A power system wide frequency domain stability evaluation method considering new energy fluctuation

Abstract

The application discloses a kind of power system wideband stability evaluation method considering new energy fluctuation, it is related to electric power evaluation technical field, to solve the problem of insufficient accuracy of wideband potential oscillation risk identification under new energy fluctuation condition, by collecting new energy field station output power time sequence and suppression control record, the amount of intervention of suppression control is analyzed, and the suppression intervention intensity is generated by combining the change of new energy output, the intervention window of suppression is determined, the grid connection point voltage fluctuation signal is collected in the intervention window of suppression, according to the apparent suppression trend of suppression intervention intensity analysis voltage fluctuation, impedance frequency band track and damping change track are extracted, disturbance frequency band migration characteristics are generated, the semi-suppression residual level is evaluated in combination with apparent suppression trend, the duration of semi-suppression residual level is counted, and the residual level is recalibrated according to the duration, to generate wideband stability evaluation result, improve the wideband stability evaluation accuracy of new energy access power system.

Description

Technical Field

[0001] This invention relates to the field of power assessment technology, and more specifically, to a wideband stability assessment method for power systems that takes into account fluctuations in new energy sources. Background Technology

[0002] As the scale of new energy power generation continues to expand, large-scale new energy power plants are connected to the power system through power electronic conversion devices. Their output has obvious random fluctuation characteristics. At the same time, new energy power plants are usually equipped with control strategies such as power suppression and oscillation suppression to reduce the impact of new energy fluctuations on the stability of grid operation. In actual operation, suppression control cannot always completely eliminate the dynamic impact caused by new energy fluctuations.

[0003] The existing technology has the following shortcomings: Currently, existing technologies typically perform stability analysis based on the operating status data of renewable energy power plants or grid connection response characteristics. They lack a dynamic correlation evaluation mechanism for the intervention process of suppression control, making it difficult to distinguish between the stable recovery state after the control action completely eliminates the disturbance and the semi-suppressed state where the disturbance is controlled but still has residual effects. This results in insufficient accuracy in identifying potential oscillation risks in the wide frequency domain under renewable energy fluctuation conditions. Therefore, a wide frequency domain stability assessment method for power systems that considers renewable energy fluctuations is proposed. Summary of the Invention

[0004] To overcome the aforementioned deficiencies of the prior art, embodiments of the present invention provide a wideband stability assessment method for power systems that considers renewable energy fluctuations. This method addresses the problems mentioned in the background by employing correlation analysis between renewable energy output fluctuations and suppression control intervention states, voltage response stage identification based on suppression intervention strength, disturbance frequency band migration feature extraction, and semi-suppression residual level dynamic assessment techniques.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a broadband stability assessment method for power systems considering new energy fluctuations, comprising the following steps: Step S1: Read the power output time sequence and suppression control record of the new energy power station, analyze the suppression control intervention amount through the suppression control record, generate the suppression intervention intensity by combining the power output time sequence, and set the suppression intervention window; Step S2: Collect voltage fluctuation signals at the grid connection point within the suppression intervention window, analyze the apparent suppression trend after performing stage correlation on the voltage fluctuation signals based on the suppression intervention strength, and use the apparent suppression trend to determine whether the semi-suppression identification mechanism has been entered. Step S3: When entering the semi-suppression identification mechanism, extract the impedance frequency band trajectory and damping change trajectory within the suppression intervention window, integrate the impedance frequency band trajectory and damping change trajectory to generate disturbance frequency band migration features, and evaluate the semi-suppression residual level in combination with the apparent suppression trend. Step S4: Calculate the duration of the semi-suppression residual level within the suppression intervention window, and generate a wideband stable result by recalibrating the semi-suppression residual level based on the duration of the residual level.

[0006] In a preferred embodiment, in step S1, the power output time sequence refers to the active power sequence output by the new energy power station at continuous sampling time. Suppression control records refer to the records of the start-up time, stop-up time, and action amplitude of the suppression control unit on the new energy power station side when it performs suppression control actions on grid connection point voltage fluctuations, broadband oscillations, or impedance mismatch. The amount of inhibition control intervention is calculated based on the amplitude of movement recorded in the inhibition control log. Read the rated power of the new energy power station and calculate the power fluctuation at each sampling time by combining the output power time sequence; The suppression control intervention amount and the power mutation amount are input into the exponential compression function to generate the suppression intervention intensity.

[0007] In a preferred embodiment, in step S1, the inhibition control intervention amount is compared with a preset intervention threshold: If the amount of intervention to suppress control is greater than or equal to the preset intervention threshold, the corresponding sampling time is marked as the intervention start time, and the intervention start time is extended backward to the moment when the amount of intervention to suppress control is continuously lower than the preset intervention threshold to form an intervention suppression window; Conversely, it is determined that no intervention window has been formed.

