New energy station broadband oscillation risk review and evaluation method based on multi-element data

Abstract

The present application belongs to the technical field of power system risk assessment, and particularly relates to a new energy station wide frequency oscillation risk review assessment method based on multi-element data, steps of which comprise: for the coupling system of a new energy station-grid, data collection and data preprocessing are performed to obtain a historical data set; oscillation characteristic indexes are extracted to form an index vector; oscillation frequency source positioning analysis is performed, time-frequency spectrum energy functions are calculated, oscillation energy spectrum is obtained, main frequency energy trajectory extraction is performed, and a frequency-power cross analysis mechanism is introduced to realize accurate identification of the oscillation source device; a source-grid coupling transfer function is constructed, stability margin calculation is performed, and the stability state of the coupling system is determined; based on the index vector and the stability margin, oscillation risk level division is performed, and in combination with the source positioning result, an oscillation review spectrum is generated. The present application can realize panoramic review and risk quantitative assessment of the new energy station wide frequency oscillation problem.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of power system risk assessment, and particularly relates to a new energy station wide frequency oscillation risk review evaluation method based on multi-element data. BACKGROUND

[0002] With the rapid development of "double high" characteristic power systems, i.e. high proportion of new energy access and high proportion of power electronic equipment application, the operation characteristics of the power grid are becoming increasingly complex. Under this background, the wide frequency oscillation problem has become a prominent problem affecting the safe and stable operation of the power system. During the grid-connected operation of the new energy station, the coupling between a large number of power electronic converters inside the station and the weak power grid often leads to oscillation phenomena with a wide frequency range and complex energy distribution. Such wide frequency oscillation not only covers low frequency mechanical-electrical modes, but also widely exists in the medium frequency and high frequency bands, and has characteristics such as multi-mode, multi-source, and multi-time and space propagation.

[0003] The current wide frequency oscillation problem presents three significant trends: first, the oscillation frequency band is widely distributed, and oscillation events from 2Hz to thousands of Hz frequently occur; second, the oscillation source is complex, involving new energy controllers, grid-connected interfaces, power electronic devices, impedance coupling and other multi-factor interactions; third, the propagation path is uncertain, and the oscillation signal may spread through multiple channels in the system, causing local or even systemic instability risks.

[0004] However, the existing oscillation risk monitoring methods are mainly real-time detection, focusing on single-point early warning, and lacking the ability to analyze the depth of systemic, implicit and evolutionary risks. In the high proportion of new energy access scenario, the oscillation problem often shows strong concealment, complex triggering mechanism and nonlinear development process, and the traditional monitoring method is difficult to timely and comprehensively reveal the evolution path and essential mechanism of the problem. SUMMARY

[0005] In view of the above deficiencies in the prior art, the purpose of the present application is to provide a new energy station wide frequency oscillation risk review evaluation method based on multi-element data, which can realize panoramic review and risk quantitative evaluation of the new energy station wide frequency oscillation problem.

[0006] To achieve the above purpose, the present application provides a new energy station wide frequency oscillation risk review evaluation method based on multi-element data, comprising the following steps:

[0007] S1, for the coupled system of the new energy station and the power grid, data acquisition is performed, including station side data, grid-connected side data and auxiliary data;

[0008] S2, the collected data is preprocessed to obtain a historical data set;

[0009] S3, extract oscillation characteristic indexes based on the historical data set, including frequency domain indexes, time domain indexes and statistical indexes, to form an index vector;

[0010] S4, perform oscillation frequency source positioning analysis, perform short-time Fourier transform on the high-frequency voltage or high-frequency current signal in the field station side data to generate a time-frequency spectrum, calculate a time-frequency spectrum energy function to obtain an oscillation energy spectrum, perform main frequency energy trajectory extraction, and introduce a frequency-power cross analysis mechanism to realize accurate identification of the oscillation source device;

[0011] S5, based on the historical data set, construct a source-network coupled transfer function, perform stability margin calculation, and determine the stable state of the coupled system;

[0012] S6, based on the index vector and the stability margin, perform oscillation risk level division, and generate an oscillation review spectrum in combination with the source positioning result.

