Broadband power grid oscillation monitoring and alarm methods, systems, equipment and storage media

Abstract

This invention belongs to the field of power automation and discloses a method, system, device, and storage medium for monitoring and alarming broadband oscillations in power grids. It includes acquiring the oscillation monitoring type and oscillation monitoring data from oscillation monitoring points; and obtaining oscillation monitoring alarm results based on the oscillation monitoring data using the oscillation monitoring judgment method corresponding to the oscillation monitoring type. Different oscillation monitoring judgment methods are used for different oscillation monitoring types. For ultra-low frequency or low frequency oscillations, a combination of time-domain analysis, FFT algorithm, and Prony algorithm is used; for subsynchronous oscillations, a combination of time-domain analysis and FFT algorithm is used; and for sub / supersynchronous or medium-high frequency oscillations, a master-slave combined oscillation monitoring judgment method is used. This effectively solves the problem of misanalysis caused by frequency aliasing in data window selection and data analysis resampling using the pure Prony algorithm, and improves alarm efficiency by enhancing the effectiveness of the Prony algorithm calculation.

Description

Technical Field

[0001] This invention belongs to the field of power automation and relates to a method, system, device and storage medium for monitoring and alarming broadband oscillations in power grids. Background Technology

[0002] With the rapid development of new energy sources and the construction of ultra-high voltage AC / DC transmission projects, power electronic equipment is widely used in the power grid. Currently, the power grid exhibits the dual characteristics of a high proportion of new energy sources and a high proportion of power electronic equipment. Unlike traditional synchronous generators, power electronic equipment achieves energy conversion and grid connection through rapid switching and multi-time-scale control. Moreover, because different types of power electronic equipment have different control modes, their interaction with the power grid injects a large amount of non-power frequency electrical quantities into the grid, which may trigger new broadband oscillations in the sub- / super-synchronous to mid-to-high frequency ranges, causing multiple oscillation accidents.

[0003] For monitoring broadband oscillations, existing broadband measurement devices are compatible with the WAMS (Wide Area Measurement System) functional architecture and channels, enabling unified real-time measurement of the fundamental, interharmonic, and harmonic waves of the power grid, as well as the oscillation power components, within a 2500Hz range. Data is transmitted to the master station using time-division multiplexing. The master station's WAMS receives the data and initiates broadband oscillation monitoring and alarm functions. Broadband oscillations are mainly categorized by frequency band into ultra-low frequency (0.02–0.1Hz), low-frequency oscillations (0.1–2.5Hz), sub- / supersynchronous oscillations (2.5–100Hz), and mid-to-high frequency oscillations (100–2500Hz). However, differences in implementation among manufacturers lead to inconsistent oscillation monitoring results.

[0004] Currently, broadband oscillation monitoring is mostly based on power grid components, categorized into transformers, lines, and generators. An alarm is issued when the oscillation amplitude exceeds a set value and meets the duration requirement. The alarms used in the main station application currently employ fixed thresholds or simply set different thresholds according to voltage levels. In terms of algorithms, the Prony algorithm is the primary approach. The Prony algorithm is a method that uses a linear combination of exponential terms to fit equally spaced sampled data. However, in practical applications, problems such as insufficient performance, computation timeouts, and data anomalies often occur. Although the Prony algorithm, with its exponential signal model, is more suitable for oscillation monitoring, the need for downsampling the original signal during calculation leads to unavoidable frequency aliasing and a long computation time. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method, system, device and storage medium for monitoring and alarming broadband oscillations in power grids.

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

[0007] In a first aspect, this invention provides a broadband oscillation monitoring and alarm method for power grids, comprising: acquiring the oscillation monitoring type and oscillation monitoring data of oscillation monitoring points; obtaining an oscillation monitoring alarm result based on the oscillation monitoring data and using an oscillation monitoring judgment method corresponding to the oscillation monitoring type; wherein, when the oscillation monitoring type is ultra-low frequency oscillation or low frequency oscillation, the oscillation monitoring judgment method is: determining whether the fluctuation of the oscillation monitoring data exceeds a set dead zone based on a time-domain analysis method; and when the fluctuation of the oscillation monitoring data exceeds the set dead zone, determining whether the oscillation monitoring data belongs to the frequency band range of the current monitored oscillation type based on an FFT algorithm; and when the oscillation monitoring data belongs to the frequency band range of the current monitored oscillation type, obtaining an oscillation monitoring alarm result based on a Prony algorithm; when the oscillation monitoring type is subsynchronous oscillation, the oscillation monitoring judgment method is: determining whether the fluctuation of the oscillation monitoring data exceeds a set dead zone based on a time-domain analysis method; and when the fluctuation of the oscillation monitoring data exceeds the set dead zone, obtaining an oscillation monitoring alarm result based on an FFT algorithm; when the oscillation monitoring type is sub / supersynchronous oscillation or medium-high frequency oscillation, the oscillation monitoring judgment method is: an oscillation monitoring judgment method based on a master-slave station combination.

[0008] Optionally, when acquiring the oscillation monitoring type and oscillation monitoring data, when the oscillation monitoring type is ultra-low frequency oscillation, low frequency oscillation, or subsynchronous oscillation, the oscillation monitoring data is active power data; when the oscillation monitoring type is sub / supersynchronous oscillation or medium-high frequency oscillation, the oscillation monitoring data is the instantaneous oscillation power component or interharmonic current data transmitted by the substation; wherein, all oscillation monitoring points perform oscillation monitoring alarms for ultra-low frequency oscillation, low frequency oscillation, and subsynchronous oscillation, and broadband oscillation monitoring points perform oscillation monitoring alarms for sub / supersynchronous oscillation and medium-high frequency oscillation.

