Method and system for monitoring broadband oscillation of power system

Abstract

The invention discloses an electric power system broadband oscillation monitoring method and system, relates to the field of electric power system monitoring and control, is applied to a master station of an electric power system, and comprises the following steps: obtaining identification information of a plurality of first signals reported by each substation; wherein the identification information comprises frequency spectrum information and recording data of a time window where the frequency spectrum information is located; the first signal comprises a first-class oscillation signal and a second-class oscillation signal; screening the second-class oscillation signals according to the total hit times of each second-class oscillation signal in all substations, and combining the first-class oscillation signals to obtain a plurality of oscillation signals; and determining a parameter identification algorithm of each oscillation signal according to a frequency spectrum leakage value calculated according to the frequency spectrum information of each oscillation signal in combination with a processing load rate of the master station, and performing parameter identification on recording data of a time window where each oscillation signal is located to obtain an identification parameter so as to complete oscillation monitoring of each substation. According to the application, the broadband oscillation monitoring efficiency and accuracy of the existing circuit system can be improved.

Description

Technical Field

[0001] The present application relates to the field of power system monitoring and control, and in particular to a method and system for monitoring broadband oscillations in a power system. Background Art

[0002] Broadband oscillations in power systems are caused by interactions between power electronic devices and various other components in a "dual-high" power system. Unlike traditional oscillations, these involve multiple areas and multiple electrical devices, degrading power quality and impacting the safe and stable operation of the power system. Therefore, monitoring and controlling broadband oscillations in power systems is essential.

[0003] Existing methods for monitoring and controlling broadband oscillations have certain limitations: (1) When monitoring broadband oscillations, the sampling calculation method of traditional broadband oscillation methods is usually FFT (Fast Fourier Transform). The resolution of FFT is proportional to the length of the time window, while the computational efficiency of FFT is inversely proportional to the number of sampling points. Obtaining accurate parameter estimation results requires a longer time window. However, the sampling frequency required by the current power system is getting higher and higher. A longer time window will increase the number of sampling points, resulting in a decrease in the computational efficiency of FFT, which obviously does not meet the requirements of the power system. (2) When monitoring broadband oscillations, traditional broadband oscillation methods use FFT as the sampling calculation method, which has spectrum leakage problems that are difficult to solve, resulting in certain errors in the calculation. (3) The TLS-ESPRIT algorithm is a high-precision signal parameter estimation algorithm and is widely used in parameter identification scenarios during broadband oscillations. However, the computational cost of this algorithm is relatively high. If the power system uses this algorithm for parameter identification for a long time, it will increase the system burden. Therefore, how to monitor broadband oscillations in the power system more quickly and accurately is still a technical problem that needs to be solved in the existing technology. Summary of the Invention

[0004] The present application provides a method and system for monitoring broadband oscillations in an electric power system, so as to solve the technical problems of low efficiency and poor accuracy in the existing monitoring of broadband oscillations in an electric power system.

[0005] According to a first aspect of the embodiments of the present application, a method for monitoring broadband oscillations in a power system is provided, which is applied to a master station of a power system, the power system including the master station and multiple substations. The method includes:

[0006] Obtain identification information of multiple first signals reported by each substation; wherein each substation reports several first signals; the identification information includes spectrum information and recorded data of the time window; the first signals include a first type oscillation signal and a second type oscillation signal; the amplitude of the first type oscillation signal is greater than a preset oscillation threshold, and the amplitude of the second type oscillation signal is not greater than the preset oscillation threshold;

[0007] screening multiple second-class oscillation signals according to the total hit count of each second-class oscillation signal in all substations to obtain multiple screened oscillation signals, and obtaining multiple oscillation signals based on the multiple screened oscillation signals and the multiple first-class oscillation signals;

[0008] Based on the spectrum information of each oscillation signal, the spectrum leakage value of each oscillation signal is calculated, and the parameter identification algorithm of each oscillation signal is determined based on the spectrum leakage value and the processing load rate of the main station. Based on the parameter identification algorithm of each oscillation signal, parameter identification is performed on the recorded data of the time window where each oscillation signal is located to obtain the identification parameters of each oscillation signal, so as to complete the oscillation monitoring of each substation based on the identification parameters of each oscillation signal.

[0009] The present application first obtains identification information of multiple first signals reported by each substation, and screens the Class II oscillation signals based on the total hit count of each Class II oscillation signal in the first signal across all substations. Multiple oscillation signals are obtained by combining the multiple Class I oscillation signals in the first signal. The total hit count of all substations is used as a screening criterion for the Class II oscillation signals. This prevents a single substation from falsely reporting a certain oscillation signal and avoids interference from transient disturbances in a single substation. By mutual verification of a certain signal by multiple substations, the accuracy of screening the Class II oscillation signals is improved, thereby improving the accuracy of the monitoring results. The application then calculates the spectrum leakage value of each oscillation signal and determines a parameter identification algorithm for each oscillation signal based on the processing load rate of the master station. The parameter identification algorithm is determined based on the spectrum leakage value and the processing load rate of the master station. This allows the selection of an appropriate algorithm based on the characteristics of each oscillation signal, thereby improving system processing efficiency and, in turn, monitoring efficiency. Furthermore, the application further improves the efficiency and accuracy of the system's broadband oscillation monitoring by selecting an appropriate algorithm based on the processing load rate of the master station.

[0010] In certain embodiments of the present application, each of the substations reports a plurality of first signals, specifically including:

[0011] The current substation performs sliding window processing on the acquired recorded data to obtain multiple time windows, and performs spectrum analysis on the multiple time windows through sparse Fourier transform to obtain spectrum information of each time window; wherein the filter window function of the sparse Fourier transform is obtained by combining a rectangular window and a Gaussian window;

[0012] The current substation makes a determination based on the spectrum information of each time window. When a signal component in each time window satisfies a preset first criterion, the corresponding signal component is determined as the first signal of the current substation. The first criterion is that the number of hits and the average amplitude growth rate of the signal component in all time windows of the current substation are both greater than a preset threshold.