[0013] As a preferred scheme of the present application, the data collected in S1 specifically includes:

[0014] The field station side data includes:

[0015] High-frequency voltage / current signal: the instantaneous value signal of voltage / current of each measuring point is collected by using a voltage transformer and a current transformer;

[0016] Device control parameter: the control parameter of the power electronic device inside the new energy field station is collected, and the power electronic device includes an inverter, a converter, a static var generator, an energy storage converter and a DC-DC converter;

[0017] Power change record: the real-time change of active power and reactive power of the new energy field station to the power grid is continuously recorded by the power measuring device of each measuring point;

[0018] Device state quantity information: the running state information of the power electronic device inside the new energy field station is collected, including whether it is in the commissioning state, whether a fault or protection action occurs, and running mode switching condition;

[0019] The grid-connected side data includes:

[0020] Common connection point impedance spectrum scanning result: the impedance at the common connection point of the new energy field station and the power grid is scanned in a wide frequency domain by using an impedance measuring device or a modeling simulation method to obtain the impedance amplitude and phase characteristics at different frequencies;

[0021] Power flow data: the power flow data of the common connection point and the related line of the power grid are collected, including the power flow distribution of active power, reactive power, voltage and current;

[0022] Voltage stability parameters: collect the fluctuation range of voltage amplitude, voltage change rate, and voltage stability margin index;

[0023] Supporting data, including:

[0024] Dispatch instruction record: Records dispatch instructions issued by the power grid to renewable energy power plants, including power regulation instructions and operating mode switching instructions;

[0025] Environmental meteorological data: Collect environmental meteorological data of the area where the new energy power station is located, including wind speed, light intensity and temperature.

[0026] As a preferred embodiment of the present invention, the preprocessing step S2 includes:

[0027] Time synchronization: timestamp synchronization is performed on all acquisition channels, and resampling is performed using a uniform sampling frequency. For high-frequency voltage / current signals, a bandpass filter is used for noise removal.

[0028] An event-triggered operating condition slicing mechanism is introduced, which divides the collected time-series data into multiple stable operating segments based on sudden changes in scheduling instructions, switching of equipment operating modes, and wind speed jumps as slice boundaries.

[0029] After data slicing, structural normalization is performed to unify the dimensions and units of different physical quantities, generate standard input data moments, and obtain historical datasets.

[0030] As a preferred embodiment of the present invention, in S3, the frequency domain parameters include minimum impedance margin, phase margin, gain margin, and harmonic amplification factor, wherein the minimum impedance margin... Represented as:

[0031] ;

[0032] In the formula, The current frequency is j, where j is the imaginary unit. The frequency response of the equivalent impedance on the station side; The frequency response of the equivalent impedance on the grid-connected side; min indicates taking the minimum value;

[0033] Based on the impedance spectrum scan results of the point of common coupling, a Bode plot is drawn to find the source-grid impedance amplitude crossover frequency. The difference between the phase angle and 180° at this frequency is calculated as the phase margin. The phase crossover frequency is found, and the difference between 1 and the impedance amplitude ratio at this frequency is calculated as the gain margin.

[0034] The harmonic amplification factor (HMF) is defined as:

[0035] ;

[0036] Wherein, max represents taking maximum value;

[0037] The time-domain index includes the main frequency energy proportion and the oscillation duration, wherein the main frequency energy proportion is defined as the proportion of the signal energy in the main frequency band to the total energy:

[0038] ;

[0039] Wherein, is the main frequency; is the frequency band width; represents the frequency domain amplitude value obtained by performing short-time Fourier transform on the high-frequency voltage or high-frequency current signal; represents the energy spectrum density of the signal at the current frequency ;

[0040] The energy threshold is set, the time when the signal energy first exceeds the energy threshold is identified as the oscillation starting time , the time when the signal energy last time is lower than the energy threshold is identified as the oscillation ending time , and the oscillation duration is defined as:

[0041] ;

[0042] The statistical index includes the spectrum entropy and the waveform distortion rate, wherein the spectrum entropy H is defined as:

[0043] ;

[0044] Wherein, i and z represent the index of the frequency component, is the energy proportion probability of the i-th frequency component; represents the signal energy on the i-th frequency component; represents the signal energy on the z-th frequency component.

[0045] As a preferred scheme of the present application, in the S4, the process of obtaining the oscillation energy spectrum and extracting the main frequency energy track is:

[0046] S4.1, performing short-time Fourier transform on the high-frequency voltage or high-frequency current signal to obtain the time-frequency spectrum ;

[0047] S4.2, calculating the time-frequency spectrum energy function , converting the complex-valued signal in the time-frequency domain into the energy distribution, the value of which represents the energy intensity at the corresponding time t and the current frequency , taking t as the horizontal axis, as the vertical axis, and The value is mapped to color or gray scale, forming an oscillation energy spectrum, and the peak value trajectory indicates the excitation and attenuation process of the frequency component over time;

[0048] S4.3, extracting the main frequency energy trajectory from the oscillation energy spectrum, determining the oscillation starting time, main frequency energy proportion, energy growth stage, and energy decay stage.

[0049] As a preferred scheme of the present application, in S4, a frequency-power cross analysis mechanism is introduced to realize the process of accurate identification of the oscillation source device:

[0050] S4.4, jointly analyzing the power change rate of each measuring point and the main frequency component intensity change , wherein P represents the power, and f represents the main frequency; the Pearson correlation coefficient is used to quantify the linear correlation degree r between , and a correlation threshold is set, when is greater than the correlation threshold, it is preliminarily determined that the power electronic equipment associated with P and is involved in the oscillation, and it is classified as a suspected oscillation source equipment;

[0051] S4.5, based on the load response behavior before and after the power data, combining the device control parameters, device state quantity information and load response behavior before and after, excluding the power electronic equipment which is only a response source, so as to accurately locate the oscillation source equipment.