[0009] Optionally, the step of determining whether the fluctuation of the oscillation monitoring data exceeds the set dead zone based on the time-domain analysis method includes: obtaining the current time window data according to the oscillation monitoring type and the oscillation monitoring data, and obtaining the difference between the maximum value and the minimum value of the oscillation monitoring data in the current time window data; when the difference between the maximum value and the minimum value of the oscillation monitoring data exceeds the set dead zone, the fluctuation of the oscillation monitoring data exceeds the set dead zone; when the difference between the maximum value and the minimum value of the oscillation monitoring data does not exceed the set dead zone, the fluctuation of the oscillation monitoring data does not exceed the set dead zone, and the process returns to perform oscillation monitoring judgment for the next time window data.

[0010] Optionally, the step of determining whether the oscillation monitoring data belongs to the frequency band range of the current monitored oscillation type based on the FFT algorithm includes: obtaining the earlier of the time of the maximum value and the time of the minimum value of the oscillation monitoring data in the current time window data to obtain the start time; obtaining the data after the start time in the current time window data to obtain the data to be analyzed; and performing spectrum analysis on the data to be analyzed using the FFT algorithm to obtain the frequency corresponding to the maximum amplitude of the data to be analyzed, and determining whether the frequency corresponding to the maximum amplitude belongs to the frequency band range of the current monitored oscillation type; when the frequency corresponding to the maximum amplitude belongs to the frequency band range of the current monitored oscillation type, the oscillation monitoring data belongs to the frequency band range of the current monitored oscillation type; when the frequency corresponding to the maximum amplitude does not belong to the frequency band range of the current monitored oscillation type, the oscillation monitoring data does not belong to the frequency band range of the current monitored oscillation type, and returning to perform oscillation monitoring judgment for the next time window data.

[0011] Optionally, the oscillation alarm judgment based on the Prony algorithm to obtain the oscillation monitoring alarm result includes: analyzing the current time window data based on the Prony algorithm to obtain the dominant component amplitude and dominant component frequency of the current time window data; and updating the dominant component amplitude to the difference between the maximum and minimum values ​​of the oscillation monitoring data when the dominant component amplitude is greater than the difference between the maximum and minimum values ​​of the oscillation monitoring data; continuously acquiring the dominant component amplitude of a preset number of time window data and taking the average value to obtain the oscillation monitoring value; wherein, when continuously acquiring the dominant component amplitude of a preset number of time window data, if the current dominant component amplitude is less than half of the preset oscillation amplitude threshold of the oscillation monitoring point, returning to perform oscillation monitoring judgment on the next time window data; the preset number W num We obtain it from the following formula:

[0012]

[0013] Where N is the number of duration cycles obtained from the preset oscillation time threshold of the oscillation monitoring point, and f osc T represents the dominant component frequency of the data in the current time window. slid The time window length for the time window data.

[0014] When the oscillation monitoring value exceeds the preset oscillation amplitude threshold of the oscillation monitoring point, the oscillation monitoring alarm result is to issue an oscillation alarm, and the start time of the oscillation is the current time minus [the value of the oscillation value].

[0015] The oscillation alarm judgment based on the FFT algorithm to obtain the oscillation monitoring alarm result includes: analyzing the current time window data based on the FFT algorithm to obtain the dominant component amplitude and dominant component frequency of the current time window data; and updating the dominant component amplitude to the difference between the maximum and minimum values ​​of the oscillation monitoring data when the dominant component amplitude is greater than the difference between the maximum and minimum values ​​of the oscillation monitoring data; continuously acquiring the dominant component amplitude of a preset number of time window data and taking the average value to obtain the oscillation monitoring value; wherein, when continuously acquiring the dominant component amplitude of a preset number of time window data, if the current dominant component amplitude is less than half of the preset oscillation amplitude threshold of the oscillation monitoring point, returning to perform oscillation monitoring judgment on the next time window data; the preset number W num We obtain it from the following formula:

[0016]

[0017] Where N is the number of duration cycles obtained from the preset oscillation time threshold of the oscillation monitoring point, and f osc T represents the dominant component frequency of the data in the current time window. slid The time window length for the time window data.

[0018] When the oscillation monitoring value exceeds the preset oscillation amplitude threshold of the oscillation monitoring point, the oscillation monitoring alarm result is to issue an oscillation alarm, and the start time of the oscillation is the current time minus [the value of the oscillation value]. The preset oscillation time threshold and oscillation amplitude threshold for the oscillation monitoring point are set according to the voltage level and oscillation monitoring type.

[0019] Optionally, when the difference between the maximum and minimum values ​​of the oscillation monitoring data exceeds the set dead zone, the first marker value of the oscillation monitoring point is 1; when the difference between the maximum and minimum values ​​of the oscillation monitoring data does not exceed the set dead zone, the first marker value of the oscillation monitoring point is 0; when the frequency corresponding to the maximum amplitude value is within the frequency band range of the current monitored oscillation type, the second marker value of the oscillation monitoring point is 1; when the frequency corresponding to the maximum amplitude value is not within the frequency band range of the current monitored oscillation type, the second marker value of the oscillation monitoring point is 0; when the amplitude of the dominant component is greater than the difference between the maximum and minimum values ​​of the oscillation monitoring data, the third marker value of the oscillation monitoring point is 1; when the first marker value and the third marker value of the oscillation monitoring point are both 1, when performing oscillation monitoring judgment on the time window data, if the fluctuation of the oscillation monitoring data exceeds the set dead zone, the oscillation alarm judgment is directly performed based on the Prony algorithm to obtain the oscillation monitoring alarm result; wherein, when continuously acquiring the dominant component amplitude of a preset number of time window data, if the current dominant component amplitude is less than half of the preset oscillation amplitude threshold of the oscillation monitoring point, the first marker value, the first marker value, and the third marker value of the oscillation monitoring point are all 0.

[0020] Optionally, when obtaining the current time window data based on the oscillation monitoring type and oscillation monitoring data: when the oscillation monitoring type is an ultra-low frequency oscillation of 0.02–0.1 Hz, the time window length of the time window data is set to 100 s, and the time window overlap length is 50 s; when the oscillation monitoring type is a low frequency oscillation of 0.1–0.5 Hz, the time window length of the time window data is set to 20 s, and the time window overlap length is 10 s; when the oscillation monitoring type is a low frequency oscillation of 0.5–2.5 Hz, the time window length of the time window data is set to 10 s, and the time window overlap length is 5 s; when the oscillation monitoring type is a subsynchronous oscillation of 2.5–25 Hz, the time window length of the time window data is set to 10 s, and the time window overlap length is 2 s; when the oscillation monitoring type is a subsynchronous / supersynchronous oscillation or a medium-to-high frequency oscillation, the time window length of the time window data is set to 2 s, and the time window overlap length is 0 s.