[0013] The current substation classifies the multiple first signals based on the amplitudes of the multiple first signals obtained by discrimination, to obtain multiple first-class oscillation signals and multiple second-class oscillation signals;

[0014] The current substation sends the spectrum information of all first signals obtained by determination and the recorded data of the corresponding time window to the main station.

[0015] The present application first enables the current substation to perform sliding window processing on the recorded data to obtain multiple time windows, and performs spectrum analysis based on sparse Fourier transform to obtain spectrum information. By combining the sliding window with the sparse Fourier transform, the recorded data can be quickly analyzed and processed, thereby improving the system processing efficiency, and thereby improving the efficiency of the system's broadband oscillation monitoring; then the spectrum information of each time window is judged, the first signal that meets the first criterion is determined, and the first signal is classified based on the threshold. It can accurately determine the first signal to be monitored and distinguish different situations in the first signal, thereby improving the accuracy of subsequent processing and improving the accuracy of the system's broadband oscillation monitoring.

[0016] In certain embodiments of the present application, calculating the spectrum leakage value of each oscillation signal according to the spectrum information of each oscillation signal specifically includes:

[0017] The spectrum leakage value of each oscillation signal is determined according to the ratio of the main lobe amplitude to the side lobe amplitude in the spectrum information of each oscillation signal.

[0018] The present application determines the spectrum leakage value of each oscillation signal by calculating the ratio of the main lobe amplitude to the side lobe amplitude in the spectrum information of each oscillation signal, which can accurately determine the degree of spectrum leakage of the signal, and then more accurately determine the corresponding parameter identification algorithm based on the degree of spectrum leakage, thereby improving the accuracy of subsequent processing and improving the accuracy of system broadband oscillation monitoring.

[0019] In certain embodiments of the present application, the parameter identification algorithm for determining each oscillation signal based on the spectrum leakage value and the processing load rate of the master station specifically includes:

[0020] If the spectrum leakage value of the current oscillation signal is not less than a preset first leakage threshold, determining that the parameter identification algorithm of the current oscillation signal is the preset first identification algorithm;

[0021] If the spectrum leakage value of the current oscillation signal is not greater than a preset second leakage threshold, determining that the parameter identification algorithm of the current oscillation signal is a preset second identification algorithm; wherein the identification accuracy of the second identification algorithm is greater than that of the first identification algorithm;

[0022] If the spectrum leakage value of the current oscillation signal is less than the first leakage threshold and greater than the second leakage threshold, and the processing load rate of the master station is less than the preset load threshold, determining that the parameter identification algorithm for the current oscillation signal is the second identification algorithm;

[0023] If the spectrum leakage value of the current oscillation signal is less than the first leakage threshold and greater than the second leakage threshold, and the processing load rate of the master station is not less than the preset load threshold, the parameter identification algorithm of the current oscillation signal is determined to be the first identification algorithm.

[0024] This application determines the different characteristics of each oscillation signal through the spectrum leakage value of each oscillation signal, and determines the parameter identification algorithm of each oscillation signal in combination with the processing load rate of the master station. It can more accurately determine a more suitable parameter identification algorithm and improve the system processing efficiency, thereby improving the efficiency and accuracy of the system's broadband oscillation monitoring.

[0025] In certain embodiments of the present application, further comprising:

[0026] Calculating the equivalent resistance of each oscillation signal based on the identification parameters of each oscillation signal;

[0027] determining corresponding multiple oscillation sources according to the equivalent resistance of each oscillation signal;

[0028] determining a switching-off order of the plurality of oscillation sources according to a result of sorting the equivalent resistance of each oscillation signal from small to large;

[0029] The multiple oscillation sources and the switching-off sequence of each oscillation source are sent to each substation, so that each substation performs a corresponding switching-off operation.

[0030] The present application first calculates the equivalent resistance based on the identification parameters of each oscillation signal, then determines multiple oscillation sources based on the equivalent resistance, and determines the switching-off order of the multiple oscillation sources based on the sorting results of the equivalent resistance of each oscillation signal. The method of determining the oscillation source by the equivalent resistance and determining the switching-off order by the sorting results of the equivalent resistance is simple and easy to use, and can correspondingly improve the processing efficiency, thereby improving the processing efficiency when the system sends multiple oscillation sources and the switching-off order of each oscillation source to each substation for switching-off after broadband oscillation monitoring.

[0031] According to a second aspect of the embodiments of the present application, there is provided a power system broadband oscillation monitoring system, which is applied to a master station of a power system, the power system comprising the master station and a plurality of substations, the system comprising a data acquisition module, a signal screening module, and a signal identification module;

[0032] The data acquisition module is configured to acquire identification information of multiple first signals reported by each substation; wherein each substation reports a plurality of first signals; the identification information includes spectrum information and recorded data of a time window; the first signals include a first type oscillation signal and a second type oscillation signal; the amplitude of the first type oscillation signal is greater than a preset oscillation threshold, and the amplitude of the second type oscillation signal is not greater than the preset oscillation threshold;

[0033] The signal screening module is configured to screen multiple second-class oscillation signals according to the total hit count of each second-class oscillation signal in all substations to obtain multiple screened oscillation signals, and to obtain multiple oscillation signals according to the multiple screened oscillation signals and the multiple first-class oscillation signals;

[0034] The signal identification module is used to calculate the spectrum leakage value of each oscillation signal based on the spectrum information of each oscillation signal, determine the parameter identification algorithm of each oscillation signal based on the spectrum leakage value and the processing load rate of the master station, and perform parameter identification on the recorded data of the time window where each oscillation signal is located based on the parameter identification algorithm of each oscillation signal to obtain the identification parameters of each oscillation signal, so as to complete the oscillation monitoring of each substation based on the identification parameters of each oscillation signal.

[0035] In certain embodiments of the present application, each of the substations reports a plurality of first signals, specifically including:

[0036] The current substation performs sliding window processing on the acquired recorded data to obtain multiple time windows, and performs spectrum analysis on the multiple time windows through sparse Fourier transform to obtain spectrum information of each time window; wherein the filter window function of the sparse Fourier transform is obtained by combining a rectangular window and a Gaussian window;

[0037] The current substation makes a determination based on the spectrum information of each time window. When a signal component in each time window satisfies a preset first criterion, the corresponding signal component is determined as the first signal of the current substation. The first criterion is that the number of hits and the average amplitude growth rate of the signal component in all time windows of the current substation are both greater than a preset threshold.