[0052] As a preferred scheme of the present application, in S4.5, if the following conditions are met at the same time, it is determined that the power electronic equipment is only a response source, and is excluded:

[0053] Load response timing: the post-load power change lags behind the pre-load, and the power change trend of the pre-load is consistent with the power change trend of the power electronic equipment;

[0054] Device control parameters: the control strategy is passive following type, and the control parameters are within the normal range;

[0055] Device state quantity: the device is in normal operation and full-power stable operation state.

[0056] As a preferred scheme of the present application, in S5, the transfer function of the source-grid coupling is constructed, the stability margin is calculated, and the process of judging the stability state of the coupling system is:

[0057] S5.1, the impedance relationship at the interface between the new energy station and the power grid is simplified as:

[0058] ;

[0059] In the formula, a transfer function of source-net coupling;

[0060] S5.2, if in a certain frequency band and , then the coupling system has a stability threat, wherein arg represents the argument of a complex number;

[0061] S5.3, a stability margin calculation is performed, the stability margin includes a phase margin, a gain margin and a harmonic magnification factor, when the HMF is greater than a set empirical threshold value, then the coupling system has a stability threat;

[0062] S5.4, based on and curves, a Nyquist diagram is drawn, and the relative position of the transfer function trajectory and the -1+j0 point is observed, if the trajectory encloses the point, then the coupling system has a stability threat.

[0063] As a preferred scheme of the present application, in S6, the oscillation risk level is divided into three categories: low risk, medium risk and high risk:

[0064] High risk: simultaneously satisfying the phase margin less than 10°, HMF greater than 0.9, less than 1.2, greater than 70%, H greater than 0.8, greater than 3 seconds;

[0065] Medium risk: there is at least one of the phase margin less than 10°, HMF greater than 0.9, less than 1.2, greater than 70%, H greater than 0.8, greater than 3 seconds, but not all of them are satisfied;

[0066] Low risk: there is no any one of the phase margin less than 10°, HMF greater than 0.9, less than 1.2, greater than 70%, H greater than 0.8, greater than 3 seconds.

[0067] As a preferred scheme of the present application, in S6, the oscillation complex atlas contains:

[0068] a main frequency evolution trajectory diagram, based on a frequency domain index, showing the trend of the main frequency changing with time;

[0069] a frequency domain amplitude-phase margin curve diagram: based on a Bode diagram, marking the crossover point and the margin value;

[0070] Time-domain oscillation waveform diagram: based on high-frequency voltage or high-frequency current signal, and superimposed with oscillation start / end time;

[0071] Device state and control response superposition diagram: based on device control parameters and device state quantity information, and superimposed with oscillation source positioning results, showing the correlation between power electronic device state changes and oscillation;

[0072] Risk level spatial distribution diagram: marking the risk level of each power electronic device in the area where the new energy station is located.

[0073] The present application has the beneficial effects of:

[0074] The present application constructs a full-process, multi-dimensional systematic evaluation system, breaks through the limitations of traditional real-time detection, integrates high-frequency voltage and current, impedance scanning, device state, weather and other multi-source historical data, forms a unified analysis basis through standardized preprocessing, and then constructs a complete index system from the frequency domain (such as impedance margin, phase margin), time domain (such as main frequency energy ratio, oscillation duration), statistical domain (such as spectral entropy, distortion rate), which can realize the comprehensive quantification of oscillation characteristics, solve the fragmentation and localization problem of traditional methods, and the core index has clear physical meaning and clear safety boundary, which is convenient for engineering landing and standardized promotion.

[0075] The present application uses time-frequency method (short-time Fourier transform STFT), combines power change and device state, can accurately locate the oscillation source start time, propagation path and suspected device, and restores the whole chain of oscillation evolution; through source-network impedance model and Bode diagram, Nyquist diagram and other tools to inverse stability margin, which can identify the risk of coupled system approaching stability boundary in advance. On this basis, through fuzzy logic and threshold mapping to divide the risk level, and generate visual review atlas including main frequency trajectory, device response, etc., which can directly support operation management, parameter setting and other scenes, significantly improve the grid control and decision-making efficiency, and can adapt to different types of new energy stations and access modes, with strong adaptability. BRIEF DESCRIPTION OF DRAWINGS

[0076] Figure 1 is the flow principle diagram of the present application. DETAILED DESCRIPTION

[0077] The embodiments of the present application will be further described below in combination with the drawings:

[0078] Embodiment 1: as shown in the figure, the new energy station wideband oscillation risk review evaluation method based on multi-element data includes the following steps: Figure 1