[0021] In a second aspect, the present invention provides a broadband power grid oscillation monitoring and alarm system, comprising: a data acquisition module for acquiring the oscillation monitoring type and oscillation monitoring data of oscillation monitoring points; and an oscillation monitoring module for obtaining an oscillation monitoring alarm result based on the oscillation monitoring data and an oscillation monitoring judgment method corresponding to the oscillation monitoring type; wherein, when the oscillation monitoring type is ultra-low frequency oscillation or low frequency oscillation, the oscillation monitoring judgment method is: determining whether the fluctuation of the oscillation monitoring data exceeds a set dead zone based on a time-domain analysis method; and when the fluctuation of the oscillation monitoring data exceeds the set dead zone, determining whether the oscillation monitoring data belongs to the currently monitored oscillation based on an FFT algorithm. Within the frequency band of the oscillation type; and when the oscillation monitoring data belongs to the frequency band of the current monitored oscillation type, the oscillation alarm judgment is based on the Prony algorithm to obtain the oscillation monitoring alarm result; when the oscillation monitoring type is subsynchronous oscillation, the oscillation monitoring judgment method is: based on the time domain analysis method to determine whether the fluctuation of the oscillation monitoring data exceeds the set dead zone; and when the fluctuation of the oscillation monitoring data exceeds the set dead zone, the oscillation alarm judgment is based on the FFT algorithm to obtain the oscillation monitoring alarm result; when the oscillation monitoring type is sub / supersynchronous oscillation or medium-high frequency oscillation, the oscillation monitoring judgment method is: based on the oscillation monitoring alarm method of master and slave stations.

[0022] In a third aspect, the present invention provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described power grid broadband oscillation monitoring and alarm method.

[0023] In a fourth aspect, the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the above-described power grid broadband oscillation monitoring and alarm method.

[0024] Compared with the prior art, the present invention has the following beneficial effects:

[0025] This invention provides a broadband power grid oscillation monitoring and alarm method that employs different oscillation monitoring and judgment methods for different oscillation monitoring types. Specifically, for ultra-low frequency or low frequency oscillations, a method combining time-domain analysis, FFT algorithm, and Prony algorithm is used; for subsynchronous oscillations, a method combining time-domain analysis and FFT algorithm is used; and for sub / supersynchronous or medium-high frequency oscillations, a method based on master-slave station integration is used. This method fully integrates the advantages of time-domain analysis, FFT algorithm, and Prony algorithm, effectively solving the problem of misanalysis caused by frequency aliasing in data window selection and data analysis resampling using the Prony algorithm alone. Furthermore, since the Prony algorithm is computationally time-consuming, this invention improves the efficiency of oscillation monitoring and alarm by enhancing the computational effectiveness of the Prony algorithm. Attached Figure Description

[0026] Figure 1 This is a flowchart of a power grid broadband oscillation monitoring and alarm method according to an embodiment of the present invention.

[0027] Figure 2 This is a detailed flowchart of the power grid broadband oscillation monitoring and alarm method according to an embodiment of the present invention.

[0028] Figure 3 This is a schematic diagram of the oscillation monitoring value calculation method considering the oscillation dynamic process in an embodiment of the present invention.

[0029] Figure 4 This is a block diagram of the power grid broadband oscillation monitoring and alarm system according to an embodiment of the present invention. Detailed Implementation

[0030] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. 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 should fall within the scope of protection of the present invention.

[0031] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0032] The present invention will now be described in further detail with reference to the accompanying drawings:

[0033] See Figure 1 In one embodiment of the present invention, a broadband oscillation monitoring and alarm method for power grids is provided. Specifically, it is a broadband oscillation monitoring and alarm method for power grids based on the fusion of multiple time-frequency domain methods, covering ultra-low frequency oscillations, low frequency oscillations, subsynchronous oscillations, sub / supersynchronous oscillations, and medium- and high frequency oscillations. It comprehensively applies the advantages of the time-domain analysis methods FFT algorithm and Prony algorithm to increase the practicality and effectiveness of the current broadband oscillation monitoring and alarm method.

[0034] Specifically, the power grid broadband oscillation monitoring and alarm method of the present invention includes the following steps:

[0035] S1: Obtain the oscillation monitoring type and oscillation monitoring data of the oscillation monitoring point.

[0036] S2: Based on the oscillation monitoring data, the oscillation monitoring alarm result is obtained through the oscillation monitoring judgment method corresponding to the oscillation monitoring type.

[0037] Specifically, when the oscillation monitoring type is ultra-low frequency oscillation or low frequency oscillation, the oscillation monitoring judgment method is as follows: based on the time domain analysis method, it is determined whether the fluctuation of the oscillation monitoring data exceeds the set dead zone; and when the fluctuation of the oscillation monitoring data exceeds the set dead zone, it is determined whether the oscillation monitoring data belongs to the frequency band range of the current oscillation type based on the FFT algorithm; and when the oscillation monitoring data belongs to the frequency band range of the current oscillation type, the oscillation alarm judgment is performed based on the Prony algorithm to obtain the oscillation monitoring alarm result.

[0038] When the oscillation monitoring type is subsynchronous oscillation, the oscillation monitoring judgment method is as follows: based on the time domain analysis method, it is determined whether the fluctuation of the oscillation monitoring data exceeds the set dead zone; and when the fluctuation of the oscillation monitoring data exceeds the set dead zone, the oscillation alarm judgment is performed based on the FFT algorithm to obtain the oscillation monitoring alarm result.

[0039] When the oscillation monitoring type is subsynchronous / supersynchronous oscillation or medium-to-high frequency oscillation, the oscillation monitoring judgment method is: an oscillation monitoring judgment method based on the combination of master and substations.