[0008] In a preferred embodiment, in step S2, the voltage fluctuation signal refers to the sequence of deviations of the grid connection point voltage from the rated voltage; The voltage fluctuation envelope is extracted from the voltage fluctuation signal. The voltage fluctuation envelope is obtained by extracting the peak value of the voltage fluctuation signal within the suppression intervention window according to the sliding time window. The amplitude decrease coefficient at each sampling time is calculated using the voltage fluctuation envelope. Multiply the amplitude decrease coefficient corresponding to the sampling time by the suppression intervention intensity, and take the median of the multiplication result as the apparent suppression trend; Compare the apparent suppression tendency with the preset apparent threshold: When the apparent suppression trend is greater than or equal to the preset apparent threshold, it is determined that the voltage fluctuation has apparent suppression and enters the semi-suppression identification mechanism. Conversely, it does not enter the semi-suppression recognition mechanism.

[0009] In a preferred embodiment, in step S3, a test disturbance is injected into the grid connection point within the suppression intervention window, the voltage response signal and current response signal of the grid connection point are collected, the equivalent impedance amplitude-frequency curve of the grid connection point is generated according to the ratio of the voltage response signal and the current response signal at each frequency point, and the equivalent impedance amplitude-frequency curve of the grid connection point is segmented according to the sliding spectrum window. Within each sliding spectrum window, the magnitude of the equivalent impedance of the grid connection point corresponding to each frequency point is compared. The equivalent impedance of the grid connection point with the largest magnitude is taken as the peak value of the impedance magnitude, and the frequency where the peak value of the impedance magnitude is located is taken as the dominant peak frequency at the corresponding sampling time. Arrange the dominant peak frequencies corresponding to each sliding spectral window within the suppression intervention window in chronological order to obtain the impedance frequency band trajectory. The migration offset is calculated based on the dominant peak frequency in the impedance band trajectory.

[0010] In a preferred embodiment, in step S3, the voltage fluctuation signal and current fluctuation signal of the grid connection point are collected within the suppression intervention window, and the data is divided into multiple time window segments according to the same time step as the impedance frequency band trajectory. The spectrum of each time window data segment is decomposed, and the frequency components whose frequency falls into the preset wideband oscillation frequency band and whose amplitude is greater than the oscillation identification threshold are taken as oscillation components. The oscillation component with the largest oscillation amplitude is selected as the dominant oscillation mode, and the damping ratio is calculated based on the decay envelope of the dominant oscillation mode. The damping ratios corresponding to each time window data segment are arranged in chronological order to obtain the damping change trajectory. The migration characteristics of the disturbance frequency band are calculated by combining the damping ratio and migration offset in the combined damping change trajectory. The product of the perturbation band migration characteristics and the apparent suppression trend is used as the residual index.

[0011] In a preferred embodiment, in step S3, the residue index is compared with the residue classification threshold: When the residual index is less than the first residual threshold, the semi-suppressed residual level is marked as a low residual level. When the residual index is greater than or equal to the first residual threshold and less than the second residual threshold, the semi-suppressed residual level is calibrated as the medium residual level. When the residual index is greater than or equal to the second residual threshold, the semi-inhibited residual level is labeled as a high residual level.

[0012] In a preferred embodiment, in step S4, the residual duration refers to the cumulative duration of sampling time when the semi-suppressed residual level reaches the medium residual level or the high residual level; The residual duration is used to recalibrate the residual suppression hierarchy in half of the time. Specifically, the residual duration is compared with a duration threshold. When the duration of residual effect is less than the first duration threshold, the semi-suppressed residual effect level is maintained. When the duration of residual events is greater than or equal to the first duration threshold and less than the second duration threshold, the level of semi-suppressed residual events will be increased by one level. When the duration of the residual is greater than or equal to the second duration threshold, the level of semi-suppressed residual will be increased by two levels.

[0013] In a preferred embodiment, in step S4, a wideband stabilization result is generated based on the recalibrated semi-suppression residual level: Low residual level corresponds to low-risk stable results, medium residual level corresponds to medium-risk stable results, and high residual level corresponds to high-risk stable results; when the semi-suppressed residual level is increased to reach the high residual level, the wideband stable result output is a high-risk stable result.

[0014] The technical effects and advantages of this invention are as follows: This invention collects the power output time sequence and suppression control records of renewable energy power plants, analyzes the suppression control intervention quantity, and generates the suppression intervention strength by combining the renewable energy power output changes. It then determines the suppression intervention window, collects the voltage fluctuation signal at the grid connection point within the window, analyzes the apparent suppression trend of voltage fluctuations based on the suppression intervention strength, and determines whether a semi-suppression identification mechanism has been entered. If the semi-suppression identification mechanism has been entered, the impedance frequency band trajectory and damping change trajectory are extracted to generate disturbance frequency band migration characteristics. These characteristics are then combined with the apparent suppression trend to assess the semi-suppression residual level. The duration of the semi-suppression residual level is statistically analyzed, and the residual level is recalibrated based on the duration to generate a wideband stability assessment result. This enables accurate identification of potential wideband oscillation risks after suppression control of renewable energy power plants, improving the accuracy of wideband stability assessment for renewable energy access to the power system. Attached Figure Description

[0015] Figure 1 This is a flowchart illustrating the implementation of a broadband stability assessment method for power systems that considers new energy fluctuations, as per the present invention.

