Low-frequency oscillation data filtering method and device of thermal power generating unit

Abstract

The invention provides a low-frequency oscillation data filtering method and device for a thermal power generating unit, and the method comprises the steps: carrying out the signal conversion of original synchronous vector measurement data or a power signal measured by the unit through a preset sliding window data region, and generating symmetric signal data; performing data preprocessing on the symmetrical signal data to generate preprocessed low-frequency oscillation signal data; filtering and denoising processing is carried out on the preprocessed low-frequency oscillation signal data through a pre-constructed composite filter to generate low-frequency filtering signal data, and the composite filter is constructed based on morphology and can detect low-frequency oscillation information in real time; the low-frequency oscillation data and the normal load fluctuation are distinguished and discriminated, the low-frequency oscillation data are filtered, various noise signals are effectively eliminated, the application range is wide, and the filtering accuracy is improved; the calculation amount is controlled, and the stability and reliability of the calculation result are improved, so that an effective data basis is provided for early warning identification of subsequent low-frequency oscillation.

Description

Technical Field

[0001] The present invention relates to the technical field of power systems, and in particular to a method and device for filtering low-frequency oscillation data of a thermal power unit. Background Art

[0002] With the large-scale access of new energy power generation, due to its characteristics of randomness, intermittency and volatility, and the insufficient peak regulation capacity of the power system at the same time, the grid frequency fluctuates relatively frequently. In addition, a large number of thermal power units have completed flexibility transformation and are operating in the deep peak regulation range. Since the working areas of the main and auxiliary equipment of the unit change under this working condition, the moment of inertia of the unit is continuously reduced, and the anti-disturbance ability is continuously reduced. The simultaneous action of external disturbances or internal disturbances causes the unit to easily trigger unit-level forced oscillations, posing a huge hidden danger to system stability and endangering the operation safety of the unit and the power grid. In related technologies, the extraction of low-frequency oscillation data is carried out through time-domain methods or parameter identification methods, so as to obtain information such as phase, frequency, period and amplitude. However, the time-domain method is only effective for low-frequency oscillation waveforms with relatively simple frequency components, and is easily affected by high-order harmonics in the signal and misjudge the maximum and minimum points, resulting in a narrow application range and low accuracy; the iterative calculation method of the parameter identification method determines that its calculation amount is unstable, and various factors will lead to poor stability and reliability of its analysis results. Summary of the Invention

[0003] An object of the present invention is to provide a method for filtering low-frequency oscillation data of a thermal power unit, which can detect low-frequency oscillation information in real time, realize the distinction and discrimination between low-frequency oscillation data and normal load fluctuations, filter the low-frequency oscillation data, effectively eliminate various noise signals, has a wide application range, improves the filtering accuracy; controls the calculation amount, improves the stability and reliability of the calculation results, and thus provides an effective data basis for the early warning and identification of subsequent low-frequency oscillations. Another object of the present invention is to provide a device for filtering low-frequency oscillation data of a thermal power unit. Still another object of the present invention is to provide a computer-readable medium. Yet another object of the present invention is to provide a computer device.

[0004] To achieve the above object, on the one hand, the present invention discloses a method for filtering low-frequency oscillation data of a thermal power unit, including:

[0005] Obtaining the original synchronized vector measurement data of the thermal power unit;

[0006] Converting the original synchronized vector measurement data through a preset sliding window data area to generate symmetric signal data;

[0007] Performing data preprocessing on the symmetric signal data to generate preprocessed low-frequency oscillation signal data;

[0008] The pre-processed low-frequency oscillation signal data is filtered and denoised by using a pre-constructed composite filter to generate low-frequency filtered signal data, wherein the composite filter is constructed based on morphology.

[0009] Preferably, the raw synchrophasor measurement data includes active power data;

[0010] Through a preset sliding window, signal conversion is performed based on the original synchronous vector measurement data to generate symmetrical signal data, including:

[0011] Obtaining an input load command signal;

[0012] If the state of the load command signal is available, subtract the active power data in the sliding window data area from the load command signal to generate symmetrical signal data;

[0013] If the state of the load command signal is unavailable, extreme value calculation is performed on the active power data in the sliding window data area, and the upper and lower envelopes of the sliding window data area are determined according to the active power extreme value;

[0014] Symmetrical signal data is generated based on the actual power values of the upper and lower envelopes and the average values of the upper and lower envelopes.

[0015] Preferably, performing data preprocessing on the symmetrical signal data to generate preprocessed low-frequency oscillation signal data includes:

[0016] Perform abnormal data detection on the symmetrical signal data, remove the abnormal data, and generate cleaned symmetrical signal data;

[0017] The cleaned symmetrical signal data is processed for missing values to generate preprocessed low-frequency oscillation signal data.