[0079] S1, for the coupled system of new energy station-grid, data acquisition is carried out, including station side data, grid side data and auxiliary data; ​

[0080] S2, pre-processing the collected data to obtain a historical data set;

[0081] S3, extracting oscillation feature indicators based on the historical data set, including frequency domain indicators, time domain indicators and statistical indicators, to form an indicator vector;

[0082] S4, performing oscillation frequency source positioning analysis, performing short-time Fourier transform on the high-frequency voltage or high-frequency current signal in the field station side data to generate a time-frequency spectrum, calculating a time-frequency spectrum energy function to obtain an oscillation energy spectrum, extracting a main frequency energy trajectory, and introducing a frequency-power cross analysis mechanism to realize accurate identification of the oscillation source device;

[0083] S5, based on the historical data set, constructing a transfer function of source-network coupling, calculating a stability margin, and determining the stability state of the coupled system;

[0084] S6, based on the indicator vector and the stability margin, performing oscillation risk level division, and combining the results of source positioning to generate an oscillation review atlas.

[0085] In S1, the collected data specifically includes:

[0086] The field station side data includes:

[0087] High-frequency voltage / current signal: using voltage transformers and current transformers to collect the instantaneous value signals of voltage / current at each measuring point;

[0088] Device control parameters: collecting the control parameters of power electronic devices inside the new energy power station, including inverters, converters, static var generators, energy storage converters, and DC-DC converters;

[0089] Power change record: continuously recording the real-time changes of active power and reactive power transmitted by the new energy power station to the power grid through power measuring devices at each measuring point;

[0090] Device state quantity information: collecting the running state information of power electronic devices inside the new energy power station, including whether it is in operation, whether it has failed or protection action, and running mode switching;

[0091] The grid side data includes:

[0092] Public connection point impedance spectrum scanning result: using impedance measurement equipment or modeling simulation method to perform wide frequency domain scanning on the impedance at the public connection point of the new energy power station and the power grid, to obtain the impedance amplitude and phase characteristics at different frequencies;

[0093] Power flow data: Collect power flow data on the point of common coupling and related lines of the power grid, including active power, reactive power, voltage, current, and power flow distribution;

[0094] Voltage stability parameters: Collect the fluctuation range of voltage amplitude, voltage change rate, and voltage stability margin index;

[0095] Auxiliary data is used to assist in identifying disturbance trigger background and oscillation development boundary, including:

[0096] Dispatching instruction record: Record the dispatching instructions issued by the power grid to the new energy station, including power regulation instructions and operation mode switching instructions;

[0097] Environmental meteorological data: Collect environmental meteorological data in the area where the new energy station is located, including wind speed, light intensity, and temperature.

[0098] In S2, due to the different sampling frequencies, large differences in physical quantity dimensions, and non-uniform units of the above multi-source data, format conversion and standardization processing are required. The preprocessing process includes:

[0099] Time synchronization: synchronize the timestamps of all collection channels, resample with a unified sampling frequency, and use a band-pass filter (20Hz~5kHz range) to remove noise for high-frequency voltage / current signals;

[0100] Introduce an event-triggered working condition slicing mechanism, taking dispatching instruction mutation, device operation mode switching, and wind speed jump as the slicing boundary. The collected time series data (various dynamic data related to the operation of new energy stations and grid-connected power grids collected continuously in chronological order) are divided into multiple stable running segments;

[0101] After data slicing, structure normalization processing is performed to unify the dimensions and units of different physical quantities, generating a standard input data matrix, and obtaining a historical data set, which can be represented as:

[0102] ;

[0103] where, is the historical data set at time t; is the high-frequency voltage signal at time t; is the high-frequency current signal at time t; is the impedance frequency response at time t; is the dispatching instruction sequence at time t; is the device state quantity information at time t; is the environmental meteorological data at time t.

[0104] In S3, the frequency domain indicators include minimum impedance margin, phase margin, gain margin and harmonic magnification factor, wherein the minimum impedance margin is expressed as:

[0105] ;

[0106] In the formula, is the current frequency (a frequency range that the wide-frequency oscillation may involve), and j is the imaginary unit; is the frequency response of the equivalent impedance on the station side (reflecting the impedance characteristics of the entire source side from the grid-connection point of the new energy station inward); is the frequency response of the equivalent impedance on the grid-connection side (reflecting the impedance characteristics of the grid system from the grid-connection point of the new energy station outward); min represents the minimum value; the subscript represents the impedance amplitude of the source-grid impedance at the frequency ; calculates the value of , and selects the minimum value as ;

[0107] When and tend to be equal or the modulus is close, the coupling system stability margin is reduced, and the wide-frequency oscillation caused by control interaction is easily excited.