[0016] Figure 2 This is a schematic diagram illustrating the steps of a broadband stability assessment method for power systems that takes into account fluctuations in new energy sources, according to the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] This invention collects the power output time sequence and suppression control records of new energy power plants, analyzes the suppression control intervention amount, and generates the suppression intervention intensity based on the changes in new energy power output to determine the suppression intervention window. Within the suppression intervention window, it collects the voltage fluctuation signal at the grid connection point, analyzes the apparent suppression trend of voltage fluctuations based on the suppression intervention intensity, and determines whether it has entered the semi-suppression identification mechanism. After entering the semi-suppression identification mechanism, it extracts the impedance frequency band trajectory and damping change trajectory to generate disturbance frequency band migration characteristics. It evaluates the semi-suppression residual level based on the apparent suppression trend, counts the duration of the semi-suppression residual level, and recalibrates the residual level based on the duration to generate a wideband stability assessment result, thereby achieving accurate identification of potential wideband oscillation risks after suppression control of new energy power plants.

[0019] Example 1, such as Figures 1 to 2 As shown, a broadband stability assessment method for power systems considering new energy fluctuations includes the following steps: Step S1: Read the power output time sequence and suppression control record of the new energy power station, analyze the suppression control intervention amount through the suppression control record, generate the suppression intervention intensity by combining the power output time sequence, and set the suppression intervention window; Step S2: Collect voltage fluctuation signals at the grid connection point within the suppression intervention window, analyze the apparent suppression trend after performing stage correlation on the voltage fluctuation signals based on the suppression intervention strength, and use the apparent suppression trend to determine whether the semi-suppression identification mechanism has been entered. Step S3: When entering the semi-suppression identification mechanism, extract the impedance frequency band trajectory and damping change trajectory within the suppression intervention window, integrate the impedance frequency band trajectory and damping change trajectory to generate disturbance frequency band migration features, and evaluate the semi-suppression residual level in combination with the apparent suppression trend. Step S4: Calculate the duration of the semi-suppression residual level within the suppression intervention window, and generate a wideband stable result by recalibrating the semi-suppression residual level based on the duration of the residual level.

[0020] The specific implementation is as follows: In step S1, the power output time series refers to the active power sequence output by the new energy power station at continuous sampling time, which is used to reflect the rapid change process of new energy power output. The power output time series is derived by the power station monitoring system according to a fixed sampling period, and the power output is the active power measurement value of the grid-connected side of the new energy power station at the same sampling time.

[0021] It should be added that the power station monitoring system refers to the monitoring platform within a new energy power station used to collect, store, and manage operational data. In this example, it is used to provide output power timing, sampling time intervals, and operational data corresponding to the suppression control process.

[0022] The suppression control record is read by the grid-connected inverter control log. The suppression control record is used to characterize the actual control intervention process that the new energy power station puts in order to suppress voltage fluctuations, wideband oscillations or impedance mismatch. The suppression control record refers to the entry time, exit time and action magnitude of feedforward compensation, additional dynamic damping, impedance reshaping or other suppression control actions.

[0023] It should be added that the grid-connected inverter control log is a log of control parameter changes recorded by the grid-connected inverter during operation. In this example, it is used to supplement and determine the magnitude of the suppression control action.

[0024] The suppression control intervention amount is analyzed based on the suppression control records. The suppression control intervention amount refers to the change in the amplitude of various suppression control actions at the same sampling time, and is calculated in the following way: ; in, The suppression control intervention amount at the k-th sampling time. Let the amplitude of the j-th type of suppression control action be the amplitude at the k-th sampling time. This represents the upper limit of the allowable amplitude of the j-th type of suppression control action. Let be the weight of the j-th type of suppression control action.

[0025] The greater the change in suppression control action and the greater the amount of suppression control intervention, the stronger the response of the station controller, grid-connected inverter controller, and wide-frequency domain stability control device to new energy fluctuations. Among them, the station controller, grid-connected inverter controller, and wide-frequency domain stability control device are used for output feedforward compensation, additional dynamic damping, impedance reshaping, or other control actions related to voltage fluctuation suppression, respectively.

[0026] It should be noted that the amplitude of various suppression control actions is determined by the command value or actual execution feedback value of the corresponding control channel; the upper limit of the allowable amplitude is read from the controller parameter configuration table; the weight of various suppression control actions is determined through historical suppression control samples, specifically by statistically analyzing the contribution ratio of each suppression control action to the decrease in voltage fluctuation envelope, and normalizing the contribution ratio so that the sum of the weights of various suppression control actions is 1.