[0018] Preferably, the composite filter comprises a morphological open-closed maximum filter and a morphological closed-open minimum filter;

[0019] The pre-processed low-frequency oscillation signal data is filtered and denoised using a pre-built composite filter to generate low-frequency filtered signal data, including:

[0020] Generate a morphological open-close maximum filter signal based on the preprocessed low-frequency oscillation signal data and a preset structure element sequence through a morphological open-close maximum filter;

[0021] Generate a morphologically closed-open minimum filtered signal based on the preprocessed low-frequency oscillation signal data and a preset structure element sequence through a morphologically closed-open minimum filter;

[0022] Low-frequency filter signal data is generated according to the morphological open-close maximum filter signal and the morphological close-open minimum filter signal.

[0023] Preferably, the method further includes:

[0024] Suppressing the constructed noisy signal through a composite filter to generate a sample filtered signal;

[0025] Generating a filtering coefficient according to the sample filtered signal and the noisy signal;

[0026] Adjusting and updating the parameters of the composite filter according to the filtering coefficient to generate an updated composite filter.

[0027] The present invention also discloses a low-frequency oscillation data filtering device for a thermal power unit, including:

[0028] An acquisition unit for acquiring the original synchronous vector measurement data of the thermal power unit;

[0029] A signal conversion unit for performing signal conversion on the original synchronous vector measurement data through a preset sliding window data area to generate symmetric signal data;

[0030] A data preprocessing unit for preprocessing the symmetric signal data to generate preprocessed low-frequency oscillation signal data;

[0031] B A filtering unit for filtering and denoising the preprocessed low-frequency oscillation signal data through a pre-constructed composite filter to generate low-frequency filtered signal data, and the composite filter is constructed based on morphology.

[0032] Preferably, the original synchronous vector measurement data includes active power data;

[0033] The signal conversion unit is specifically configured to acquire an input load command signal; if the state of the load command signal is available, subtract the active power data in the sliding window data area from the load command signal to generate symmetric signal data; if the state of the load command signal is unavailable, calculate the extreme values of the active power data in the sliding window data area, and determine the upper and lower envelope lines of the sliding window data area according to the active power extreme values; generate symmetric signal data according to the actual power values of the upper and lower envelope lines and the mean values of the upper and lower envelope lines.

[0034] Preferably, the data preprocessing unit is specifically configured to detect abnormal data in the symmetric signal data, remove the abnormal data, and generate cleaned symmetric signal data; perform missing value processing on the cleaned symmetric signal data to generate preprocessed low-frequency oscillation signal data.

[0035] Preferably, the composite filter includes a morphological opening-closing maximum filter and a morphological closing-opening minimum filter;

[0036] A filtering unit, specifically configured to generate a morphological opening-closing maximum filtering signal through a morphological opening-closing maximum filter according to the preprocessed low-frequency oscillation signal data and a preset structural element sequence; generate a morphological closing-opening minimum filtering signal through a morphological closing-opening minimum filter according to the preprocessed low-frequency oscillation signal data and the preset structural element sequence; and generate low-frequency filtering signal data according to the morphological opening-closing maximum filtering signal and the morphological closing-opening minimum filtering signal.

[0037] Preferably, the apparatus further includes:

[0038] A suppression unit, configured to suppress the constructed noisy signal through a composite filter to generate a sample filtering signal;

[0039] A coefficient generation unit, configured to generate a filtering coefficient according to the sample filtering signal and the noisy signal;

[0040] An update unit, configured to adjust and update the parameters of the composite filter according to the filtering coefficient to generate an updated composite filter.

[0041] The present invention also discloses a computer-readable medium, on which a computer program is stored, and when the program is executed by a processor, the above-mentioned method is implemented.

[0042] The present invention also discloses a computer device, including a memory and a processor, where the memory is used to store information including program instructions, and the processor is used to control the execution of the program instructions. When the processor executes the program, the above-mentioned method is implemented.

[0043] The present invention also discloses a computer program product, including computer programs / instructions, and when the computer programs / instructions are executed by a processor, the above-mentioned method is implemented.

[0044] The present invention obtains the original synchronized vector measurement data of a thermal power unit; performs signal conversion on the original synchronized vector measurement data through a preset sliding window data area to generate symmetric signal data; performs data preprocessing on the symmetric signal data to generate preprocessed low-frequency oscillation signal data; performs filtering and denoising processing on the preprocessed low-frequency oscillation signal data through a pre-constructed composite filter to generate low-frequency filtering signal data. The composite filter is constructed based on morphology, can detect low-frequency oscillation information in real time, realizes the distinction and discrimination between low-frequency oscillation data and normal load fluctuations, filters the low-frequency oscillation data, effectively eliminates various noise signals, has a wide application range, improves the filtering accuracy rate, controls the calculation amount, and improves the stability and reliability of the calculation result, thereby providing an effective data basis for the subsequent early warning and identification of low-frequency oscillations. Description of the Drawings

[0045] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the accompanying drawings required for the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can also be obtained based on these drawings.