[0040] This invention provides a broadband power grid oscillation monitoring and alarm method that employs different oscillation monitoring and judgment methods for different oscillation monitoring types. Specifically, for ultra-low frequency or low frequency oscillations, a method combining time-domain analysis, FFT algorithm, and Prony algorithm is used; for subsynchronous oscillations, a method combining time-domain analysis and FFT algorithm is used; and for sub / supersynchronous or medium-high frequency oscillations, a method based on master-slave station integration is used. This method fully integrates the advantages of time-domain analysis, FFT algorithm, and Prony algorithm, effectively solving the problem of misanalysis caused by frequency aliasing in data window selection and data analysis resampling using the Prony algorithm alone. Furthermore, since the Prony algorithm is computationally time-consuming, this invention improves the efficiency of oscillation monitoring and alarm by enhancing the computational effectiveness of the Prony algorithm.

[0041] Time-domain analysis methods directly analyze the waveform of oscillating signals over time without requiring spectrum conversion. They identify and quantify oscillations by observing characteristics such as the periodicity, amplitude variation, and phase difference of the signal waveform. In oscillation monitoring, time-domain analysis visually displays the dynamic process of oscillation, helping to quickly capture the start and end of oscillations and serving as an important means of preliminary judgment of oscillation type and intensity. The Fast Fourier Transform (FFT) algorithm is an efficient algorithm for converting signals from the time domain to the frequency domain. In oscillation analysis, the FFT algorithm can reveal the frequency components and their distribution in oscillating signals, particularly identifying the dominant frequency and harmonic components. The FFT spectrum clearly shows the trend of oscillation frequency changes, providing important basis for in-depth analysis of oscillation mechanisms and the development of control strategies. The Prony algorithm is a parameter estimation method, particularly suitable for analyzing signals containing multiple exponentially decaying (or growing) sinusoidal components. In oscillation analysis, the Prony algorithm can accurately estimate the modal parameters of the oscillation, including oscillation frequency, damping ratio, and amplitude. These parameters are crucial for understanding the physical mechanism of oscillations, evaluating system stability, and designing effective control measures. Compared to the FFT algorithm, the Prony algorithm typically offers higher accuracy and resolution in extracting oscillation mode parameters.

[0042] In one possible implementation, when acquiring the oscillation monitoring type and oscillation monitoring data, if the oscillation monitoring type is ultra-low frequency oscillation, low frequency oscillation, or subsynchronous oscillation, the oscillation monitoring data is active power data; if the oscillation monitoring type is sub / supersynchronous oscillation or medium-high frequency oscillation, the oscillation monitoring data is the instantaneous oscillation power component or interharmonic current data transmitted by the substation.

[0043] All oscillation monitoring points are equipped with oscillation monitoring and alarm functions for ultra-low frequency oscillation, low frequency oscillation, and subsynchronous oscillation, while broadband oscillation monitoring points are equipped with oscillation monitoring and alarm functions for sub / supersynchronous oscillation and medium-to-high frequency oscillation.

[0044] Specifically, the presence of the "SPN" identifier on the equipment indicates whether it is a broadband device. All oscillation monitoring points monitor ultra-low frequency oscillations, low frequency oscillations, and subsynchronous oscillations. Only oscillation monitoring points with broadband monitoring equipment monitor subsynchronous / supersynchronous oscillations and mid-to-high frequency oscillations. When acquiring oscillation monitoring data from each monitoring point, active power data from PMU (Phasor Measurement Unit) data is used for ultra-low frequency oscillations, low frequency oscillations, and subsynchronous oscillations; amplitude and frequency of the instantaneous oscillation power components transmitted from the substation are directly obtained from the database for subsynchronous / supersynchronous oscillations.

[0045] In one possible implementation, see Figure 2 The method of determining whether the fluctuation of oscillation monitoring data exceeds the set dead zone based on time-domain analysis includes: obtaining the current time window data according to the oscillation monitoring type and oscillation monitoring data, and obtaining the difference between the maximum and minimum values ​​of the oscillation monitoring data in the current time window data; when the difference between the maximum and minimum values ​​of the oscillation monitoring data exceeds the set dead zone, the fluctuation of the oscillation monitoring data exceeds the set dead zone; when the difference between the maximum and minimum values ​​of the oscillation monitoring data does not exceed the set dead zone, the fluctuation of the oscillation monitoring data does not exceed the set dead zone, and the process returns to perform oscillation monitoring judgment for the next time window data.

[0046] Specifically, based on the oscillation monitoring type and the oscillation monitoring data, the current time window data is obtained. That is, the data within the set time period (current time window) of the oscillation monitoring data is obtained from the real-time time series database. The current time window data can be preprocessed and filtered, and then the maximum value V of the oscillation monitoring data is obtained using the time domain analysis method. max and the minimum value V of the oscillation monitoring data min This allows us to obtain the maximum value V of the oscillation monitoring data. max and the minimum value V of oscillation monitoring data min The difference V between the maximum and minimum values ​​of the oscillation monitoring data is then used as the fluctuation indicator for the oscillation monitoring data. When the difference V exceeds the set dead zone, the fluctuation of the oscillation monitoring data exceeds the set dead zone; when the difference V does not exceed the set dead zone, the fluctuation of the oscillation monitoring data does not exceed the set dead zone, and the process returns to perform oscillation monitoring judgment for the next time window.

[0047] The dead zone is set according to the preset oscillation amplitude threshold of the oscillation monitoring point, which can generally be set to 20% of the preset oscillation amplitude threshold of the oscillation monitoring point.