[0027] Calculate the power surge by analyzing the power output time series: ; in, Let be the power mutation amount at the k-th sampling time. The output power at the k-th sampling time is... Rated power for new energy power stations The sampling time interval, For the first The output power at each sampling moment.

[0028] The rated power of new energy power stations is obtained from the station's grid-connected capacity filing document or the station's equipment configuration table; the sampling time interval is determined by the sampling configuration record of the station's monitoring system and remains consistent within the same suppression intervention window.

[0029] The larger the power surge, the faster the output of new energy sources changes, and the easier it is to trigger wideband suppression control.

[0030] The suppression control intervention amount and the power mutation amount are input into the exponential compression function to generate the suppression intervention strength: ; in, Let α be the suppression intervention intensity at the k-th sampling time, and α be the control intervention weight. This is the calibration value for power mutation. The suppression control intervention amount at the k-th sampling time. This represents the power fluctuation at the k-th sampling time.

[0031] The greater the amount of intervention or the greater the power mutation, the closer the intensity of intervention is to 1, indicating that the intervention is more effective.

[0032] It should be noted that the control intervention weight is determined through historical operating data. Specifically, the contribution ratio of the suppression control intervention amount and the power mutation amount to the triggering criterion in the known suppression control triggering samples is statistically analyzed, and the median value of the contribution ratio is taken as the control intervention weight. The power mutation amount calibration value is determined by the upper quartile of the power mutation amount on the historical normal fluctuation days of the new energy power station.

[0033] Compare the amount of interventional control to a preset interventional threshold: If the amount of intervention to suppress control is greater than or equal to the preset intervention threshold, the corresponding sampling time is marked as the intervention start time, and the intervention start time is extended backward to the moment when the amount of intervention to suppress control is continuously lower than the preset intervention threshold to form an intervention suppression window; Conversely, if it is determined that no inhibition intervention window has been formed, the subsequent semi-inhibition judgment will not proceed.

[0034] The preset intervention threshold is determined by the upper limit of the suppression control intervention amount in the historical non-triggered control samples, and the statistical median of this upper limit is taken as the preset intervention threshold. The historical non-triggered control samples are data records corresponding to the non-triggered control event tags in the historical operation database of new energy power plants.

[0035] In step S2, the voltage fluctuation signal of the grid connection point is collected within the suppression intervention window by the synchronous phasor measurement device. The voltage fluctuation signal refers to the deviation sequence of the grid connection point voltage relative to the rated voltage, which is used to characterize the fluctuation of new energy and the change of the voltage amplitude of the grid connection point during the suppression control intervention.

[0036] It should be added that a synchronous phasor measurement device refers to a measurement device used to collect voltage and current phasors at the grid connection point according to a unified clock. In this example, it is used to provide grid connection point voltage fluctuation signals and grid connection point current fluctuation signals.

[0037] The voltage fluctuation envelope is extracted from the voltage fluctuation signal. The voltage fluctuation envelope is obtained by extracting the peak value of the voltage fluctuation signal within the suppression intervention window according to the sliding time window. Calculate the amplitude descent factor using the voltage fluctuation envelope: ; in, Let be the amplitude decrease coefficient at the k-th sampling time. To suppress voltage fluctuation envelope reference value before the start of the intervention window, The voltage fluctuation envelope is the voltage fluctuation envelope at the kth sampling time. The reference value of the voltage fluctuation envelope is determined by the median value of the voltage fluctuation envelope within the reference time window before the start of the suppression intervention window.

[0038] The length of the reference time window is 3 to 5 power frequency cycles before the start of the suppression intervention window. If the voltage fluctuation envelope reference value is lower than the minimum resolution of the voltage acquisition device, the minimum resolution is used as the voltage fluctuation envelope reference value for calculation. The larger the amplitude reduction coefficient, the more significant the reduction in voltage fluctuation amplitude at the grid connection point.

[0039] Based on the intensity of suppression intervention, a stage correlation is performed on the voltage fluctuation signal to generate an apparent suppression trend: ; Where B represents the apparent suppression trend, W represents the set of sampling times within the suppression intervention window, and median indicates taking the median. Let be the amplitude decrease coefficient at the k-th sampling time. Let be the suppression intervention intensity at the k-th sampling time.

[0040] The greater the intensity of the intervention and the greater the amplitude reduction coefficient, the greater the apparent suppression trend, indicating that voltage fluctuations exhibit a more obvious surface suppression phenomenon during intervention.

[0041] Compare the apparent suppression tendency with the preset apparent threshold: When the apparent suppression trend is greater than or equal to the preset apparent threshold, it is determined that the voltage fluctuation has apparent suppression and enters the semi-suppression identification mechanism. When the apparent suppression trend is less than the preset apparent threshold, it is determined that the voltage fluctuation has not shown apparent suppression, and it does not enter the semi-suppression identification mechanism. The wide frequency domain stability result is then labeled as a normal fluctuation state.