[0046] Figure 1 Flowchart of a low-frequency oscillation data filtering method for a thermal power unit provided by an embodiment of the present invention;

[0047] Figure 2 Schematic diagram of the corrosion operation process of a semi-circular structural element provided by an embodiment of the present invention;

[0048] Figure 3 Schematic diagram of the dilation operation process of a semi-circular structural element provided by an embodiment of the present invention;

[0049] Figure 4 Flowchart of another low-frequency oscillation data filtering method for a thermal power unit provided by an embodiment of the present invention;

[0050] Figure 5 Comparison schematic diagram of the noise suppression effect of a semi-circular CMF filter provided by an embodiment of the present invention;

[0051] Figure 6 Schematic diagram of the structure of a low-frequency oscillation data filtering device for a thermal power unit provided by an embodiment of the present invention;

[0052] Figure 7 Schematic diagram of the structure of a computer device provided by an embodiment of the present invention. Detailed implementation manners

[0053] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0054] It should be noted that a low-frequency oscillation data filtering method and device for a thermal power unit disclosed in this application can be used in the field of artificial intelligence technology, and can also be used in any field other than the field of artificial intelligence technology. The application fields of the low-frequency oscillation data filtering method and device for a thermal power unit disclosed in this application are not limited.

[0055] To facilitate the understanding of the technical solution provided by this application, the relevant content of the technical solution of this application will be described below. Low-frequency oscillation in a power system (also known as electromechanical oscillation and power oscillation) refers to the phenomenon that when the power system is disturbed, the relative swing between the rotors of synchronous generators operating in parallel causes oscillations of various electrical quantities such as power, voltage, and power angle in the system to varying degrees. The continuous oscillation frequency is between 0.2 and 2.5 Hz, which is called low-frequency oscillation; the oscillation frequency is between 0.2 and 0.7 Hz, which is called the interarea oscillation mode. This mode is the oscillation of the generator groups between two regions, and the oscillation power propagates to the entire system through the tie lines. The interarea oscillation mode is more harmful.

[0056] The problem of low-frequency oscillation has the characteristics of suddenness and urgency. If not handled in time, it will threaten the safe and stable operation of the power system. In severe cases, it will cause overcurrent tripping of tie lines and out-of-step splitting of the system. Timely and effective handling of low-frequency oscillation can greatly solve such problems. The handling of low-frequency oscillation requires data acquisition - data processing - early warning - suppression control. Since there are still a large number of various noise and other signals in the low-frequency oscillation data, traditional filtering methods cannot achieve good noise removal functions. The present invention uses morphology to preprocess the low-frequency oscillation data, effectively eliminating various noise signals and providing an effective data basis for the subsequent early warning and identification of low-frequency oscillation.

[0057] Taking the low-frequency oscillation data filtering device of a thermal power unit as the execution subject as an example below, the implementation process of the low-frequency oscillation data filtering method for a thermal power unit provided by the embodiments of the present invention will be described. It can be understood that the execution subject of the low-frequency oscillation data filtering method for a thermal power unit provided by the embodiments of the present invention includes but is not limited to the low-frequency oscillation data filtering device of a thermal power unit.

[0058] Figure 1 The flowchart of a low-frequency oscillation data filtering method for a thermal power unit provided by the embodiments of the present invention is as Figure 1 shown, and the method includes:

[0059] Step 101, obtain the original phasor measurement unit (PMU) data of the thermal power unit.

[0060] In the embodiments of the present invention, phasor measurement unit (PMU) devices have been widely used in power systems, and a large amount of high-precision data has laid a good foundation for the real-time monitoring of the dynamic behavior of the system. Low-frequency oscillation in a power system is mainly caused by electromechanical oscillation modes, manifested as the reciprocating fluctuation of the active power of the unit. Therefore, the active power of the unit is selected as the signal for online identification of low-frequency oscillation. The PMU data sampling interval is usually set to 20 ms.

[0061] As another alternative, it is also possible to obtain the power signal measured by the unit, that is, obtain the original PMU data or the power signal measured by the unit.

[0062] Step 102: Perform signal conversion on the original PMU data through a preset sliding window data area to generate symmetric signal data.

[0063] In the embodiment of the present invention, during the data processing, in order to monitor and analyze the low-frequency oscillation data of thermal power generating units in real time, a fixed-size data window (i.e., "sliding window") is set to dynamically update and screen the data. Specifically, a fixed length or time range is defined as the data interval for current analysis. Whenever new data enters the data area, the window will automatically adjust so that the data area always remains within a specific size range. For example, if the window size is 1 second, the oldest one-second data will be removed every second, and the latest one-second data will be added.