[0108] Based on the common connection point impedance frequency spectrum scanning result, a Bode diagram is drawn to find the source-grid impedance amplitude crossover frequency, calculate the difference between the phase angle and 180° at this frequency as the phase margin, find the phase crossover frequency, and calculate the difference between 1 and the impedance amplitude ratio at this frequency as the gain margin;

[0109] The phase margin is the phase angle distance at the source-grid impedance amplitude crossover frequency, reflecting the phase stability of the coupling system to small signal disturbance; the gain margin measures the margin of the coupling system when the open-loop gain reaches unit gain, and both are intuitively represented as the frequency boundary of system stability in the Bode diagram.

[0110] The harmonic magnification factor HMF is defined as:

[0111] ;

[0112] In the formula, max represents the maximum value; the subscript represents the impedance amplitude of the source-grid impedance at the frequency ; calculates the value of , and selects the maximum value as HMF;

[0113] When high-order control loop resonances, nonlinear saturation or filter parameter mismatches exist in the coupled system, HMF can significantly increase, becoming an important precursor of oscillation risk.

[0114] The time-domain indicators include the energy ratio of dominant frequency and the oscillation duration, where the energy ratio of dominant frequency (ERDF) is defined as the ratio of the signal energy in the dominant frequency band to the total energy:

[0115] ;

[0116] wherein, is the dominant frequency (the frequency of the dominant oscillation); is the band width; represents the frequency-domain amplitude obtained by short-time Fourier transform on the high-frequency voltage or high-frequency current signal; represents the energy spectrum density of the signal at the current frequency ;

[0117] The higher the ERDF is, the stronger the oscillation concentration is; otherwise, there may be a wide frequency distribution or multi-modal coupled oscillation. The oscillation duration is determined by a signal energy threshold detection window, reflecting the time span of the oscillation behavior in a certain frequency band, and plays an important guiding role in determining whether intervention is needed.

[0118] An energy threshold is set, and the time when the signal energy first exceeds the energy threshold is identified as the oscillation start time , and the time when the signal energy last falls below the energy threshold is identified as the oscillation end time , and the oscillation duration is defined as:

[0119] ;

[0120] The statistical indicators include the spectral entropy and the waveform distortion rate (for high-frequency voltage / current), where the spectral entropy H is defined as:

[0121] ;

[0122] wherein i, z represent the index of the frequency component, is the energy ratio probability of the i-th frequency component; represents the signal energy on the i-th frequency component; represents the signal energy on the z-th frequency component.

[0123] H reflects the degree of concentration of the frequency distribution. The larger the value, the more discrete the frequency distribution of the coupled system, the more modes it has, and the greater the difficulty of analysis and control. Combining frequency skewness, waveform distortion rate (THD, an existing indicator), and other indicators can further identify complex phenomena such as multi-frequency oscillations and controller coupling.

[0124] All indicators constitute an indicator vector within each operating condition segment, serving as input support for subsequent oscillation source location, risk level assessment, and retrospective chart construction.

[0125] In S4, the process of obtaining the oscillation energy spectrum and extracting the main frequency energy trajectory is as follows:

[0126] S4.1 Perform a short-time Fourier transform on the high-frequency voltage or high-frequency current signal to obtain the time spectrum. ;

[0127] S4.2 Calculation of the time-frequency energy function This converts complex-valued signals in the time-frequency domain into energy distributions. The value indicates the current frequency at the corresponding time t. The strength of energy, plotted on the horizontal axis as t. Using the vertical axis, The values ​​are mapped to colors or grayscale to form an oscillating energy spectrum, whose peak trajectory indicates the excitation and decay process of frequency components over time.

[0128] S4.3 Extract the dominant frequency energy trajectory from the oscillation energy spectrum to determine the oscillation start time, dominant frequency energy ratio, energy growth stage, and energy decay stage.

[0129] The process of introducing a frequency-power cross-analysis mechanism to accurately identify oscillation source devices is as follows:

[0130] S4.4, The power change rate at each measuring point With the change in the intensity of the main frequency component Joint analysis, where P represents power, This represents the main frequency; Pearson correlation coefficient is used for quantification. and The degree of linear correlation r, setting a correlation threshold, when When the correlation threshold is greater than 1, it is initially determined that it is simultaneously related to P and Related power electronic devices are involved in the oscillation and are classified as suspected oscillation source devices;

[0131] S4.5. Based on power data, obtain the response behavior of the load before and after the load, and combine the equipment control parameters, equipment status information and the response behavior of the load before and after the load to exclude power electronic equipment that is only a response source, thereby accurately locating the oscillation source equipment.

[0132] If the following conditions are met at the same time, it is determined that the power electronic device is only a response source, and it is excluded:

[0133] Load response timing: the power change of the post-load lags behind the pre-load, and the power change trend of the pre-load is consistent with the power change trend of the power electronic device;

[0134] Device control parameters: the control strategy is passive following type, and the control parameters are within the normal range;

[0135] Device state quantity: the device is in normal operation and full power stable operation state.