[0042] The preset apparent threshold is determined through historically known effective suppression samples. Specifically, it is the lower limit of the apparent suppression trend of samples showing a stable decrease in the voltage fluctuation envelope after the implementation of statistical suppression control, and this lower limit is taken as the preset apparent threshold. Historically known effective suppression samples are data records corresponding to the suppression effective event tags in the historical operation database of new energy power plants.

[0043] In step S3, when entering the semi-suppression identification mechanism, the impedance frequency band trajectory and damping change trajectory within the suppression intervention window are extracted; Among them, the impedance frequency band trajectory refers to the data sequence formed by recording the changes in the peak frequency band position of the equivalent impedance amplitude-frequency curve of the grid connection point in the order of continuous sampling time within the suppression intervention window, reflecting the transfer of disturbance energy between different frequency bands; the damping change trajectory refers to the data sequence formed by recording the changes in the damping ratio of the dominant oscillation mode of the grid connection point in the order of continuous sampling time within the suppression intervention window, reflecting the changes in the system's ability to attenuate oscillation disturbances during the suppression control intervention process; The disturbance injection identification device injects a test disturbance with an amplitude lower than the upper limit of the grid voltage allowable disturbance into the grid connection point within the suppression intervention window. It acquires the voltage response signal through the grid connection point voltage acquisition channel and the current response signal through the grid connection point current acquisition channel. Based on the ratio of the voltage response signal and the current response signal at each frequency point, the amplitude-frequency curve of the equivalent impedance of the grid connection point is obtained. The amplitude-frequency curve of the equivalent impedance of the grid connection point is segmented according to the sliding spectrum window. Within each sliding spectrum window, the amplitude of the equivalent impedance of the grid connection point corresponding to each frequency point is compared. The equivalent impedance of the grid connection point with the largest amplitude is taken as the peak value of the impedance amplitude, and the frequency where the peak value of the impedance amplitude is located is taken as the dominant peak frequency at the corresponding sampling time. Arrange the dominant peak frequencies corresponding to each sliding spectral window within the suppression intervention window in chronological order to obtain the impedance frequency band trajectory. It should be added that the disturbance injection identification device refers to the identification equipment used to inject a small test disturbance into the grid connection point and collect the disturbance response under the condition that it does not affect the normal grid connection operation of the new energy power station. In this example, it is used to generate the equivalent impedance amplitude-frequency curve of the grid connection point. The grid connection point voltage acquisition channel is a data acquisition channel connected to the grid connection point voltage transformer or broadband voltage sensor, used to collect the voltage response signal generated by the grid connection point after the test disturbance injection. The grid connection point current acquisition channel is a data acquisition channel connected to the grid connection point current transformer or broadband current sensor, used to collect the current response signal generated by the grid connection point after the test disturbance injection.

[0044] Calculate the migration offset based on the impedance frequency band trajectory: ; in, Let $\mathbf{k}$ be the migration offset at the $k$-th sampling time. Let be the dominant peak frequency of the impedance band trajectory at the k-th sampling time. To suppress the dominant peak frequency before the intervention window begins, This refers to the reference frequency bandwidth.

[0045] The dominant peak frequency before the start of the suppression intervention window is determined by the median value of the dominant peak frequencies within the reference time window; the reference bandwidth is determined by the interquartile range of the dominant peak frequencies within the reference time window. If the interquartile range is lower than the spectral resolution, the spectral resolution is used as the reference bandwidth. The greater the deviation of the dominant peak frequency, the greater the migration offset, indicating a more significant transfer of disturbance energy from the original frequency band to other frequency bands.

[0046] Within the suppression intervention window, voltage fluctuation signals are acquired through the grid connection point voltage acquisition channel, and current fluctuation signals are acquired through the grid connection point current acquisition channel. A sliding time window is set with the same time step as the impedance frequency band trajectory, and the voltage fluctuation signals and current fluctuation signals are divided into multiple time window data segments according to the sliding time window. Spectral decomposition is performed on each time window data segment to obtain multiple oscillation components within the time window data segment, as well as the oscillation amplitude and oscillation frequency corresponding to each oscillation component. Frequency components whose frequencies fall within the preset wideband oscillation frequency band and whose amplitudes are greater than the oscillation identification threshold are taken as oscillation components. It should be explained that the preset wideband oscillation frequency band is jointly determined by the grid connection specifications of new energy power plants and the frequency range corresponding to historical wideband oscillation events. It is used to limit the frequency components that participate in the oscillation component screening after spectrum decomposition. The oscillation identification threshold is determined by the historical normal operation samples of new energy power plants. Specifically, it is to statistically analyze the upper limit of the amplitude of each frequency component in the preset wideband oscillation frequency band in the historical normal operation samples, and use this upper limit as the oscillation identification threshold. The oscillation component with the largest amplitude within the corresponding time window data segment is identified as the dominant oscillation mode; the adjacent peak amplitudes of the dominant oscillation mode are extracted; and the damping ratio corresponding to the dominant oscillation mode is calculated based on the decay envelope of the dominant oscillation mode within the corresponding time window data segment. ; in, The damping ratio corresponding to the k-th time window data segment. This represents the first peak amplitude of the dominant oscillation mode within the k-th time window data segment. It represents the second peak amplitude of the dominant oscillation mode within the k-th time window data segment.