[0038] The current substation classifies the multiple first signals based on the amplitudes of the multiple first signals obtained by discrimination, to obtain multiple first-class oscillation signals and multiple second-class oscillation signals;

[0039] The current substation sends the spectrum information of all first signals obtained by determination and the recorded data of the corresponding time window to the main station.

[0040] In certain embodiments of the present application, the signal identification module includes a spectrum leakage calculation unit;

[0041] The spectrum leakage calculation unit is used to determine the spectrum leakage value of each oscillation signal according to the ratio of the main lobe amplitude to the side lobe amplitude in the spectrum information of each oscillation signal.

[0042] In certain embodiments of the present application, the signal recognition module includes an identification algorithm determination unit; the identification algorithm determination unit includes a first determination subunit, a second determination subunit, a third determination subunit, and a fourth determination subunit;

[0043] The first determination subunit is configured to determine that the parameter identification algorithm of the current oscillation signal is a preset first identification algorithm if the spectrum leakage value of the current oscillation signal is not less than a preset first leakage threshold;

[0044] The second determination subunit is configured to determine that the parameter identification algorithm for the current oscillation signal is a preset second identification algorithm if the spectrum leakage value of the current oscillation signal is not greater than a preset second leakage threshold; wherein the identification accuracy of the second identification algorithm is greater than that of the first identification algorithm;

[0045] the third determination subunit being configured to determine that the parameter identification algorithm for the current oscillation signal is the second identification algorithm if the spectrum leakage value of the current oscillation signal is less than the first leakage threshold and greater than the second leakage threshold, and the processing load rate of the master station is less than a preset load threshold;

[0046] The fourth determination subunit is configured to determine that the parameter identification algorithm for the current oscillation signal is the first identification algorithm if the spectrum leakage value of the current oscillation signal is less than the first leakage threshold and greater than the second leakage threshold, and the processing load rate of the master station is not less than a preset load threshold.

[0047] In some embodiments of the present application, a monitoring and processing module is further included; the monitoring and processing module includes an equivalent resistance calculation unit, an oscillation source determination unit, a power-off sequence determination unit, and a power-off operation issuing unit;

[0048] The equivalent resistance calculation unit is used to calculate the equivalent resistance of each oscillation signal according to the identification parameters of each oscillation signal;

[0049] The oscillation source determination unit is configured to determine the corresponding multiple oscillation sources according to the equivalent resistance of each oscillation signal;

[0050] The switching-off sequence determining unit is configured to determine a switching-off sequence of the plurality of oscillation sources according to a result of sorting the equivalent resistance of each oscillation signal from small to large;

[0051] The power-off operation sending unit is configured to send the multiple oscillation sources and the power-off sequence of each oscillation source to each substation, so that each substation performs the power-off operation accordingly.

[0052] The present application first obtains identification information of multiple first signals reported by each substation, and screens the Class II oscillation signals based on the total hit count of each Class II oscillation signal in the first signal across all substations. Multiple oscillation signals are obtained by combining the multiple Class I oscillation signals in the first signal. The total hit count of all substations is used as a screening criterion for the Class II oscillation signals. This prevents a single substation from falsely reporting a certain oscillation signal and avoids interference from transient disturbances in a single substation. By mutual verification of a certain signal by multiple substations, the accuracy of screening the Class II oscillation signals is improved, thereby improving the accuracy of the monitoring results. The application then calculates the spectrum leakage value of each oscillation signal and determines a parameter identification algorithm for each oscillation signal based on the processing load rate of the master station. The parameter identification algorithm is determined based on the spectrum leakage value and the processing load rate of the master station. This allows the selection of an appropriate algorithm based on the characteristics of each oscillation signal, thereby improving system processing efficiency and, in turn, monitoring efficiency. Furthermore, the application further improves the efficiency and accuracy of the system's broadband oscillation monitoring by selecting an appropriate algorithm based on the processing load rate of the master station. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 : is a flow chart of a method for monitoring wide-band oscillations in a power system according to certain embodiments of the present application;

[0054] Figure 2 : A module structure diagram of a power system broadband oscillation monitoring system shown in certain embodiments of the present application. DETAILED DESCRIPTION

[0055] The embodiments of the present application are described in detail below. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals represent the same or similar elements or elements with the same or similar functions from beginning to end. The embodiments described below in conjunction with the accompanying drawings are exemplary and are only used to explain some embodiments of the present application and should not be understood as limiting the embodiments of the present application. Based on the embodiments shown in this application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0056] In the description of this application, it should be understood that the terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly indicate the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of such features. In the description of this application, unless otherwise clearly specified, "multiple" and "several" mean two or more.

[0057] The existing broadband oscillation monitoring methods have the following problems: (1) The FFT is used for calculation during monitoring sampling. The resolution of the FFT is proportional to the length of the time window, while the computational efficiency of the FFT is inversely proportional to the number of sampling points. A longer time window is required to obtain accurate parameter estimation results. However, the sampling frequency required by the current power system is getting higher and higher. A longer time window will increase the number of sampling points, resulting in a decrease in the computational efficiency of the FFT. This obviously does not meet the requirements of the power system. (2) There is a spectrum leakage problem in the FFT during monitoring sampling, which is difficult to solve, resulting in certain errors in the calculation. (3) When parameter identification is required during the monitoring process, based on the high-precision requirements of partial signal estimation, a high-precision TLS-ESPRIT parameter estimation algorithm is required. However, long-term use of this algorithm will bring unnecessary burden to the system. Therefore, how to monitor broadband oscillations in power systems more quickly and accurately remains a technical problem that needs to be solved in the existing technology.

[0058] Based on the above technical background, please refer to Figure 1 The present application provides a method for monitoring broadband oscillations in a power system, which is applied to a master station of a power system, wherein the power system includes the master station and multiple substations. The method includes steps S101 to S103, each of which is as follows:

[0059] Step S101: Obtain identification information of multiple first signals reported by each substation; wherein each substation reports several first signals; the identification information includes spectrum information and recorded data of the time window; the first signal includes a Class I oscillation signal and a Class II oscillation signal; the amplitude of the Class I oscillation signal is greater than a preset oscillation threshold, and the amplitude of the Class II oscillation signal is not greater than the preset oscillation threshold.