[0136] In addition, combined with the scale-time representation in wavelet analysis, transient oscillation and wide frequency sweep phenomenon can be located. Especially in the presence of multi-frequency coupling or controller switching, wavelet packet decomposition can show clearer modal overlap and amplitude mutation, effectively supporting source identification and propagation trend restoration in complex oscillation scenarios.

[0137] In S5, the transfer function of source-grid coupling is constructed, the stability margin is calculated, and the process of judging the stable state of the coupled system is as follows:

[0138] S5.1, the impedance relationship at the interface between the new energy station and the power grid is simplified as:

[0139] ;

[0140] In the formula, is the transfer function of source-grid coupling;

[0141] S5.2, if satisfies and , the coupled system has a stability threat, where arg represents the argument of a complex number;

[0142] S5.3, stability margin calculation is performed, including phase margin, gain margin and harmonic magnification factor. When HMF is greater than the set empirical threshold (0.9), the coupled system has a stability threat;

[0143] S5.4, based on and curves, the Nyquist diagram (a frequency characteristic diagram of a linear control system) is drawn, and the relative position of the trajectory of the transfer function and the point -1+j0 (a key point on the complex plane, which can also be expressed as (-1, 0) point) is observed. If the trajectory encloses the point (which indicates that the phase margin and other stability indicators do not meet the requirements), the coupled system has a stability threat.

[0144] In S6, the oscillation risk level is divided into low risk, medium risk and high risk:

[0145] High risk: simultaneously satisfying phase margin less than 10°, HMF greater than 0.9, less than 1.2, greater than 70%, H greater than 0.8, greater than 3 seconds;

[0146] Medium risk: at least one of the following conditions exists, but not all of them are satisfied: phase margin less than 10°, HMF greater than 0.9, less than 1.2, greater than 70%, H greater than 0.8, greater than 3 seconds;

[0147] Low risk: none of the following conditions exists: phase margin less than 10°, HMF greater than 0.9, less than 1.2, greater than 70%, H greater than 0.8, greater than 3 seconds.

[0148] The oscillation risk level evaluation mechanism can realize the automatic judgment and visual review of the oscillation degree of new energy station under different scenarios. By setting classification thresholds, the oscillation risk level of the station under certain working conditions is quantified by considering frequency domain indicators, time domain indicators and statistical indicators. For example, in a certain scenario, if the spectral concentration is very high and the main frequency band coincides with the open-loop frequency of the device controller, combined with the frequency source positioning display, the oscillation starts from the key equipment, which can be comprehensively evaluated as a high-risk working condition, and timely attention or treatment measures should be taken.

[0149] The oscillation review atlas includes:

[0150] Main frequency evolution trajectory diagram: based on frequency domain indicators, showing the trend of main frequency change over time;

[0151] Frequency domain amplitude-phase margin curve diagram: based on Bode diagram, marking the crossover point and margin value;

[0152] Time domain oscillation waveform diagram: based on high-frequency voltage or high-frequency current signal, and superimposed with oscillation start / end time;

[0153] Device state and control response superposition diagram: based on device control parameters and device state quantity information, and superimposed with oscillation source positioning results, showing the correlation between power electronic device state change and oscillation;

[0154] Risk level spatial distribution diagram: marking the risk level of each power electronic device in the area where the new energy station is located.

[0155] Under the condition of multi-point measurement, the oscillation reconstruction atlas can also reflect the oscillation propagation path. For example, by the order of frequency component excitation between measurement points, the oscillation propagation time sequence chain can be constructed, and the space mapping can be carried out combined with the device position, and finally the full-chain reproduction of the oscillation event "from where to start, how to spread, and when to end" is realized. These reconstruction information has high reference value for subsequent control strategy modification, device parameter optimization and dispatching mode adjustment.

[0156] The method of the embodiment can be applied to a new energy station, a regional regulation center or a power grid operation management platform, realizes real-time data archiving and periodic reconstruction evaluation, and enhances the foresight and scientificity of power system oscillation prevention and control.

[0157] A typical broadband oscillation signal is simulated, and based on the method of the embodiment, the broadband oscillation offline evaluation table generated is shown in Table 1. It can be seen that the main oscillation components are successfully identified, each frequency band risk is evaluated, and the potential optimization direction is pointed out. This set of process and method can be applied to the analysis and diagnosis of complex oscillation problems in actual engineering systems.

[0158] Table 1: Broadband oscillation offline evaluation table

[0159]

[0160] Embodiment 2: On the basis of embodiment 1, a structured auxiliary decision evaluation report is further generated, including oscillation event occurrence time, dominant frequency interval, index overrun information, suspected source device position, stability margin change trend, oscillation risk level determination conclusion and optimization suggestions for the station or regulation department.