[0047] The closer the ratio of the first peak amplitude to the second peak amplitude is to 1, the smaller the damping ratio, indicating that the oscillation decays more slowly; the larger the ratio of the first peak amplitude to the second peak amplitude, the larger the damping ratio, indicating that the oscillation decays more quickly. Arrange the damping ratios corresponding to each time window data segment within the suppression intervention window in chronological order to obtain the damping change trajectory; Calculate the damping attenuation based on the damping change trajectory: ; in, Let be the damping attenuation at the k-th sampling time. To suppress the damping ratio before the intervention window begins, Let be the damping ratio at the k-th sampling time.

[0048] The damping ratio before the start of the intervention window is determined by the median value of the damping ratio within the reference time window; if the damping ratio before the start of the intervention window is lower than the minimum effective value of the damping ratio, then the minimum effective value of the damping ratio is used as the damping ratio in the calculation of damping attenuation.

[0049] The lower the damping ratio, the greater the damping attenuation, indicating that the system has a weaker ability to dissipate disturbances.

[0050] Integrating migration offset and damping attenuation, the perturbation band migration characteristics are generated: ; in, The perturbation frequency band migration characteristics at the k-th sampling time. Let $\mathbf{k}$ be the migration offset at the $k$-th sampling time. This represents the damping attenuation at the k-th sampling time.

[0051] An increase in either the migration offset or the damping attenuation will increase the disturbance frequency band migration characteristics, indicating that the system has a risk of residual disturbance caused by frequency band migration or damping reduction.

[0052] The residual index is calculated by combining the perturbation band migration characteristics with the apparent suppression trend. ; in, Let B be the residual index at the k-th sampling time, and let B be the apparent suppression trend.

[0053] The greater the apparent suppression trend and the greater the frequency band migration characteristics, the larger the residual index, indicating that although the voltage amplitude at the grid connection point decreases, there is still a risk of migration of disturbances within the wide frequency domain.

[0054] Compare the residue index with the residue grading threshold: When the residual index is less than the first residual threshold, the semi-suppressed residual level is marked as a low residual level. When the residual index is greater than or equal to the first residual threshold and less than the second residual threshold, the semi-suppressed residual level is calibrated as the medium residual level. When the residual index is greater than or equal to the second residual threshold, the semi-inhibited residual level is labeled as a high residual level.

[0055] The first and second residual thresholds were determined using historical semi-suppression samples. Specifically, this involved statistically analyzing the residual index distribution intervals of non-migrating, slightly migrating, and continuously migrating samples within known disturbance frequency bands, and using the boundary value between adjacent distribution intervals as the residual classification threshold. Historical semi-suppression samples were derived from data records corresponding to semi-suppression event tags in the historical operation database of new energy power plants.

[0056] In step S4, the residual duration of the semi-suppressed residual layer within the suppression intervention window is calculated. The residual duration refers to the cumulative duration of the sampling time when the semi-suppressed residual layer reaches the medium or high residual layer. The calculation formula is as follows:

[0057] in, Duration of residue To reduce the number of sampling points within the intervention window that reach the intermediate or high residual level of the semi-suppression residual layer, The sampling time interval is denoted by . The longer the residual duration, the longer the semi-suppressed state persists, and the less suitable it is to directly down-adjust the broadband stability risk.

[0058] The residual duration is used to recalibrate the residual suppression hierarchy in half of the time. Specifically, the residual duration is compared with a duration threshold. When the duration of residual effect is less than the first duration threshold, the semi-suppressed residual effect level is maintained. When the duration of residual events is greater than or equal to the first duration threshold and less than the second duration threshold, the level of semi-suppressed residual events will be increased by one level. When the duration of the residual is greater than or equal to the second duration threshold, the level of semi-suppressed residual will be increased by two levels.

[0059] The first and second persistence thresholds were determined using historical disturbance recovery samples from renewable energy power plants. Specifically, they were the time required for the disturbance frequency band migration characteristics to recover to below the first residual threshold after statistical suppression control intervention. The median of this duration distribution was taken as the first persistence threshold, and the upper quartile of this duration distribution was taken as the second persistence threshold. The historical disturbance recovery samples were obtained from the data records corresponding to the disturbance recovery event tags in the historical operation database of renewable energy power plants.