[0060] In certain embodiments of the present application, each of the substations reports a plurality of first signals, specifically including:

[0061] The current substation performs sliding window processing on the acquired recorded data to obtain multiple time windows, and performs spectrum analysis on the multiple time windows through sparse Fourier transform to obtain spectrum information of each time window; wherein the filter window function of the sparse Fourier transform is obtained by combining a rectangular window and a Gaussian window;

[0062] The current substation makes a determination based on the spectrum information of each time window. When a signal component in each time window satisfies a preset first criterion, the corresponding signal component is determined as the first signal of the current substation. The first criterion is that the number of hits and the average amplitude growth rate of the signal component in all time windows of the current substation are both greater than a preset threshold.

[0063] The current substation classifies the multiple first signals based on the amplitudes of the multiple first signals obtained by discrimination, to obtain multiple first-class oscillation signals and multiple second-class oscillation signals;

[0064] The current substation sends the spectrum information of all first signals obtained by determination and the recorded data of the corresponding time window to the main station.

[0065] Generally, the sparse Fourier transform process includes spectrum rearrangement, filtering, downsampling FFT and positioning evaluation; wherein, spectrum rearrangement is to rearrange the time domain sequence of each time window of the input according to the spectrum rearrangement coefficient to obtain the rearranged time domain sequence; filtering is to filter the rearranged time domain sequence through the window function to obtain a filtered signal sequence; downsampling FFT is to sample and frequency domain extract FFT on the filtered signal sequence to obtain a sampled signal sequence; positioning evaluation is to reversely reconstruct the sampled signal sequence to obtain the corresponding spectral line amplitude estimation; by repeatedly iterating each step and selecting a different spectrum rearrangement coefficient for iteration each time, the accuracy of spectrum recognition is improved. Specifically, the general steps and parameter selection in the sparse Fourier transform process are well known to those skilled in the art and will not be repeated here.

[0066] Generally, the implementation of filtering in the sparse Fourier transform process includes any one of a rectangular window, a Gaussian window, a Hanning window, a Hamming window, a flat-top window, a Kaiser window, and a Blackman window.

[0067] In certain embodiments of the present application, the filter window function of the sparse Fourier transform is obtained by combining a rectangular window and a Gaussian window, specifically:

[0068] The rectangular window is specifically:

[0069] w rect (n) = 1;

[0070] The Gaussian window is specifically:

[0071]

[0072] The filter window function is obtained by convolution of the rectangular window and the Gaussian window, specifically:

[0073]

[0074] Where n∈[0, N-1] is the signal number, N is the window length, and σ is the Gaussian filter standard deviation.

[0075] More specifically, when performing spectrum analysis on the time window through sparse Fourier transform in this application, except that the filter window function is obtained by combining the rectangular window and the Gaussian window, the remaining steps and parameter selections are the same or similar to the prior art, which are well known to those skilled in the art and will not be repeated here.

[0076] In certain embodiments of the present application, when the signal component in each time window satisfies a preset first criterion, the corresponding signal component is determined as the first signal of the current substation, specifically:

[0077] If the number of hits of the current signal component in all time windows of the current substation is greater than a preset time window hit threshold and the average amplitude growth rate is greater than a preset growth rate threshold, the current signal component is determined to be the first signal.

[0078] In certain embodiments of the present application, the average amplitude growth rate is specifically:

[0079]

[0080] Where k is the number of hits of the current signal component in all time windows of the current substation, A j is the amplitude of the current signal component in the jth time window, A j+1 is the amplitude of the current signal component in the j+1th time window.

[0081] Specifically, the preferred value of the preset time window hit threshold is 4, and the preferred value of the preset growth rate threshold is 0.

[0082] The present application first enables the current substation to perform sliding window processing on the recorded data to obtain multiple time windows, and performs spectrum analysis based on sparse Fourier transform to obtain spectrum information. By combining the sliding window with the sparse Fourier transform, the recorded data can be quickly analyzed and processed, thereby improving the system processing efficiency, and thereby improving the efficiency of the system's broadband oscillation monitoring; then the spectrum information of each time window is judged, the first signal that meets the first criterion is determined, and the first signal is classified based on the threshold. It can accurately determine the first signal to be monitored and distinguish different situations in the first signal, thereby improving the accuracy of subsequent processing and improving the accuracy of the system's broadband oscillation monitoring.

[0083] Step S102: Filter multiple second-class oscillation signals according to the total hit count of each second-class oscillation signal in all substations to obtain multiple filtered oscillation signals, and obtain multiple oscillation signals based on the multiple filtered oscillation signals and multiple first-class oscillation signals.

[0084] In certain embodiments of the present application, the plurality of second-class oscillation signals are screened according to the total hit count of each second-class oscillation signal in all substations to obtain a plurality of screened oscillation signals, specifically:

[0085] According to the total hit count of each Class II oscillation signal in all substations, multiple Class II oscillation signals are screened to obtain multiple screened oscillation signals; wherein, during the screening, the Class II oscillation signal whose total hit count in all substations is higher than a preset substation hit threshold is selected as the screened oscillation signal.

[0086] Step S103: Calculate the spectrum leakage value of each oscillation signal based on the spectrum information of each oscillation signal, determine the parameter identification algorithm for each oscillation signal based on the spectrum leakage value and the processing load rate of the master station, and perform parameter identification on the recorded data of the time window where each oscillation signal is located based on the parameter identification algorithm for each oscillation signal to obtain the identification parameters of each oscillation signal, so as to complete the oscillation monitoring of each substation based on the identification parameters of each oscillation signal.

[0087] In certain embodiments of the present application, calculating the spectrum leakage value of each oscillation signal according to the spectrum information of each oscillation signal specifically includes:

[0088] The spectrum leakage value of each oscillation signal is determined according to the ratio of the main lobe amplitude to the side lobe amplitude in the spectrum information of each oscillation signal.