[0064] As another alternative, it is also possible to obtain the power signal measured by the unit, that is: perform signal conversion on the original PMU data or the power signal measured by the unit through a preset sliding window data area to generate symmetric signal data.

[0065] Step 103: Perform data preprocessing on the symmetric signal data to generate preprocessed low-frequency oscillation signal data.

[0066] In the embodiment of the present invention, problems such as data anomalies during the PMU sampling process and data packet loss during the data transmission process may occur during the data acquisition and transmission. For data anomalies, data preprocessing includes abnormal data detection and elimination; for data packet loss, data preprocessing includes missing value processing.

[0067] Step 104: Perform filtering and denoising processing on the preprocessed low-frequency oscillation signal data through a pre-constructed composite filter to generate low-frequency filtered signal data.

[0068] In the embodiment of the present invention, in addition to data anomalies and packet loss, noise signals will inevitably be generated during the acquisition and transmission of power signals, which will have an adverse impact on the accuracy of low-frequency oscillation identification. To address this problem, mathematical morphology is used to filter the measured signals, leveraging the characteristics of fast calculation speed, good noise filtering effect, and strong signal reconstruction ability of mathematical morphology to effectively suppress the interference of noise signals on the monitoring signals.

[0069] In the embodiments of the present invention, the composite filter is constructed based on morphology. The basic operations of mathematical morphology include dilation, erosion, opening, closing operations, etc. The power sampling signal is generally one-dimensional data. Assume that the domain of the one-dimensional multi-valued power signal f(n) obtained is D[f] = {0, 1, 2, 3, …, N}; the selected structural element sequence is g(x), and its domain is D[g] = {0, 1, 2, 3, …, P}; where P and N are integers. Then the erosion and dilation operations are defined as follows:

[0070] (f Θ g)(n) = min{f(n + x) - g(x)}, x ∈ D[g], n = (1, 2, …, N)

[0071]

[0072] Among them, (f Θ g)(n) is the result of the erosion operation; f(n + x) is the signal value after moving x steps to the right starting from position n; f(n - x) is the signal value after moving x steps to the left starting from position n; g(x) is the structural element sequence; is the result of the dilation operation; D[g] is the domain of the structural element sequence.

[0073] The definitions of the morphological opening and closing operations are as follows:

[0074]

[0075] Among them, is the opening operation, and · is the closing operation. The opening operation is to perform erosion first and then dilation, and the closing operation is to perform dilation first and then erosion.

[0076] The opening operation derived from the erosion and dilation operations can suppress the spikes in the curve and remove the thin protrusions on the curve, making the curve smoother; the closing operation can fill the valleys in the signal waveform and also achieve the purpose of smoothing the curve. By comparing the filtering effects of morphological erosion, dilation, opening operation, closing operation, opening-closing operation, closing-opening operation, and composite operation, it is concluded that the composite operation in the average combination form of the opening-closing operation and the closing-opening operation filters has the best filtering effect. This is because the expansibility of the opening operation and the contractility of the closing operation cause statistical offsets in both the opening-closing and closing-opening operations. The output amplitude of the opening-closing filter is small, while the output amplitude of the closing-opening filter is large. Using any one of these combination forms alone for filtering cannot obtain an ideal filtering effect. To overcome this defect, subsequent scholars took the arithmetic mean of the closing-opening and opening-closing operators as the final filtering result and constructed a morphological composite filter (Combination morphological filter, abbreviated as: CMF) for noise suppression.

[0077] In the embodiments of the present invention, the composite filter includes a morphological opening-closing (OC) maximum filter and a morphological closing-opening (CO) minimum filter. Specifically, for a discrete input signal and a multi-structuring element sequence, the morphological opening-closing (OC) maximum filter and the morphological closing-opening (CO) minimum filter are defined as follows:

[0078] φ OC [f(n)] = max(OCg1, OCg2, …, OCg p )

[0079] φ CO [f(n)] = min(COg1, COg2, …, COg p )

[0080]

[0081] Wherein, φ OC [f(n)] is the morphological opening-closing maximum filtering signal; φ CO [f(n)] is the morphological closing-opening minimum filtering signal; OCg i is the morphological opening-closing signal; COg i is the morphological closing-opening signal.

[0082] Morphological operators have an important influence on the noise suppression effect. Similarly, structuring elements play the role of a filtering window or a reference template in morphological operations and also determine the final filtering effect. Commonly used structuring elements in morphology include linear, semi-circular, triangular, circular, flat, etc. In the present invention, the filtering effects of the above several structuring elements are compared, and it is found that the filtering effect of the semi-circular structuring element is relatively good.