[0060] Broadband stability results were generated based on the recalibrated semi-suppressed residual hierarchy: Low residual level corresponds to low-risk stable results, medium residual level corresponds to medium-risk stable results, and high residual level corresponds to high-risk stable results; when the semi-suppressed residual level is increased to reach the high residual level, the wideband stable result output is a high-risk stable result.

[0061] Wideband stability results are used to reflect whether there are still wideband stability risks caused by disturbance frequency band migration and damping attenuation after the intervention of suppression control at the new energy power station. Low-risk stability results indicate that voltage fluctuations have been effectively suppressed and residual disturbances are not persistent. Medium-risk stability results indicate that there are certain residual disturbances and continuous monitoring is required. High-risk stability results indicate that although voltage fluctuations have shown an apparent decrease, disturbances have undergone frequency band migration or damping attenuation and persist, requiring further stability control or alarms to be triggered.

[0062] It should be noted that the historical operation database of new energy power plants refers to a data set that uniformly stores output power, grid connection point voltage, grid connection point current, controller action records, impedance identification data, and damping identification data according to the sampling time. Each historical sample is classified according to event tags before being entered into the database. Event tags include no-triggered control, effective suppression, partial suppression, and disturbance recovery, which are used to provide statistical sources for preset intervention thresholds, preset apparent thresholds, residual classification thresholds, and duration thresholds.

[0063] Through the above processing, after the rapid change in the output of new energy triggers the intervention of suppression control, not only is the apparent suppression judged based on the voltage fluctuation amplitude at the grid connection point, but also the characteristics of the disturbance frequency band migration are identified by combining the impedance frequency band trajectory and the damping change trajectory. The residual duration is used to recalibrate the semi-suppression residual level, thereby avoiding the output of a low-risk conclusion simply because the voltage fluctuation amplitude has decreased.

[0064] Finally, it should be noted that in this paper, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0065] Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, as well as elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0066] In this document, the singular forms “a,” “an,” and “the” may also include the plural forms unless the context clearly indicates otherwise. It should also be understood that terms such as “comprising / including” or “having” specify the presence of the stated features, integrals, steps, operations, components, parts, or combinations thereof, but do not preclude the possibility of the presence or addition of one or more other features, integrals, steps, operations, components, parts, or combinations thereof. Meanwhile, the term “and / or” as used in this specification includes any and all combinations of the associated listed items.

[0067] The various embodiments in this specification are described in a progressive manner. Each embodiment focuses on the differences from other embodiments. The various embodiments can be combined as needed, and the same or similar parts can be referred to each other.

[0068] The above description of the disclosed embodiments will enable those skilled in the art to make or use various modifications to these embodiments. It will be readily apparent to those skilled in the art that the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A broadband stability assessment method for power systems considering renewable energy fluctuations, characterized in that: Includes the following steps: Step S1: Read the power output time sequence and suppression control record of the new energy power station, analyze the suppression control intervention amount through the suppression control record, generate the suppression intervention intensity by combining the power output time sequence, and set the suppression intervention window; Step S2: Collect voltage fluctuation signals at the grid connection point within the suppression intervention window, analyze the apparent suppression trend after performing stage correlation on the voltage fluctuation signals based on the suppression intervention strength, and use the apparent suppression trend to determine whether the semi-suppression identification mechanism has been entered. Step S3: When entering the semi-suppression identification mechanism, extract the impedance frequency band trajectory and damping change trajectory within the suppression intervention window, integrate the impedance frequency band trajectory and damping change trajectory to generate disturbance frequency band migration features, and evaluate the semi-suppression residual level in combination with the apparent suppression trend. Step S4: Calculate the duration of the semi-suppression residual level within the suppression intervention window, and generate a wideband stable result by recalibrating the semi-suppression residual level based on the duration of the residual level.

2. The method for evaluating the broadband stability of a power system considering new energy fluctuations according to claim 1, characterized in that: In step S1, the output power time sequence refers to the active power sequence output by the new energy power station at continuous sampling time. Suppression control records refer to the records of the start-up time, stop-up time, and action amplitude of the suppression control unit on the new energy power station side when it performs suppression control actions on grid connection point voltage fluctuations, broadband oscillations, or impedance mismatch. The amount of inhibition control intervention is calculated based on the amplitude of movement recorded in the inhibition control log. Read the rated power of the new energy power station and calculate the power fluctuation at each sampling time by combining the output power time sequence; The suppression control intervention amount and the power mutation amount are input into the exponential compression function to generate the suppression intervention intensity.

3. The method for evaluating the broadband stability of a power system considering new energy fluctuations according to claim 2, characterized in that: In step S1, the inhibition control intervention amount is compared with a preset intervention threshold: If the amount of intervention to suppress control is greater than or equal to the preset intervention threshold, the corresponding sampling time is marked as the intervention start time, and the intervention start time is extended backward to the moment when the amount of intervention to suppress control is continuously lower than the preset intervention threshold to form an intervention suppression window; Conversely, it is determined that no intervention window has been formed.