[0048] In one possible implementation, see Figure 2 The step of determining whether oscillation monitoring data belongs to the frequency band range of the current monitored oscillation type based on the FFT algorithm includes: obtaining the earlier of the times of the maximum value and the minimum value of the oscillation monitoring data in the current time window data to obtain the start time; obtaining the data after the start time in the current time window data to obtain the data to be analyzed; and performing spectrum analysis on the data to be analyzed using the FFT algorithm to obtain the frequency corresponding to the maximum amplitude of the data to be analyzed, and determining whether the frequency corresponding to the maximum amplitude belongs to the frequency band range of the current monitored oscillation type; when the frequency corresponding to the maximum amplitude belongs to the frequency band range of the current monitored oscillation type, the oscillation monitoring data belongs to the frequency band range of the current monitored oscillation type; when the frequency corresponding to the maximum amplitude does not belong to the frequency band range of the current monitored oscillation type, the oscillation monitoring data does not belong to the frequency band range of the current monitored oscillation type, and returning to perform oscillation monitoring judgment for the next time window data.

[0049] Specifically, taking ultra-low frequency oscillation as an example, if the frequency corresponding to the maximum amplitude of the data to be analyzed is not within the frequency band specified for ultra-low frequency oscillation, the process returns to the next calculation. If the frequency corresponding to the maximum amplitude of the data to be analyzed is within the frequency band specified for ultra-low frequency oscillation, it indicates that ultra-low frequency oscillation exists at the oscillation monitoring point, and the next step of the Prony algorithm calculation is performed.

[0050] In one possible implementation, see Figure 2 The oscillation alarm judgment based on the Prony algorithm to obtain the oscillation monitoring alarm result includes: analyzing the current time window data based on the Prony algorithm to obtain the dominant component amplitude and dominant component frequency of the current time window data; when the dominant component amplitude is greater than the difference between the maximum and minimum values ​​of the oscillation monitoring data, updating the dominant component amplitude to the difference between the maximum and minimum values ​​of the oscillation monitoring data; continuously acquiring the dominant component amplitude of a preset number of time window data and taking the average value to obtain the oscillation monitoring value; wherein, when continuously acquiring the dominant component amplitude of a preset number of time window data, when the current dominant component amplitude is less than half of the preset oscillation amplitude threshold of the oscillation monitoring point, returning to perform oscillation monitoring judgment for the next time window data.

[0051] When the oscillation monitoring value exceeds the preset oscillation amplitude threshold of the oscillation monitoring point, the oscillation monitoring alarm result is to issue an oscillation alarm, and the start time of the oscillation is the current time minus [the value of the oscillation value].

[0052] Optional, preset quantity Wnum We obtain it from the following formula:

[0053]

[0054] Where N is the number of duration cycles obtained from the preset oscillation time threshold of the oscillation monitoring point, and f osc T represents the dominant component frequency of the data in the current time window. slid The time window length for the time window data.

[0055] Specifically, the Prony algorithm is used to analyze the data within the current time window to obtain the amplitude and frequency of the dominant component, i.e., the amplitude and frequency of the dominant component, which are then used as oscillation monitoring points to observe the oscillation within that time period. At this point, the frequency f of the dominant component is... osc As the oscillation frequency, and simultaneously the amplitude V of the dominant component cur With the maximum value V of the oscillation monitoring data max and the minimum value V of oscillation monitoring data min Compare the difference V, if the amplitude of the dominant component V cur If the value is greater than V, then it is corrected to V. cur =V.

[0056] In this embodiment, the preset oscillation time threshold of the oscillation monitoring point is taken as an example of the number of continuous cycles N. The number of continuous cycles N is converted into the number of windows, i.e., the number of operations, to limit the amount of time window data. A circular array is set to store the amplitude of the dominant component of each time window data. Then, after the preset number is met, the average value is taken to obtain the oscillation monitoring value, which is compared with the preset oscillation amplitude threshold of the oscillation monitoring point. When the oscillation monitoring value is greater than the preset oscillation amplitude threshold of the oscillation monitoring point, the oscillation monitoring alarm result is to issue an oscillation alarm. This fully considers the dynamic process of oscillation and can better reflect oscillation events.

[0057] In one possible implementation, similar to the process of oscillation alarm judgment based on the Prony algorithm, the oscillation alarm judgment based on the FFT algorithm to obtain the oscillation monitoring alarm result includes: analyzing the current time window data based on the FFT algorithm to obtain the dominant component amplitude and dominant component frequency of the current time window data; and updating the dominant component amplitude to the difference between the maximum and minimum values ​​of the oscillation monitoring data when the dominant component amplitude is greater than the difference between the maximum and minimum values ​​of the oscillation monitoring data; continuously acquiring the dominant component amplitude of a preset number of time window data and taking the average value to obtain the oscillation monitoring value; wherein, when continuously acquiring the dominant component amplitude of a preset number of time window data, if the current dominant component amplitude is less than half of the preset oscillation amplitude threshold of the oscillation monitoring point, returning to perform oscillation monitoring judgment for the next time window data; when the oscillation monitoring value is greater than the preset oscillation amplitude threshold of the oscillation monitoring point, the oscillation monitoring alarm result is to issue an oscillation alarm, and the start time of the oscillation is the current time minus

[0058] Optionally, the preset oscillation time threshold and oscillation amplitude threshold for the oscillation monitoring point are set according to the voltage level and oscillation monitoring type.

[0059] Specifically, the process involves acquiring power grid topology and equipment model information, including generators, lines, and transformers, determining oscillation monitoring points, obtaining the voltage levels corresponding to these monitoring points, and then setting thresholds for each oscillation monitoring point based on the oscillation monitoring type, including oscillation amplitude thresholds and oscillation time thresholds.

[0060] In one possible implementation, when the difference between the maximum and minimum values ​​of the oscillation monitoring data exceeds the set dead zone, the first marker value for the oscillation monitoring point is 1; when the difference between the maximum and minimum values ​​of the oscillation monitoring data does not exceed the set dead zone, the first marker value for the oscillation monitoring point is 0; when the frequency corresponding to the maximum amplitude value is within the frequency band range of the current oscillation type being monitored, the second marker value for the oscillation monitoring point is 1; when the frequency corresponding to the maximum amplitude value is not within the frequency band range of the current oscillation type being monitored, the second marker value for the oscillation monitoring point is 0; when the amplitude of the dominant component is greater than the oscillation monitoring data... When the difference between the maximum value and the minimum value of the oscillation monitoring data is 1, the third marker value of the oscillation monitoring point is set to 1. When the first marker value and the third marker value of the oscillation monitoring point are both 1, when performing oscillation monitoring judgment on the time window data, if the fluctuation of the oscillation monitoring data exceeds the set dead zone, the oscillation alarm judgment is directly performed based on the Prony algorithm to obtain the oscillation monitoring alarm result. Among them, when continuously acquiring the dominant component amplitude of a preset number of time window data, if the current dominant component amplitude is less than half of the preset oscillation amplitude threshold of the oscillation monitoring point, the first marker value, the first marker value, and the third marker value of the oscillation monitoring point are all 0.