[0089] Specifically, the spectrum leakage value of each oscillation signal is:

[0090]

[0091] Among them, A main , A leakage are the main lobe amplitude and side lobe amplitude, respectively.

[0092] Generally, if there is no sidelobe in the spectrum information of a certain oscillation signal, it is considered that the sidelobe leakage is negligible. In this case, the spectrum leakage value is set to 999.

[0093] The present application determines the spectrum leakage value of each oscillation signal by calculating the ratio of the main lobe amplitude to the side lobe amplitude in the spectrum information of each oscillation signal, which can accurately determine the degree of spectrum leakage of the signal, and then more accurately determine the corresponding parameter identification algorithm based on the degree of spectrum leakage, thereby improving the accuracy of subsequent processing and improving the accuracy of system broadband oscillation monitoring.

[0094] In certain embodiments of the present application, the parameter identification algorithm for determining each oscillation signal based on the spectrum leakage value and the processing load rate of the master station specifically includes:

[0095] If the spectrum leakage value of the current oscillation signal is not less than a preset first leakage threshold, determining that the parameter identification algorithm of the current oscillation signal is the preset first identification algorithm;

[0096] If the spectrum leakage value of the current oscillation signal is not greater than a preset second leakage threshold, determining that the parameter identification algorithm of the current oscillation signal is a preset second identification algorithm; wherein the identification accuracy of the second identification algorithm is greater than that of the first identification algorithm;

[0097] If the spectrum leakage value of the current oscillation signal is less than the first leakage threshold and greater than the second leakage threshold, and the processing load rate of the master station is less than the preset load threshold, determining that the parameter identification algorithm for the current oscillation signal is the second identification algorithm;

[0098] If the spectrum leakage value of the current oscillation signal is less than the first leakage threshold and greater than the second leakage threshold, and the processing load rate of the master station is not less than the preset load threshold, the parameter identification algorithm of the current oscillation signal is determined to be the first identification algorithm.

[0099] In certain embodiments of the present application, the preferred value of the first leakage threshold is 20, the preferred value of the second leakage threshold is 10, and the preferred value of the preset load threshold is 40%.

[0100] Consider setting the first leakage threshold and the second leakage threshold and dividing the spectrum leakage value into three intervals. This is because when the spectrum leakage value is not less than the first leakage threshold, it means that the degree of spectrum leakage is not high and the error is small, and a higher-precision parameter identification algorithm is not required; when the spectrum leakage value is not greater than the second leakage threshold, it means that the degree of spectrum leakage is relatively the highest, and a higher-precision parameter identification is required to avoid errors; when the spectrum leakage value is between the first leakage threshold and the second leakage threshold, it means that the degree of spectrum leakage is between the two, and the first identification algorithm and the second identification algorithm can be arbitrarily selected. Therefore, a second algorithm selection reference is introduced, namely the processing load rate of the master station; when the processing load rate of the master station is less than the preset load threshold, it means that the calculation pressure is small, and a higher-precision second identification algorithm can be used; when the processing load rate of the master station is not less than the preset load threshold, it means that the calculation pressure is large, and the first identification algorithm with smaller calculation amount should be used.

[0101] In certain embodiments of the present application, a preferred implementation of the first identification algorithm is a dual-spectrum interpolation FFT algorithm, and a preferred implementation of the second identification algorithm is a tls-esprit algorithm.

[0102] Specifically, the recognition accuracy of the dual-line interpolation FFT algorithm and the tls-esprit algorithm can meet the identification of any oscillation signal in this application, but the tls-esprit algorithm has higher recognition accuracy and greater computational complexity; while the dual-line interpolation FFT has lower recognition accuracy and less computational complexity.

[0103] This application determines the different characteristics of each oscillation signal through the spectrum leakage value of each oscillation signal, and determines the parameter identification algorithm of each oscillation signal in combination with the processing load rate of the master station. It can more accurately determine a more suitable parameter identification algorithm and improve the system processing efficiency, thereby improving the efficiency and accuracy of the system's broadband oscillation monitoring.

[0104] In certain embodiments of the present application, further comprising:

[0105] Calculating the equivalent resistance of each oscillation signal based on the identification parameters of each oscillation signal;

[0106] determining corresponding multiple oscillation sources according to the equivalent resistance of each oscillation signal;

[0107] determining a switching-off order of the plurality of oscillation sources according to a result of sorting the equivalent resistance of each oscillation signal from small to large;

[0108] The multiple oscillation sources and the switching-off sequence of each oscillation source are sent to each substation, so that each substation performs a corresponding switching-off operation.

[0109] Generally, when there is an oscillation source in the power system, the expression of the equivalent impedance at the oscillation frequency of the oscillation source is defined as:

[0110]

[0111] Among them, Z s is the actual reactance of the oscillation source corresponding to each oscillation signal, They are respectively the positive sequence voltage phasor and positive sequence current phasor corresponding to the oscillation source of each oscillation signal in the abc coordinate system, j represents the imaginary part, r s , x s The equivalent resistance and equivalent reactance of the oscillation source corresponding to each oscillation signal.

[0112] Specifically, the calculations of equivalent resistance and equivalent reactance are:

[0113]

[0114] Wherein, p and q are respectively the active power and reactive power of the oscillation source corresponding to each oscillation signal, and I is the inflow current of the oscillation source corresponding to each oscillation signal.

[0115] In certain embodiments of the present application, the direction of the current flowing into the power system is regarded as the positive direction of the current, and the corresponding multiple oscillation sources are determined according to the equivalent resistance of each oscillation signal, specifically:

[0116] When and only when the equivalent resistance is less than zero, a corresponding first oscillation source is determined according to frequency spectrum information of the corresponding oscillation signal; wherein the first oscillation source is an active oscillation source.

[0117] In certain embodiments of the present application, the direction of the current flowing into the power system is regarded as the positive direction of the current, and further includes: determining corresponding multiple oscillation sources according to the equivalent reactance of each oscillation signal.

[0118] In certain embodiments of the present application, the determining of the corresponding multiple oscillation sources according to the equivalent reactance of each oscillation signal is specifically as follows:

[0119] When and only when the equivalent reactance is less than zero, a corresponding second oscillation source is determined according to frequency spectrum information of the corresponding oscillation signal; wherein the second oscillation source is a reactive oscillation source.