[0161] The auxiliary decision evaluation report supports a variety of engineering scene applications such as grid connection evaluation, operation and maintenance governance, regulation parameter setting and control strategy formulation, and has strong practical guiding value.

[0162] Embodiment 3: A new energy station broadband oscillation risk reconstruction evaluation device based on multi-element data, comprising:

[0163] One or more processors;

[0164] A memory for storing one or more computer programs;

[0165] When one or more programs are executed by one or more processors, the one or more processors execute the method in embodiment 1 or embodiment 2.

[0166] Embodiment 4: A computer readable storage medium having executable instructions stored thereon, the instructions being executed by a processor to execute the method in embodiment 1 or embodiment 2.

Claims

1. A method for wide frequency oscillation risk review and evaluation of a new energy station based on multi-element data, characterized in that The method comprises the following steps: S1, for the coupling system of new energy station-grid, data acquisition is carried out, including station side data, grid side data and auxiliary data; S2, the collected data is preprocessed to obtain a historical data set; S3, based on the historical data set, oscillation characteristic indexes are extracted, including frequency domain indexes, time domain indexes and statistical indexes, to form an index vector; S4, oscillation frequency source positioning analysis is carried out, high-frequency voltage or high-frequency current signals obtained by collecting the instantaneous value signals of voltage / current of each measuring point in the station side data are subjected to short-time Fourier transform to generate a time-frequency spectrum, the energy function of the time-frequency spectrum is calculated to obtain an oscillation energy spectrum, and a main frequency energy track is extracted, the process being: S4.1, short-time Fourier transform of the high-frequency voltage or high-frequency current signal, resulting in a time-frequency spectrum ; S4.2, calculate time-frequency spectrum energy function , convert the complex-valued signal in time-frequency domain to energy distribution, , the value size represents the energy intensity of the corresponding time t, current frequency , take t as the horizontal axis, , take as the vertical axis, map the value of to color or gray scale, form an oscillation energy spectrum, and the peak value trajectory indicates the excitation and decay process of frequency components over time; S4.3, the main frequency energy track is extracted from the oscillation energy spectrum, and the oscillation starting time, the main frequency energy proportion, the energy growth stage and the energy attenuation stage are determined; A frequency-power cross analysis mechanism is introduced to realize accurate identification of the oscillation source device, the process being: S4.4, the power change rate of each measurement point with the main frequency component intensity change joint analysis, where P represents power, represent the main frequency; using Pearson correlation coefficient to quantify with linear correlation degree r, set the correlation threshold, when greater than the correlation threshold, preliminary determination of the power electronic equipment associated with P and related to the oscillation, which is classified as a suspected oscillation source equipment; S4.5, based on the load response behavior before and after the power data, combined with the device control parameters, device state quantity information and load response behavior before and after, the power electronic device which is only a response source is excluded, so as to accurately locate the oscillation source device; S5, based on the historical data set, a transfer function of source-grid coupling is constructed, stability margin calculation is carried out, and the stability state of the coupling system is judged; S6, based on the index vector and the stability margin, the oscillation risk level is divided, and the oscillation review spectrum is generated combined with the source positioning result.

2. The method of claim 1, wherein the method further comprises: The data collected in S1 specifically includes: The station side data includes: High-frequency voltage / current signals: the instantaneous value signals of voltage / current of each measuring point are collected by using voltage transformers and current transformers; Device control parameters: the control parameters of power electronic devices inside the new energy station are collected, the power electronic devices including inverters, converters, static var generators, energy storage converters and DC-DC converters; Power change record: the real-time change of active power and reactive power transmitted by the new energy station to the grid is continuously recorded by the power measuring device of each measuring point; Device state quantity information: the running state information of power electronic devices inside the new energy station is collected, including whether it is in the commissioning state, whether it has occurred fault or protection action, and running mode switching condition; The grid side data includes: Public connection point impedance spectrum scanning result: the impedance at the public connection point between the new energy station and the grid is scanned in a wide frequency domain by using impedance measuring equipment or modeling simulation method to obtain the impedance amplitude and phase characteristics at different frequencies; Power flow data: the power flow data of the public connection point and the related lines of the grid are collected, including the power flow distribution of active power, reactive power, voltage and current; Voltage stability parameters: the fluctuation range of voltage amplitude, voltage change rate and voltage stability margin index are collected; The auxiliary data includes: Dispatching instruction record: the dispatching instructions issued by the grid to the new energy station are recorded, including power regulation instructions and running mode switching instructions; Environmental meteorological data: the environmental meteorological data of the area where the new energy station is located are collected, including wind speed, light intensity and temperature.