[0083] Taking the semi-circular structuring element as an example, Figure 2 is a schematic diagram of the erosion operation process of a semi-circular structuring element provided by the embodiments of the present invention. As Figure 2 shown, the upper left figure is a schematic diagram of a one-dimensional multi-valued power signal, where the horizontal axis x represents the position of the signal and the vertical axis f represents the value of the signal. The upper right figure is a schematic diagram of the semi-circular structuring element, where the horizontal axis x represents the position of the signal and the vertical axis f represents the value of the signal. Figure 2 The two lower-middle figures show the process of the erosion operation. The lower left figure shows the process of the interaction between the semi-circular structuring element and the one-dimensional multi-valued power signal during the erosion operation. The horizontal axis s is the position of the structuring element, and the vertical axis f represents the value of the signal; in the lower right figure, the horizontal axis s represents the position of the structuring element, and the vertical axis f represents the value of the signal. The dashed line represents the schematic diagram of the signal value of the one-dimensional multi-valued power signal before the erosion operation, and the solid line represents the schematic diagram of the signal value of the operation result after the erosion operation. The erosion operation can remove the spikes and noise in the signal and retain the main features of the signal.

[0084] Taking the semi-circular structural element as an example, Figure 3 is a schematic diagram of the dilation operation process of a semi-circular structural element provided by an embodiment of the present invention. As Figure 3 shown, the horizontal axis s of the left figure is the position of the element, corresponding to the sampling points of the one-dimensional signal, and the vertical axis f is the signal intensity or value at each sampling point. The solid line represents the schematic diagram of the one-dimensional multi-value power signal, the dashed line parallel to the horizontal axis s is the maximum value of the power signal, and the semi-circular dashed line represents the structural element. The horizontal axis s of the right figure is the position of the element, corresponding to the sampling points of the one-dimensional signal, and the vertical axis f is the signal intensity or value at each sampling point. The solid line represents the schematic diagram of the signal value of the operation result after the dilation operation, and the dashed line represents the schematic diagram of the signal value of the one-dimensional multi-value power signal before the dilation operation for comparison. The dilation operation can fill the depressions and gaps in the signal, making the signal more plump. This helps to enhance the main features of the signal and remove noise in some cases.

[0085] In the technical solution provided by the embodiment of the present invention, the original synchronous vector measurement data of the thermal power unit is obtained; through a preset sliding window data area, the original synchronous vector measurement data is subjected to signal conversion to generate symmetric signal data; the symmetric signal data is subjected to data preprocessing to generate preprocessed low-frequency oscillation signal data; through a pre-constructed composite filter, the preprocessed low-frequency oscillation signal data is filtered and denoised to generate low-frequency filtered signal data. The composite filter is constructed based on morphology, can detect low-frequency oscillation information in real time, realizes the distinction and discrimination between low-frequency oscillation data and normal load fluctuations, and filters the low-frequency oscillation data, effectively eliminating various noise signals, with a wide application range, improving the filtering accuracy rate; controlling the calculation amount, improving the stability and reliability of the calculation result, thereby providing an effective data basis for the subsequent early warning and identification of low-frequency oscillations.

[0086] Figure 4 is a flowchart of another low-frequency oscillation data filtering method for a thermal power unit provided by an embodiment of the present invention. As Figure 4 shown, the method includes:

[0087] Step 201, obtain the original PMU data of the thermal power unit.

[0088] In the embodiment of the present invention, each step is executed by a low-frequency oscillation data filtering device of the thermal power unit.

[0089] The wide-area measurement system (WAMS) based on PMU can measure information such as voltage phasors, current phasors, power, and frequency at each measuring point of the power grid.

[0090] In the embodiment of the present invention, the original PMU data includes active power data.

[0091] Step 202, obtain the input load command signal.

[0092] In an embodiment of the present invention, the load command signal is a load change signal controlled by a user or a power grid in the system, and usually needs to be obtained by combining the operating state of the system, the load curve, or other sensor data.

[0093] Step 203: Determine whether the state of the load command signal is available. If so, execute Step 204; if not, execute Step 205.

[0094] In an embodiment of the present invention, when the load command signal cannot be collected in real time or the command changes and cannot be determined, the state of the load command signal is unavailable. Specifically, if the state of the load command signal is available, it indicates that the load command signal is reliable, and the subsequent inference of the low-frequency oscillation characteristics can be performed through the load command information, and Step 204 is continued; if the state of the load command signal is unavailable, it indicates that the load command signal is unreliable, and other methods need to be used for the subsequent inference of the low-frequency oscillation characteristics, and Step 205 is continued.

