtain the injected active power at each oscillation frequency, and obtain the oscillation component of each oscillation frequency in the complex voltage signal; A frequency influence graph structure is constructed using oscillation frequencies as nodes. A convergent cross-mapping algorithm is used to obtain the unidirectional influence coefficient between two oscillation components. The unidirectional influence coefficient is used as the edge weight in the frequency influence graph structure. Each edge in the frequency influence graph structure is traversed. If the frequency difference between the corresponding two nodes satisfies the verification condition, the peak significance of the two nodes in the bispectrum of the complex current signal is obtained. The edge weight is adjusted according to the peak significance to obtain the verification oscillation influence graph. The injected active power of each node is adjusted according to the edge weights in the verification oscillation influence graph to obtain the propagation power; the dominant influence path in the verification oscillation influence graph is found according to the propagation power; the overall propagation power in the dominant influence path is compared with the propagation power at the starting node of the dominant influence path to obtain the propagation path amplification factor. Based on the magnitude of injected active power at the oscillation frequency, the amplification factor of the propagation path, and the structural complexity of the verification oscillation influence diagram, the grid oscillation state is determined, and coordinated operation is carried out according to the grid oscillation state. The formula for obtaining the injected active power includes: ;in The k-th oscillation frequency The injected active power, Re{} represents taking the real part of the complex number, The k-th oscillation frequency The complex spectral values ​​corresponding to the complex voltage signal. The k-th oscillation frequency The complex spectral values ​​corresponding to the complex current signal. Indicates taking the conjugate; The power grid oscillation state is determined step-by-step according to a multi-level judgment mechanism, including: The first-level judgment mechanism is used to calculate the cumulative value of all positive injected active power after obtaining the injected active power of each oscillation frequency in the oscillation frequency set as the first judgment value. If the first judgment value is less than the preset safety threshold, the grid oscillation state is judged to be a stable state and the multi-level judgment ends; otherwise, it proceeds to the next level of judgment. The second-level judgment mechanism is used to judge the structural complexity of the oscillation influence diagram. If the structure is complex, the power grid oscillation state is judged to be a systemic coupling conflict state; otherwise, it proceeds to the next level of judgment. The third-level judgment mechanism is used to determine whether the propagation path amplification coefficient is less than the preset coefficient threshold. If it is less, the power grid oscillation state is determined to be a latent source state; otherwise, it is a path-dominated instability state.

2. The method for high-resilience coordinated operation of a power grid under multi-source disturbance scenarios according to claim 1, characterized in that, The selection criteria for the oscillation frequency are as follows: Within a preset frequency band, peak searches are performed on both the complex voltage signal and the complex current signal. If a certain frequency corresponds to a peak value in both the complex voltage signal and the complex current signal, and the amplitude of the peak value is greater than a preset energy threshold, then the frequency is taken as the oscillation frequency.

3. The method for high-resilience coordinated operation of a power grid under multi-source disturbance scenarios according to claim 1, characterized in that, The method for obtaining the one-way influence coefficient includes: Obtain the correlation coefficient change curve between the predicted value and the true value generated by the two oscillating components in the convergent cross-mapping algorithm; take the average of the last preset number of correlation coefficients on the curve as the one-way influence coefficient.

4. The method for high-resilience coordinated operation of a power grid under multi-source disturbance scenarios according to claim 1, characterized in that, The method for obtaining the verification oscillation influence diagram includes: For two nodes that meet the verification conditions, the significance of the peak value is multiplied by the original edge weight to obtain the adjusted edge weight. For two nodes that do not meet the verification conditions, the adjusted edge weights are set to 0. If the adjusted edge weight is less than the preset edge weight threshold, the corresponding edge is removed to obtain the verification oscillation influence map.

5. The method for high-resilience coordinated operation of a power grid under multi-source disturbance scenarios according to claim 1, characterized in that, The method for obtaining the propagation power includes: For a node, if the injected active power is not positive, the propagation power is set to 0; if the injected active power is positive, the product of the injected active power and the edge weight is used as the propagation power.

6. The method for high-resilience coordinated operation of a power grid under multi-source disturbance scenarios according to claim 5, characterized in that, The method for obtaining the dominant influence path includes: Starting from any node with non-zero propagation power and ending at any node, traverse all paths and select the path with the largest cumulative propagation power as the dominant influence path.

7. The method for high-resilience coordinated operation of a power grid under multi-source disturbance scenarios according to claim 1, characterized in that, The method for obtaining the propagation path amplification factor includes: The propagation path amplification factor is obtained by using the sum of the propagation power of all nodes on the dominant influence path as the numerator and the propagation power of the starting node as the denominator.

8. The method for high-resilience coordinated operation of a power grid under multi-source disturbance scenarios according to claim 6, characterized in that, The methods for determining the structural complexity include: If there is more than one dominant influence path, or if the difference between the cumulative propagation power of other paths and the dominant influence path is less than a preset difference threshold, then the structure of the verification oscillation image is determined to be complex.

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