[0061] Specifically, by using a first label value, a third label value, and a third label value, when the first label value is 1 and the third label value is 1, the calculation process of the FFT algorithm can be omitted, thus saving time.

[0062] In one possible implementation, when acquiring the current time window data based on the oscillation monitoring type and oscillation monitoring data: when the oscillation monitoring type is an ultra-low frequency oscillation of 0.02–0.1 Hz, the time window length of the time window data is set to 100 s, and the time window overlap length is 50 s; when the oscillation monitoring type is a low frequency oscillation of 0.1–0.5 Hz, the time window length of the time window data is set to 20 s, and the time window overlap length is 10 s; when the oscillation monitoring type is a low frequency oscillation of 0.5–2.5 Hz, the time window length of the time window data is set to 10 s, and the time window overlap length is 5 s; when the oscillation monitoring type is a subsynchronous oscillation of 2.5–25 Hz, the time window length of the time window data is set to 10 s, and the time window overlap length is 2 s; when the oscillation monitoring type is a sub / supersynchronous oscillation or a mid-to-high frequency oscillation, the time window length of the time window data is set to 2 s, and the time window overlap length is 0 s.

[0063] Specifically, based on the characteristics of oscillation monitoring, a strategy for frequency band division and time window data division for oscillation monitoring is given, which greatly improves performance efficiency.

[0064] In one possible implementation, a master-slave combined approach is used for sub / supersynchronous oscillations or mid-to-high frequency oscillations at broadband oscillation monitoring points. The amplitude and frequency of the instantaneous oscillation power components transmitted from the substations are directly obtained from the database. Oscillation monitoring is performed by segmenting the sub / supersynchronous and mid-to-high frequency oscillations according to their frequencies, obtaining the maximum amplitude and corresponding frequency for each frequency band. Considering the frequency fluctuation characteristics of broadband oscillations, the initial frequency is used as the oscillation frequency. An alarm is triggered when the oscillation amplitude falls below 0.5 times the oscillation amplitude threshold.

[0065] In one possible implementation, taking a low-frequency oscillation as an example, assume the oscillation amplitude threshold is set to V1. The oscillation active power data is as follows: Figure 3As shown, the current approach to determining the threshold and duration is to start counting only when the amplitude exceeds the oscillation amplitude threshold, i.e., starting the duration counting at t1. In this invention, the approach is as follows: at time t0, time-domain analysis within a set time window is used to determine if the difference between the maximum and minimum values ​​exceeds the oscillation amplitude threshold. Therefore, spectral analysis is performed based on the FFT algorithm. The obtained frequency falls within the low-frequency oscillation range, and further analysis is performed based on the Prony algorithm to obtain the oscillation frequency and amplitude V0. Since the oscillation amplitude V0 exceeds the set dead zone threshold and the frequency meets the low-frequency oscillation range, the value of oscillation amplitude V0 is added to the array. When the number of calculations reaches the set time requirement, the average value of the cyclic array is calculated, which is the oscillation monitoring amplitude. At this point, if the oscillation monitoring amplitude exceeds V1, an oscillation alarm is issued. Figure 3 As can be seen, compared with the previous approach, the method of the present invention takes into account the dynamic process of oscillation, so the alarm time and judgment of oscillation are more in line with the actual situation and can provide timely alarms.

[0066] The following are embodiments of the apparatus of the present invention, which can be used to execute embodiments of the method of the present invention. For details not disclosed in the apparatus embodiments, please refer to the embodiments of the method of the present invention.

[0067] See Figure 4 In another embodiment of the present invention, a power grid broadband oscillation monitoring and alarm system is provided, which can be used to implement the above-mentioned power grid broadband oscillation monitoring and alarm method. Specifically, the power grid broadband oscillation monitoring and alarm system includes a data acquisition module and an oscillation monitoring module.

[0068] The data acquisition module acquires the oscillation monitoring type and data from the oscillation monitoring points. The oscillation monitoring module uses the oscillation monitoring data and the corresponding oscillation monitoring judgment method to obtain oscillation monitoring alarm results. Specifically, when the oscillation monitoring type is ultra-low frequency oscillation or low frequency oscillation, the oscillation monitoring judgment method is as follows: a time-domain analysis method is used to determine whether the fluctuation of the oscillation monitoring data exceeds the set dead zone; when the fluctuation exceeds the set dead zone, an FFT algorithm is used to determine whether the oscillation monitoring data falls within the frequency band of the current oscillation type; and when the oscillation monitoring data falls within the frequency band of the current oscillation type, the Prony algorithm is used to perform oscillation alarm judgment and obtain the oscillation monitoring alarm result. When the oscillation monitoring type is subsynchronous oscillation, the oscillation monitoring judgment method is as follows: a time-domain analysis method is used to determine whether the fluctuation of the oscillation monitoring data exceeds the set dead zone; and when the fluctuation exceeds the set dead zone, an FFT algorithm is used to perform oscillation alarm judgment and obtain the oscillation monitoring alarm result. When the oscillation monitoring type is sub / supersynchronous oscillation or medium-high frequency oscillation, the oscillation monitoring judgment method is based on a master-slave station combined oscillation monitoring alarm method.

[0069] All relevant content of each step involved in the aforementioned embodiments of the power grid broadband oscillation monitoring and alarm method can be referenced to the functional description of the corresponding functional module of the power grid broadband oscillation monitoring and alarm system in the embodiments of the present invention, and will not be repeated here.