[0095] Step 204: Subtract the active power data in the sliding window data area from the load command signal to generate symmetric signal data, and continue to execute Step 207.

[0096] In an embodiment of the present invention, the power signal during the low-frequency oscillation process mixes oscillation information and the power change of the unit itself in response to the load command, resulting in a complex data curve feature. Therefore, it is necessary to remove the power change caused by the load command, convert the low-frequency oscillation signal into a symmetric signal, so as to highlight the signal feature, reduce the identification difficulty, and improve the identification accuracy. Specifically, if the load command signal is reliable, subtract the active power data in the sliding window data area from the load command signal, convert the collected frequency signal into symmetric signal data, and continue to execute Step 207.

[0097] Step 205: Calculate the extreme values of the active power data in the sliding window data area, and determine the upper and lower envelope lines of the sliding window data area according to the extreme values of the active power.

[0098] In an embodiment of the present invention, the power signal during the low-frequency oscillation process mixes oscillation information and the power change of the unit itself in response to the load command, resulting in a complex data curve feature. Therefore, it is necessary to remove the power change caused by the load command, convert the low-frequency oscillation signal into a symmetric signal, so as to highlight the signal feature, reduce the identification difficulty, and improve the identification accuracy. Specifically, if the load command signal is unreliable, since the load command changes relatively slowly, the extreme values of the PMU active power data in the sliding window data area can be obtained by fixing the sliding window length, so as to obtain the upper and lower envelope lines of the data in the sliding window data area.

[0099] Step 206: Generate symmetric signal data based on the actual power values of the upper and lower envelope lines and the mean of the upper and lower envelope lines.

[0100] Specifically, perform interpolation processing on the upper and lower envelope lines, obtain the mean of the upper and lower envelope lines, subtract the actual power values of the upper and lower envelope lines from the mean of the upper and lower envelope lines, and finally obtain symmetric signal data symmetric about the x-axis for subsequent identification and analysis.

[0101] Step 207: Detect abnormal data in the symmetric signal data, remove the abnormal data, and generate the symmetric signal data after cleaning.

[0102] In the embodiment of the present invention, data verification errors and transmission failures may occur during the acquisition and transmission processes, resulting in obviously unreasonable data in the signal. Such abnormal data must be removed. The inspection of abnormal data generally uses the 3δ discrimination:

[0103] |x i -μ|≥3δ

[0104] where x i is the symmetric signal data, μ is the mean of the symmetric signal data, and δ is the standard deviation of the symmetric signal data.

[0105] Specifically, through the 3δ discrimination method, screen out the abnormal data from the symmetric signal data, remove the screened abnormal data from the symmetric signal, complete data cleaning, and generate the symmetric signal data after cleaning.

[0106] Step 208: Process the missing values in the symmetric signal data after cleaning to generate the preprocessed low-frequency oscillation signal data.

[0107] In the embodiment of the present invention, for the symmetric signal data after removing the abnormal data, fill in the missing values. The filling of the missing data can use a simple linear interpolation method or a complex linear model to process. For the case of a large amount of data loss, it cannot be filled, and the original data should be segmented. When the number of interpolation points is small, it can be directly realized by taking the normal sampling value in front of it.

[0108] Step 209: Generate a morphological opening-closing maximum filter signal based on the preprocessed low-frequency oscillation signal data and a preset structural element sequence through a morphological opening-closing maximum filter.

[0109] Specifically, through the following morphological opening-closing maximum filter, calculate the preprocessed low-frequency oscillation signal data and the preset structural element sequence to generate a morphological opening-closing maximum filter signal.

[0110] φ OC [f(n)]=max(OCg1,OCg2,…,OCg p)

[0111]

[0112] Among them, φ OC [f(n)] is the morphological opening-closing maximum filtering signal, and OCg i is the morphological opening-closing signal, f is the low-frequency oscillation signal data, and g i is the structural element sequence, is the opening operation, and · is the closing operation.

[0113] Step 210: Generate a morphological closing-opening minimum filtering signal through a morphological closing-opening minimum filter according to the preprocessed low-frequency oscillation signal data and a preset structural element sequence.

[0114] Specifically, calculate the preprocessed low-frequency oscillation signal data and the preset structural element sequence through the following morphological closing-opening minimum filter to generate a morphological closing-opening minimum filtering signal.

[0115] φ CO [f(n)] = min(COg1, COg2, …, COg p )

[0116]

[0117] Among them, φ CO [f(n)] is the morphological closing-opening minimum filtering signal, COg i is the morphological closing-opening signal, f is the low-frequency oscillation signal data, and g i is the structural element sequence, is the opening operation, and · is the closing operation.

[0118] Step 211: Generate low-frequency filtered signal data according to the morphological opening-closing maximum filtering signal and the morphological closing-opening minimum filtering signal.