[0120] Specifically, the order of tripping the oscillation sources is determined based on the results of sorting the equivalent resistance of each oscillation signal from small to large. This is because the smaller the equivalent resistance value (the farther the equivalent resistance value is from the origin on the negative half axis of the number axis or the closer it is to the origin on the positive half axis of the number axis), the higher the impact of the oscillation source corresponding to the oscillation signal where the equivalent resistance is located on the power system, the higher its importance, and the priority should be given to the tripping operation.

[0121] The present application first calculates the equivalent resistance based on the identification parameters of each oscillation signal, then determines multiple oscillation sources based on the equivalent resistance, and determines the switching-off order of the multiple oscillation sources based on the sorting results of the equivalent resistance of each oscillation signal. The method of determining the oscillation source by the equivalent resistance and determining the switching-off order by the sorting results of the equivalent resistance is simple and easy to use, and can correspondingly improve the processing efficiency, thereby improving the processing efficiency when the system sends multiple oscillation sources and the switching-off order of each oscillation source to each substation for switching-off after broadband oscillation monitoring.

[0122] Compared to the prior art, the present application first obtains identification information of multiple first signals reported by each substation, and filters the Class II oscillation signals based on the total hit count of each Class II oscillation signal in the first signal across all substations. Multiple oscillation signals are obtained by combining the multiple Class I oscillation signals in the first signal. The total hit count of all substations is used as a screening criterion for the Class II oscillation signals. This prevents a single substation from falsely reporting a certain oscillation signal and avoids interference from transient disturbances in a single substation. By mutual verification of a certain signal by multiple substations, the accuracy of screening the Class II oscillation signals is improved, thereby improving the accuracy of the monitoring results. The present application then calculates the spectrum leakage value of each oscillation signal and determines a parameter identification algorithm for each oscillation signal based on the processing load rate of the master station. By determining the parameter identification algorithm based on the spectrum leakage value and the processing load rate of the master station, an appropriate algorithm can be selected based on the characteristics of each oscillation signal, thereby improving system processing efficiency and, in turn, monitoring efficiency. Furthermore, an appropriate algorithm can be selected based on the processing load rate of the master station, thereby improving system processing efficiency and, in turn, monitoring efficiency, thereby improving the efficiency and accuracy of the system's broadband oscillation monitoring.

[0123] Corresponding to the above method, see Figure 2 , an embodiment of the present application provides a power system broadband oscillation monitoring system, which is applied to a master station of a power system, the power system including the master station and multiple substations, the system including a data acquisition module 210, a signal screening module 220 and a signal identification module 230;

[0124] The data acquisition module 210 is configured to acquire identification information of multiple first signals reported by each substation; wherein each substation reports a plurality of first signals; the identification information includes spectrum information and recorded data of a time window; the first signals include a first type oscillation signal and a second type oscillation signal; the amplitude of the first type oscillation signal is greater than a preset oscillation threshold, and the amplitude of the second type oscillation signal is not greater than the preset oscillation threshold;

[0125] The signal screening module 220 is configured to screen multiple second-class oscillation signals according to the total hit count of each second-class oscillation signal in all substations to obtain multiple screened oscillation signals, and to obtain multiple oscillation signals based on the multiple screened oscillation signals and multiple first-class oscillation signals;

[0126] The signal identification module 230 is used to calculate the spectrum leakage value of each oscillation signal based on the spectrum information of each oscillation signal, determine the parameter identification algorithm of each oscillation signal based on the spectrum leakage value and the processing load rate of the master station, and perform parameter identification on the recorded data of the time window where each oscillation signal is located based on the parameter identification algorithm of each oscillation signal to obtain the identification parameters of each oscillation signal, so as to complete the oscillation monitoring of each substation based on the identification parameters of each oscillation signal.

[0127] In certain embodiments of the present application, each of the substations reports a plurality of first signals, specifically including:

[0128] The current substation performs sliding window processing on the acquired recorded data to obtain multiple time windows, and performs spectrum analysis on the multiple time windows through sparse Fourier transform to obtain spectrum information of each time window; wherein the filter window function of the sparse Fourier transform is obtained by combining a rectangular window and a Gaussian window;

[0129] The current substation makes a determination based on the spectrum information of each time window. When a signal component in each time window satisfies a preset first criterion, the corresponding signal component is determined as the first signal of the current substation. The first criterion is that the number of hits and the average amplitude growth rate of the signal component in all time windows of the current substation are both greater than a preset threshold.

[0130] The current substation classifies the multiple first signals based on the amplitudes of the multiple first signals obtained by discrimination, to obtain multiple first-class oscillation signals and multiple second-class oscillation signals;

[0131] The current substation sends the spectrum information of all first signals obtained by determination and the recorded data of the corresponding time window to the main station.

[0132] In certain embodiments of the present application, the signal identification module 230 includes a spectrum leakage calculation unit;

[0133] The spectrum leakage calculation unit is used to determine the spectrum leakage value of each oscillation signal according to the ratio of the main lobe amplitude to the side lobe amplitude in the spectrum information of each oscillation signal.

[0134] In certain embodiments of the present application, the signal identification module 230 includes an identification algorithm determination unit; the identification algorithm determination unit includes a first determination subunit, a second determination subunit, a third determination subunit, and a fourth determination subunit;

[0135] The first determination subunit is configured to determine that the parameter identification algorithm of the current oscillation signal is a preset first identification algorithm if the spectrum leakage value of the current oscillation signal is not less than a preset first leakage threshold;

[0136] The second determination subunit is configured to determine that the parameter identification algorithm for the current oscillation signal is a preset second identification algorithm if the spectrum leakage value of the current oscillation signal is not greater than a preset second leakage threshold; wherein the identification accuracy of the second identification algorithm is greater than that of the first identification algorithm;

[0137] the third determination subunit being configured to determine that the parameter identification algorithm for the current oscillation signal is the second identification algorithm if the spectrum leakage value of the current oscillation signal is less than the first leakage threshold and greater than the second leakage threshold, and the processing load rate of the master station is less than a preset load threshold;

[0138] The fourth determination subunit is configured to determine that the parameter identification algorithm for the current oscillation signal is the first identification algorithm if the spectrum leakage value of the current oscillation signal is less than the first leakage threshold and greater than the second leakage threshold, and the processing load rate of the master station is not less than a preset load threshold.