[0070] The module division in this embodiment of the invention is illustrative and represents only one logical functional division. In actual implementation, other division methods may be used. Furthermore, the functional modules in the various embodiments of the invention can be integrated into a single processor, exist as separate physical entities, or be integrated into a single module. The integrated modules described above can be implemented in hardware or as software functional modules.

[0071] In another embodiment of the present invention, a computer device is provided, comprising a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions in the computer storage medium to achieve a corresponding method flow or corresponding function. The processor described in this embodiment of the present invention can be used for the operation of a power grid broadband oscillation monitoring and alarm method.

[0072] In another embodiment of the present invention, a storage medium is provided, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the computer device and extended storage media supported by the computer device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, the storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the corresponding steps of the power grid broadband oscillation monitoring and alarm method in the above embodiments.

[0073] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0074] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0075] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0076] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0077] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for monitoring and alarming broadband oscillations in a power grid, characterized in that, include: Obtain the oscillation monitoring type and oscillation monitoring data from the oscillation monitoring points; Based on oscillation monitoring data, oscillation monitoring alarm results are obtained through the oscillation monitoring judgment method corresponding to the oscillation monitoring type. Specifically, when the oscillation monitoring type is ultra-low frequency oscillation or low frequency oscillation, the oscillation monitoring judgment method is as follows: based on the time domain analysis method, it is determined whether the fluctuation of the oscillation monitoring data exceeds the set dead zone; and when the fluctuation of the oscillation monitoring data exceeds the set dead zone, it is determined whether the oscillation monitoring data belongs to the frequency band range of the current oscillation type based on the FFT algorithm; and when the oscillation monitoring data belongs to the frequency band range of the current oscillation type, the oscillation alarm judgment is performed based on the Prony algorithm to obtain the oscillation monitoring alarm result. When the oscillation monitoring type is subsynchronous oscillation, the oscillation monitoring judgment method is as follows: based on the time domain analysis method, it is determined whether the fluctuation of the oscillation monitoring data exceeds the set dead zone; and when the fluctuation of the oscillation monitoring data exceeds the set dead zone, the oscillation alarm judgment is performed based on the FFT algorithm to obtain the oscillation monitoring alarm result. When the oscillation monitoring type is subsynchronous / supersynchronous oscillation or medium-to-high frequency oscillation, the oscillation monitoring judgment method is: an oscillation monitoring judgment method based on the combination of master and substations.

2. The power grid broadband oscillation monitoring and alarm method according to claim 1, characterized in that, When acquiring the oscillation monitoring type and oscillation monitoring data, when the oscillation monitoring type is ultra-low frequency oscillation, low frequency oscillation, or subsynchronous oscillation, the oscillation monitoring data is active power data; when the oscillation monitoring type is sub / supersynchronous oscillation or medium-high frequency oscillation, the oscillation monitoring data is the instantaneous oscillation power component or interharmonic current data transmitted by the substation; wherein, all oscillation monitoring points perform oscillation monitoring alarms for ultra-low frequency oscillation, low frequency oscillation, and subsynchronous oscillation, and broadband oscillation monitoring points perform oscillation monitoring alarms for sub / supersynchronous oscillation and medium-high frequency oscillation.

3. The power grid broadband oscillation monitoring and alarm method according to claim 1, characterized in that, The method of determining whether the fluctuation of oscillation monitoring data exceeds the set dead zone based on time-domain analysis includes: Based on the oscillation monitoring type and oscillation monitoring data, obtain the current time window data, and obtain the difference between the maximum and minimum values ​​of the oscillation monitoring data in the current time window data; When the difference between the maximum and minimum values ​​of the oscillation monitoring data exceeds the set dead zone, the fluctuation of the oscillation monitoring data exceeds the set dead zone. When the difference between the maximum and minimum values ​​of the oscillation monitoring data does not exceed the set dead zone, the fluctuation of the oscillation monitoring data does not exceed the set dead zone, and the process returns to perform oscillation monitoring and judgment for the next time window.

4. The power grid broadband oscillation monitoring and alarm method according to claim 3, characterized in that, The method of determining whether oscillation monitoring data belongs to the frequency band range of the current monitored oscillation type based on the FFT algorithm includes: The earlier of the timestamps of the maximum and minimum values ​​of the oscillation monitoring data in the current time window is obtained to determine the starting time. The data after the start time in the current time window is obtained to obtain the data to be analyzed; and the FFT algorithm is used to perform spectrum analysis on the data to be analyzed to obtain the frequency corresponding to the maximum amplitude of the data to be analyzed, and to determine whether the frequency corresponding to the maximum amplitude belongs to the frequency band range of the current monitored oscillation type. When the frequency corresponding to the maximum amplitude value is within the frequency band range of the current monitored oscillation type, the oscillation monitoring data is within the frequency band range of the current monitored oscillation type; when the frequency corresponding to the maximum amplitude value is not within the frequency band range of the current monitored oscillation type, the oscillation monitoring data is not within the frequency band range of the current monitored oscillation type, and the process returns to perform oscillation monitoring judgment for the next time window data.