4. The method for evaluating the broadband stability of a power system considering new energy fluctuations according to claim 1, characterized in that: In step S2, the voltage fluctuation signal refers to the sequence of deviations of the grid connection point voltage from the rated voltage; The voltage fluctuation envelope is extracted from the voltage fluctuation signal. The voltage fluctuation envelope is obtained by extracting the peak value of the voltage fluctuation signal within the suppression intervention window according to the sliding time window. The amplitude decrease coefficient at each sampling time is calculated using the voltage fluctuation envelope. Multiply the amplitude decrease coefficient corresponding to the sampling time by the suppression intervention intensity, and take the median of the multiplication result as the apparent suppression trend; Compare the apparent suppression tendency with the preset apparent threshold: When the apparent suppression trend is greater than or equal to the preset apparent threshold, it is determined that the voltage fluctuation has apparent suppression and enters the semi-suppression identification mechanism. Conversely, it does not enter the semi-suppression recognition mechanism.

5. The method for evaluating the broadband stability of a power system considering new energy fluctuations according to claim 1, characterized in that: In step S3, a test disturbance is injected into the grid connection point within the suppression intervention window, and the voltage response signal and current response signal of the grid connection point are collected. The equivalent impedance amplitude-frequency curve of the grid connection point is generated according to the ratio of the voltage response signal and the current response signal at each frequency point. The equivalent impedance amplitude-frequency curve of the grid connection point is segmented according to the sliding spectrum window. Within each sliding spectrum window, the magnitude of the equivalent impedance of the grid connection point corresponding to each frequency point is compared. The equivalent impedance of the grid connection point with the largest magnitude is taken as the peak value of the impedance magnitude, and the frequency where the peak value of the impedance magnitude is located is taken as the dominant peak frequency at the corresponding sampling time. Arrange the dominant peak frequencies corresponding to each sliding spectral window within the suppression intervention window in chronological order to obtain the impedance frequency band trajectory. The migration offset is calculated based on the dominant peak frequency in the impedance band trajectory.

6. The method for evaluating the broadband stability of a power system considering new energy fluctuations according to claim 5, characterized in that: In step S3, voltage fluctuation signals and current fluctuation signals of the grid connection point are collected within the suppression intervention window. The data is divided into multiple time window segments according to the same time step as the impedance frequency band trajectory. Spectral decomposition is performed on each time window data segment, and frequency components whose frequencies fall into the preset wideband oscillation frequency band and whose amplitudes are greater than the oscillation identification threshold are taken as oscillation components. The oscillation component with the largest oscillation amplitude is selected as the dominant oscillation mode, and the damping ratio is calculated based on the decay envelope of the dominant oscillation mode. The damping ratios corresponding to each time window data segment are arranged in chronological order to obtain the damping change trajectory. The migration characteristics of the disturbance frequency band are calculated by combining the damping ratio and migration offset in the combined damping change trajectory. The product of the perturbation band migration characteristics and the apparent suppression trend is used as the residual index.

7. The method for evaluating the broadband stability of a power system considering new energy fluctuations according to claim 6, characterized in that: In step S3, the residue index is compared with the residue classification threshold: When the residual index is less than the first residual threshold, the semi-suppressed residual level is marked as a low residual level. When the residual index is greater than or equal to the first residual threshold and less than the second residual threshold, the semi-suppressed residual level is calibrated as the medium residual level. When the residual index is greater than or equal to the second residual threshold, the semi-inhibited residual level is labeled as a high residual level.

8. The method for evaluating the broadband stability of a power system considering new energy fluctuations according to claim 7, characterized in that: In step S4, the residual duration refers to the cumulative duration of sampling time when the semi-suppressed residual level reaches the medium residual level or the high residual level; The residual duration is used to recalibrate the residual suppression hierarchy in half of the time. Specifically, the residual duration is compared with a duration threshold. When the duration of residual events is less than the first duration threshold, the semi-suppressed residual level is maintained. When the duration of residual events is greater than or equal to the first duration threshold and less than the second duration threshold, the level of semi-suppressed residual events will be increased by one level. When the duration of the residual is greater than or equal to the second duration threshold, the level of semi-suppressed residual will be increased by two levels.

9. The method for evaluating the broadband stability of a power system considering new energy fluctuations according to claim 8, characterized in that: In step S4, a wideband stabilization result is generated based on the recalibrated semi-suppression residual level: Low residue levels correspond to low-risk stable outcomes, medium residue levels correspond to medium-risk stable outcomes, and high residue levels correspond to high-risk stable outcomes. When the semi-suppression residual level is increased to reach a high residual level, the wideband stabilization result output is a high-risk stabilization result.

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