[0139] In some embodiments of the present application, a monitoring and processing module is further included; the monitoring and processing module includes an equivalent resistance calculation unit, an oscillation source determination unit, a power-off sequence determination unit, and a power-off operation issuing unit;

[0140] The equivalent resistance calculation unit is used to calculate the equivalent resistance of each oscillation signal according to the identification parameters of each oscillation signal;

[0141] The oscillation source determination unit is configured to determine the corresponding multiple oscillation sources according to the equivalent resistance of each oscillation signal;

[0142] The switching-off sequence determining unit is configured to determine a switching-off sequence of the plurality of oscillation sources according to a result of sorting the equivalent resistance of each oscillation signal from small to large;

[0143] The power-off operation sending unit is configured to send the multiple oscillation sources and the power-off sequence of each oscillation source to each substation, so that each substation performs the power-off operation accordingly.

[0144] The present application first obtains identification information of multiple first signals reported by each substation, and screens the Class II oscillation signals based on the total hit count of each Class II oscillation signal in the first signal across all substations. Multiple oscillation signals are obtained by combining the multiple Class I oscillation signals in the first signal. The total hit count of all substations is used as a screening criterion for the Class II oscillation signals. This prevents a single substation from falsely reporting a certain oscillation signal and avoids interference from transient disturbances in a single substation. By mutual verification of a certain signal by multiple substations, the accuracy of screening the Class II oscillation signals is improved, thereby improving the accuracy of the monitoring results. The application then calculates the spectrum leakage value of each oscillation signal and determines a parameter identification algorithm for each oscillation signal based on the processing load rate of the master station. The parameter identification algorithm is determined based on the spectrum leakage value and the processing load rate of the master station. This allows the selection of an appropriate algorithm based on the characteristics of each oscillation signal, thereby improving system processing efficiency and, in turn, monitoring efficiency. Furthermore, the application further improves the efficiency and accuracy of the system's broadband oscillation monitoring by selecting an appropriate algorithm based on the processing load rate of the master station.

[0145] It should be understood that the system provided in the embodiment of the present application corresponds to the aforementioned method, and the power system broadband oscillation monitoring system provided in the embodiment of the present application can implement the power system broadband oscillation monitoring method provided in any embodiment of the present application.

[0146] Adaptively, the embodiments of the present application further provide a computer device and a computer-readable storage medium.

[0147] The computer device comprises: a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor;

[0148] Wherein, when the processor executes the computer program, a method for monitoring wide-band oscillation of a power system of the present application is implemented.

[0149] The computer-readable storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor to execute a method for monitoring wide-band oscillation of a power system according to the present application.

[0150] The above description is a partial embodiment of the present application, which further describes the purpose, technical solutions, and beneficial effects of the present application in detail. It should be understood that the above description of the partial embodiment of the present application is not to be construed as limiting the present application. In particular, it is pointed out that for those skilled in the art, any changes, modifications, equivalent substitutions, and variations made within the spirit and principles of the present application should be included within the scope of protection of the present application.

Claims

1. A method for monitoring broadband oscillations in a power system, characterized in that: Applied to a master station of a power system, the power system comprising the master station and a plurality of substations, the method comprising: Obtain identification information of multiple first signals reported by each substation; wherein each substation reports several first signals; the identification information includes spectrum information and recorded data of the time window; the first signals include a first type oscillation signal and a second type oscillation signal; the amplitude of the first type oscillation signal is greater than a preset oscillation threshold, and the amplitude of the second type oscillation signal is not greater than the preset oscillation threshold; screening multiple second-class oscillation signals according to the total hit count of each second-class oscillation signal in all substations to obtain multiple screened oscillation signals, and obtaining multiple oscillation signals based on the multiple screened oscillation signals and the multiple first-class oscillation signals; Based on the spectrum information of each oscillation signal, the spectrum leakage value of each oscillation signal is calculated, and the parameter identification algorithm of each oscillation signal is determined based on the spectrum leakage value and the processing load rate of the main station. Based on the parameter identification algorithm of each oscillation signal, parameter identification is performed on the recorded data of the time window where each oscillation signal is located to obtain the identification parameters of each oscillation signal, so as to complete the oscillation monitoring of each substation based on the identification parameters of each oscillation signal.

2. A method for monitoring wide-band oscillations in a power system according to claim 1, characterized in that: Each of the substations reports a number of first signals, specifically including: The current substation performs sliding window processing on the acquired recorded data to obtain multiple time windows, and performs spectrum analysis on the multiple time windows through sparse Fourier transform to obtain spectrum information of each time window; wherein the filter window function of the sparse Fourier transform is obtained by combining a rectangular window and a Gaussian window; The current substation makes a determination based on the spectrum information of each time window. When a signal component in each time window satisfies a preset first criterion, the corresponding signal component is determined as the first signal of the current substation. The first criterion is that the number of hits and the average amplitude growth rate of the signal component in all time windows of the current substation are both greater than a preset threshold. The current substation classifies the multiple first signals based on the amplitudes of the multiple first signals obtained by discrimination, to obtain multiple first-class oscillation signals and multiple second-class oscillation signals; The current substation sends the spectrum information of all first signals obtained by determination and the recorded data of the corresponding time window to the main station.

3. A method for monitoring broadband oscillations in a power system according to claim 1, characterized in that: Calculating the spectrum leakage value of each oscillation signal according to the spectrum information of each oscillation signal specifically includes: The spectrum leakage value of each oscillation signal is determined according to the ratio of the main lobe amplitude to the side lobe amplitude in the spectrum information of each oscillation signal.