5. The power grid broadband oscillation monitoring and alarm method according to claim 4, characterized in that, The oscillation alarm judgment based on the Prony algorithm to obtain the oscillation monitoring alarm results includes: The Prony algorithm is used to analyze the data of the current time window to obtain the amplitude and frequency of the dominant component of the current time window data. When the amplitude of the dominant component is greater than the difference between the maximum and minimum values ​​of the oscillation monitoring data, the amplitude of the dominant component is updated to the difference between the maximum and minimum values ​​of the oscillation monitoring data. The amplitude of the dominant component of a preset number of time windows is continuously acquired and averaged to obtain the oscillation monitoring value; Specifically, when continuously acquiring the dominant component amplitude of a preset number of time windows, if the current dominant component amplitude is less than half of the preset oscillation amplitude threshold of the oscillation monitoring point, the process returns to perform oscillation monitoring and judgment for the next time window; the preset number W num We obtain it from the following formula: Where N is the number of duration cycles obtained from the preset oscillation time threshold of the oscillation monitoring point, and f osc T represents the dominant component frequency of the data in the current time window. slid The length of the time window for the time window data; When the oscillation monitoring value exceeds the preset oscillation amplitude threshold of the oscillation monitoring point, the oscillation monitoring alarm result is to issue an oscillation alarm, and the start time of the oscillation is the current time minus [the value of the oscillation value]. The oscillation monitoring alarm results obtained by the oscillation alarm judgment based on the FFT algorithm include: The FFT algorithm is used to analyze the data of the current time window to obtain the amplitude and frequency of the dominant component of the current time window data. When the amplitude of the dominant component is greater than the difference between the maximum and minimum values ​​of the oscillation monitoring data, the amplitude of the dominant component is updated to the difference between the maximum and minimum values ​​of the oscillation monitoring data. The amplitude of the dominant component of a preset number of time windows is continuously acquired and averaged to obtain the oscillation monitoring value; Specifically, when continuously acquiring the dominant component amplitude of a preset number of time windows, if the current dominant component amplitude is less than half of the preset oscillation amplitude threshold of the oscillation monitoring point, the process returns to perform oscillation monitoring and judgment for the next time window; the preset number W num We obtain it from the following formula: Where N is the number of duration cycles obtained from the preset oscillation time threshold of the oscillation monitoring point, and f osc T represents the dominant component frequency of the data in the current time window. slid The length of the time window for the time window data; When the oscillation monitoring value exceeds the preset oscillation amplitude threshold of the oscillation monitoring point, the oscillation monitoring alarm result is to issue an oscillation alarm, and the start time of the oscillation is the current time minus [the value of the oscillation value]. The preset oscillation time threshold and oscillation amplitude threshold for the oscillation monitoring point are set according to the voltage level and oscillation monitoring type.

6. The power grid broadband oscillation monitoring and alarm method according to claim 5, characterized in that, When the difference between the maximum and minimum values ​​of the oscillation monitoring data exceeds the set dead zone, the first marker value of the oscillation monitoring point is 1; when the difference between the maximum and minimum values ​​of the oscillation monitoring data does not exceed the set dead zone, the first marker value of the oscillation monitoring point is 0; when the frequency corresponding to the maximum amplitude value is within the frequency band range of the current oscillation type being monitored, the second marker value of the oscillation monitoring point is 1; when the frequency corresponding to the maximum amplitude value is not within the frequency band range of the current oscillation type being monitored, the second marker value of the oscillation monitoring point is 0. When the amplitude of the dominant component is greater than the difference between the maximum value and the minimum value of the oscillation monitoring data, the third mark value for marking the oscillation monitoring point is 1; When the first and third marker values ​​of the oscillation monitoring point are both 1, and the oscillation monitoring judgment is performed on the time window data, if the fluctuation of the oscillation monitoring data exceeds the set dead zone, the oscillation alarm judgment is directly performed based on the Prony algorithm to obtain the oscillation monitoring alarm result; among them, when continuously acquiring the dominant component amplitude of a preset number of time window data, if the current dominant component amplitude is less than half of the preset oscillation amplitude threshold of the oscillation monitoring point, the first, third, and third marker values ​​of the oscillation monitoring point are all 0.

7. The power grid broadband oscillation monitoring and alarm method according to claim 3, characterized in that, When obtaining the current time window data based on the oscillation monitoring type and oscillation monitoring data: When the oscillation monitoring type is ultra-low frequency oscillation of 0.02–0.1 Hz, the time window length of the time window data is set to 100 s, and the time window overlap length is 50 s; when the oscillation monitoring type is low frequency oscillation of 0.1–0.5 Hz, the time window length of the time window data is set to 20 s, and the time window overlap length is 10 s; when the oscillation monitoring type is low frequency oscillation of 0.5–2.5 Hz, the time window length of the time window data is set to 10 s, and the time window overlap length is 5 s; when the oscillation monitoring type is subsynchronous oscillation of 2.5–25 Hz, the time window length of the time window data is set to 10 s, and the time window overlap length is 2 s; when the oscillation monitoring type is subsynchronous / supersynchronous oscillation or medium-high frequency oscillation, the time window length of the time window data is set to 2 s, and the time window overlap length is 0 s.

8. A broadband power grid oscillation monitoring and alarm system, characterized in that, include: The data acquisition module is used to acquire the oscillation monitoring type and oscillation monitoring data of the oscillation monitoring points; The oscillation monitoring module is used to obtain oscillation monitoring alarm results based on oscillation monitoring data and the oscillation monitoring judgment method corresponding to the oscillation monitoring type. Specifically, when the oscillation monitoring type is ultra-low frequency oscillation or low frequency oscillation, the oscillation monitoring judgment method is as follows: based on the time domain analysis method, it is determined whether the fluctuation of the oscillation monitoring data exceeds the set dead zone; and when the fluctuation of the oscillation monitoring data exceeds the set dead zone, it is determined whether the oscillation monitoring data belongs to the frequency band range of the current oscillation type based on the FFT algorithm; and when the oscillation monitoring data belongs to the frequency band range of the current oscillation type, the oscillation alarm judgment is performed based on the Prony algorithm to obtain the oscillation monitoring alarm result. When the oscillation monitoring type is subsynchronous oscillation, the oscillation monitoring judgment method is as follows: based on the time domain analysis method, it is determined whether the fluctuation of the oscillation monitoring data exceeds the set dead zone; and when the fluctuation of the oscillation monitoring data exceeds the set dead zone, the oscillation alarm judgment is performed based on the FFT algorithm to obtain the oscillation monitoring alarm result. When the oscillation monitoring type is subsynchronous / supersynchronous oscillation or medium-to-high frequency oscillation, the oscillation monitoring judgment method is: an oscillation monitoring alarm method based on the combination of master and slave stations.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the power grid broadband oscillation monitoring and alarm method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the power grid broadband oscillation monitoring and alarm method as described in any one of claims 1 to 7.

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