[0119] Specifically, generate low-frequency filtered signal data by calculating the mean value of the morphological opening-closing maximum filtering signal and the morphological closing-opening minimum filtering signal. Among them, CMF[f(n)] is the low-frequency filtered signal data, φ CO [f(n)] is the morphological closing-opening minimum filtering signal, φ OC [f(n)] is the morphological opening-closing maximum filtering signal.

[0120] Step 212: Suppress the constructed noisy signal through a composite filter to generate a sample filtered signal.

[0121] In the embodiments of the present invention, to verify the effectiveness of mathematical morphology filtering, a noisy signal is constructed, and a semi-circular composite filter CMF is used to suppress the noise. The noisy signal is as follows:

[0122] y = 1.2e -0.4t cos(2π×0.5t)+0.8e -t cos(2π×1.5t+π)+e -1.2t cos(2π×0.9t)+ω(t)

[0123] where y is the constructed noisy signal; ω(t) is the mixed Gaussian white noise with signal-to-noise ratios of 20 db and 30 db respectively, and a semi-circular structural element with a structural element length of 5 and a size radius of 0.01 unit length is used for filtering; t is time.

[0124] Specifically, the noisy signal is input into the composite filter for suppression processing, that is: filtering and denoising processing, and the sample filtered signal is output.

[0125] Figure 5 It is a comparison schematic diagram of the noise suppression effect of a semi-circular CMF filter provided by the embodiments of the present invention. As Figure 5 shown, the first figure is the sample amplitude schematic diagram of the ideal signal, the horizontal axis is the sample (0 - 1000), and the vertical axis is the amplitude (0 - 1); the second figure is the sample amplitude schematic diagram of the noisy signal, the horizontal axis is the sample (0 - 1000), and the vertical axis is the amplitude (0 - 1); the third figure is the sample amplitude schematic diagram of the sample filtered signal after noise suppression by the semi-circular CMF filter, the horizontal axis is the sample (0 - 1000), and the vertical axis is the amplitude (0 - 1). It can be seen that the filtering effect of the semi-circular CMF filter in this application is very close to the ideal signal.

[0126] Step 213: Generate a filtering coefficient according to the sample filtered signal and the noisy signal.

[0127] In the embodiments of the present invention, to quantitatively evaluate the filtering effect of morphology, a filtering coefficient E is introduced, and the definition is as follows:

[0128]

[0129] where E is the filtering coefficient, N is the total number of sampling points, y i0 is the noisy signal, and y i is the sample filtered signal.

[0130] In the embodiments of the present invention, the smaller the filtering coefficient E, the closer the filtered signal is to the signal without added noise, and the better the filtering effect. In practical applications, after calculation, the filtering coefficient of the signal filtered by the CMF filter is 0.0018, which has a very good filtering effect.

[0131] Step 214: According to the filtering coefficient, adjust and update the parameters of the composite filter to generate an updated composite filter.

[0132] In the embodiment of the present invention, if the filtering coefficient is greater than a preset coefficient threshold, the parameters of the composite filter are adjusted and updated so that the filtered signal output by the composite filter is closer to the ideal signal until the filtering coefficient is less than the preset coefficient threshold, and an updated composite filter is generated.

[0133] Furthermore, after filtering the low-frequency oscillation data in practical applications, the parameters of the composite filter can also be optimized based on historical data to generate a composite filter with better denoising effect.

[0134] The following uses a specific example to illustrate the actual application process of the composite filter:

[0135] When the active power of a certain unit drops from 394.893 MW, power oscillation occurs, lasting for about 5 minutes, with an oscillation amplitude of 362.2 MW - 408.8 MW and an oscillation frequency of 1 Hz. There is high-frequency noise in the unit power signal, and the measured active power curve of the unit is in a non-stationary state. Before the oscillation starts, the unit operates stably at 400 MW, and after the oscillation ends, the unit operates at 380 MW. During the oscillation process, the power signal also incorporates the load drop process, and the entire curve is not symmetric about the horizontal axis. The PMU data is processed by the semi-circular CMF filter in this application. The semi-circular CMF filter in this application is sensitive to information such as noise and asymmetry, avoiding problems such as noise and asymmetry, and providing a good data basis for subsequent low-frequency oscillation identification.

[0136] It should be noted that in the technical solution of this application, the acquisition, storage, use, processing, etc. of data all comply with the relevant regulations of laws and regulations. The user information in the embodiments of this application is obtained through legal and compliant channels, and the acquisition, storage, use, processing, etc. of user information are authorized and consented by the customer.