4. A method for monitoring broadband oscillations in a power system according to claim 1, characterized in that: The parameter identification algorithm for each oscillation signal is determined according to the spectrum leakage value and the processing load rate of the master station, specifically comprising: If the spectrum leakage value of the current oscillation signal is not less than a preset first leakage threshold, determining that the parameter identification algorithm of the current oscillation signal is the preset first identification algorithm; If the spectrum leakage value of the current oscillation signal is not greater than a preset second leakage threshold, determining that the parameter identification algorithm of the current oscillation signal is a preset second identification algorithm; wherein the identification accuracy of the second identification algorithm is greater than that of the first identification algorithm; If the spectrum leakage value of the current oscillation signal is less than the first leakage threshold and greater than the second leakage threshold, and the processing load rate of the master station is less than the preset load threshold, determining that the parameter identification algorithm for the current oscillation signal is the second identification algorithm; If the spectrum leakage value of the current oscillation signal is less than the first leakage threshold and greater than the second leakage threshold, and the processing load rate of the master station is not less than the preset load threshold, the parameter identification algorithm of the current oscillation signal is determined to be the first identification algorithm.

5. A method for monitoring wide-band oscillations in a power system according to any one of claims 1 to 4, characterized in that: Also includes: Calculating the equivalent resistance of each oscillation signal based on the identification parameters of each oscillation signal; determining corresponding multiple oscillation sources according to the equivalent resistance of each oscillation signal; determining a switching-off order of the plurality of oscillation sources according to a result of sorting the equivalent resistance of each oscillation signal from small to large; The multiple oscillation sources and the switching-off sequence of each oscillation source are sent to each substation, so that each substation performs a corresponding switching-off operation.

6. A power system broadband oscillation monitoring system, characterized in that: A master station applied to a power system, the power system comprising the master station and a plurality of substations, the system comprising a data acquisition module, a signal screening module and a signal identification module; The data acquisition module is configured to acquire identification information of multiple first signals reported by each substation; wherein each substation reports a plurality of first signals; the identification information includes spectrum information and recorded data of a time window; the first signals include a first type oscillation signal and a second type oscillation signal; the amplitude of the first type oscillation signal is greater than a preset oscillation threshold, and the amplitude of the second type oscillation signal is not greater than the preset oscillation threshold; The signal screening module is configured to screen multiple second-class oscillation signals according to the total hit count of each second-class oscillation signal in all substations to obtain multiple screened oscillation signals, and to obtain multiple oscillation signals according to the multiple screened oscillation signals and the multiple first-class oscillation signals; The signal identification module is used to calculate the spectrum leakage value of each oscillation signal based on the spectrum information of each oscillation signal, determine the parameter identification algorithm of each oscillation signal based on the spectrum leakage value and the processing load rate of the master station, and perform parameter identification on the recorded data of the time window where each oscillation signal is located based on the parameter identification algorithm of each oscillation signal to obtain the identification parameters of each oscillation signal, so as to complete the oscillation monitoring of each substation based on the identification parameters of each oscillation signal.

7. The power system broadband oscillation monitoring system according to claim 6, characterized in that: Each of the substations reports a number of first signals, specifically including: The current substation performs sliding window processing on the acquired recorded data to obtain multiple time windows, and performs spectrum analysis on the multiple time windows through sparse Fourier transform to obtain spectrum information of each time window; wherein the filter window function of the sparse Fourier transform is obtained by combining a rectangular window and a Gaussian window; The current substation makes a determination based on the spectrum information of each time window. When a signal component in each time window satisfies a preset first criterion, the corresponding signal component is determined as the first signal of the current substation. The first criterion is that the number of hits and the average amplitude growth rate of the signal component in all time windows of the current substation are both greater than a preset threshold. The current substation classifies the multiple first signals based on the amplitudes of the multiple first signals obtained by discrimination, to obtain multiple first-class oscillation signals and multiple second-class oscillation signals; The current substation sends the spectrum information of all first signals obtained by determination and the recorded data of the corresponding time window to the main station.

8. The power system broadband oscillation monitoring system according to claim 6, characterized in that: The signal identification module includes a spectrum leakage calculation unit; The spectrum leakage calculation unit is used to determine the spectrum leakage value of each oscillation signal according to the ratio of the main lobe amplitude to the side lobe amplitude in the spectrum information of each oscillation signal.

9. The power system broadband oscillation monitoring system according to claim 6, characterized in that: The signal recognition module includes an identification algorithm determination unit; the identification algorithm determination unit includes a first determination subunit, a second determination subunit, a third determination subunit and a fourth determination subunit; The first determination subunit is configured to determine that the parameter identification algorithm of the current oscillation signal is a preset first identification algorithm if the spectrum leakage value of the current oscillation signal is not less than a preset first leakage threshold; The second determination subunit is configured to determine that the parameter identification algorithm for the current oscillation signal is a preset second identification algorithm if the spectrum leakage value of the current oscillation signal is not greater than a preset second leakage threshold; wherein the identification accuracy of the second identification algorithm is greater than that of the first identification algorithm; the third determination subunit being configured to determine that the parameter identification algorithm for the current oscillation signal is the second identification algorithm if the spectrum leakage value of the current oscillation signal is less than the first leakage threshold and greater than the second leakage threshold, and the processing load rate of the master station is less than a preset load threshold; The fourth determination subunit is configured to determine that the parameter identification algorithm for the current oscillation signal is the first identification algorithm if the spectrum leakage value of the current oscillation signal is less than the first leakage threshold and greater than the second leakage threshold, and the processing load rate of the master station is not less than a preset load threshold.

10. A power system broadband oscillation monitoring system according to any one of claims 6 to 9, characterized in that: It also includes a monitoring and processing module; the monitoring and processing module includes an equivalent resistance calculation unit, an oscillation source determination unit, a power-off sequence determination unit, and a power-off operation issuing unit; The equivalent resistance calculation unit is used to calculate the equivalent resistance of each oscillation signal according to the identification parameters of each oscillation signal; The oscillation source determination unit is configured to determine the corresponding multiple oscillation sources according to the equivalent resistance of each oscillation signal; The switching-off sequence determining unit is configured to determine a switching-off sequence of the plurality of oscillation sources according to a result of sorting the equivalent resistance of each oscillation signal from small to large; The power-off operation sending unit is configured to send the multiple oscillation sources and the power-off sequence of each oscillation source to each substation, so that each substation performs the power-off operation accordingly.

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