3. The method of claim 2, wherein the method further comprises: The S2, the preprocessing process comprises: Time synchronization, time stamp synchronization is carried out to all acquisition channels, re-sampling processing is carried out by using unified sampling frequency, for high-frequency voltage / current signal, noise removal is carried out by using band-pass filter; The working condition slicing mechanism based on event triggering is introduced, the instruction mutation, the device running mode switching and the wind speed jump are taken as the slicing boundaries, and the collected time sequence data is divided into multiple stable running segments; After the data slicing, structure normalization processing is carried out, the dimension and unit of different physical quantities are unified, the standard input data matrix is generated, and the historical data set is obtained.

4. The method of claim 2, wherein the method further comprises: In the S3, the frequency domain indicators include a minimum impedance margin, a phase margin, a gain margin, and a harmonic amplification factor, wherein the minimum impedance margin is represented as: ； wherein is the current frequency, j is the imaginary unit; is the frequency response of the plant-side equivalent impedance; is the frequency response of the grid-side equivalent impedance; min denotes taking the minimum value; Based on the common connection point impedance frequency spectrum scanning result, the Bode diagram is drawn, the source-grid impedance amplitude crossover frequency is found, the difference between the phase angle and 180° at the frequency is calculated as the phase margin, the phase crossover frequency is found, the difference between 1 and the impedance amplitude ratio at the frequency is calculated as the gain margin; The harmonic magnification factor HMF is defined as: ； In the formula, max represents taking the maximum value; The time domain indicators include a main frequency energy proportion and an oscillation duration. The main frequency energy proportion is defined as a proportion of signal energy in a dominant frequency band to total energy. defined as a proportion of signal energy in a dominant frequency band to total energy. ； wherein is the main frequency; is the band width; denotes the frequency domain amplitude obtained by short-time Fourier transformation of the high-frequency voltage or high-frequency current signal; denotes the energy spectral density of the signal at the current frequency f. An energy threshold is set, and the moment when the signal energy first exceeds the energy threshold is identified as the oscillation start moment , and the moment when the signal energy last falls below the energy threshold is identified as the oscillation end moment , and the oscillation duration is defined as: ； The statistical indexes include spectrum entropy and waveform distortion rate, wherein the spectrum entropy H is defined as: ； In the formula, i, z represent the index of the frequency component, The energy proportion probability of the i th frequency component; The signal energy on the i th frequency component is represented by The signal energy on the z th frequency component is represented by 5. The method of claim 1, wherein, In the S4.5, if the following conditions are met at the same time, it is determined that the power electronic device is only a response source, and is excluded: Load response time sequence: the power change of the rear load lags behind the front load, and the power change trend of the front load is consistent with the power change trend of the power electronic device; Device control parameter: the control strategy is passive following type, and the control parameter is in the normal range; Device state quantity: the device is in the normal operation and full-power stable operation state.

6. The method of claim 4, wherein the method further comprises: In the S5, the transfer function of the source-grid coupling is constructed, the stability margin calculation is carried out, and the process of judging the stable state of the coupling system is as follows: S5.1, the impedance relationship at the interface of the new energy station and the power grid is simplified as: ； wherein is the transfer function of the source-net coupling; S5.2, if Under certain frequency band and then the coupling system is at risk of instability, where arg denotes the argument of a complex number. S5.3, the stability margin calculation is carried out, the stability margin includes the phase margin, the gain margin and the harmonic magnification factor, when the HMF is greater than the set empirical threshold value, the coupling system has a stability threat; S5.4, based on and Plotting the Nyquist plot, the transfer function is observed The relative position of the trajectory to the -1+j0 point, if the trajectory encloses this point, the coupled system is threatened by stability.

7. The method of claim 4, wherein the method further comprises: In the S6, the oscillation risk level is divided into three categories: low risk, medium risk and high risk: High risk: both phase margin less than 10°, HMF greater than 0.9, less than 1.2, greater than 70%, H greater than 0.8, greater than 3 seconds; Medium risk: at least one of the following conditions is met, but not all: phase margin less than 10°, HMF greater than 0.9, less than 1.2, greater than 70%, H greater than 0.8, greater than 3 seconds. Low risk: None of the phase margin less than 10°, HMF greater than 0.9, less than 1.2, greater than 70%, H greater than 0.8, any of greater than 3 seconds.

8. The method of claim 7, wherein the method further comprises: In the S6, the oscillation risk atlas comprises: The main frequency evolution trajectory diagram shows the trend of the main frequency frequency change with time based on the frequency domain index; The frequency domain amplitude-phase margin curve diagram: based on the Bode diagram, the crossover point and the margin value are marked; The time domain oscillation waveform diagram: based on the high-frequency voltage or high-frequency current signal, and superimposes the oscillation starting / ending time; The device state and control response superposition diagram: based on the device control parameter and the device state quantity information, and superimposes the oscillation source positioning result, and shows the correlation between the power electronic device state change and the oscillation; The risk level spatial distribution diagram: the risk level of each power electronic device in the area where the new energy station is located is marked.

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