[0137] It should be noted that the information collected in this application is information and data authorized by the user or fully authorized by all parties, and the processing of related data such as collection, storage, use, processing, transmission, provision, disclosure, and application complies with the relevant laws, regulations, and standards of relevant countries and regions, takes necessary confidentiality measures, does not violate public order and good customs, and provides corresponding operation entrances for users to choose to authorize or refuse.

[0138] It should be noted that the technical solution provided in this application provides corresponding operation entrances for users to choose to agree or refuse the results of automated decision-making; if the user chooses to refuse, the expert decision-making process will be entered.

[0139] In the technical solution of the low-frequency oscillation data filtering method for a thermal power unit provided by an embodiment of the present invention, the original synchronous vector measurement data of the thermal power unit is obtained; through a preset sliding window data area, the original synchronous vector measurement data is subjected to signal conversion to generate symmetric signal data; the symmetric signal data is subjected to data preprocessing to generate preprocessed low-frequency oscillation signal data; through a pre-constructed composite filter, the preprocessed low-frequency oscillation signal data is filtered and denoised to generate low-frequency filtered signal data. The composite filter is constructed based on morphology, can detect low-frequency oscillation information in real time, realizes the distinction and discrimination between low-frequency oscillation data and normal load fluctuations, filters the low-frequency oscillation data, effectively eliminates various noise signals, has a wide application range, improves the filtering accuracy; controls the calculation amount, improves the stability and reliability of the calculation results, and thus provides an effective data basis for subsequent early warning and identification of low-frequency oscillations.

[0140] Figure 6 FIG. is a structural schematic diagram of a low-frequency oscillation data filtering device for a thermal power unit provided by an embodiment of the present invention. This device is used to execute the above-mentioned low-frequency oscillation data filtering method for a thermal power unit, such as Figure 6 shown, the device includes: an acquisition unit 11, a signal conversion unit 12, a data preprocessing unit 13, and a filtering unit 14.

[0141] The acquisition unit 11 is used to acquire the original synchronous vector measurement data of the thermal power unit.

[0142] The signal conversion unit 12 is used to perform signal conversion on the original synchronous vector measurement data through a preset sliding window data area to generate symmetric signal data.

[0143] The data preprocessing unit 13 is used to perform data preprocessing on the symmetric signal data to generate preprocessed low-frequency oscillation signal data.

[0144] The filtering unit 14 is used to perform filtering and denoising on the preprocessed low-frequency oscillation signal data through a pre-constructed composite filter to generate low-frequency filtered signal data. The composite filter is constructed based on morphology.

[0145] In an embodiment of the present invention, the original synchronous vector measurement data includes active power data; the signal conversion unit 12 is specifically used to obtain an input load command signal; if the state of the load command signal is available, subtract the active power data in the sliding window data area from the load command signal to generate symmetric signal data; if the state of the load command signal is unavailable, perform an extreme value calculation on the active power data in the sliding window data area, and determine the upper and lower envelope lines of the sliding window data area according to the active power extreme values; generate symmetric signal data according to the actual power values of the upper and lower envelope lines and the mean values of the upper and lower envelope lines.

[0146] In an embodiment of the present invention, the data preprocessing unit 13 is specifically used to perform abnormal data detection on the symmetrical signal data, and eliminate the abnormal data to generate cleaned symmetrical signal data; perform missing value processing on the cleaned symmetrical signal data to generate preprocessed low-frequency oscillation signal data.

[0147] In an embodiment of the present invention, the composite filter includes a morphological open-closed maximum filter and a morphological closed-open minimum filter; the filtering unit 14 is specifically configured to generate a morphological open-closed maximum filtered signal based on the preprocessed low-frequency oscillation signal data and a preset structural element sequence through the morphological open-closed maximum filter; generate a morphological closed-open minimum filtered signal based on the preprocessed low-frequency oscillation signal data and a preset structural element sequence through the morphological closed-open minimum filter; and generate low-frequency filtered signal data based on the morphological open-closed maximum filtered signal and the morphological closed-open minimum filtered signal.

[0148] In the embodiment of the present invention, the apparatus further includes: a suppression unit 15 , a coefficient generation unit 16 and an update unit 17 .

[0149] The suppression unit 15 is used to suppress the constructed noisy signal through a composite filter to generate a sample filtered signal.

[0150] The coefficient generating unit 16 is configured to generate filter coefficients according to the sample filter signal and the noisy signal.

[0151] The updating unit 17 is used to adjust and update the parameters of the composite filter according to the filter coefficients to generate an updated composite filter.

[0152] In the solution of the embodiment of the present invention, original synchronous vector measurement data of the thermal power unit is obtained; signal conversion is performed on the original synchronous vector measurement data through a preset sliding window data area to generate symmetrical signal data; data preprocessing is performed on the symmetrical signal data to generate preprocessed low-frequency oscillation signal data; and filtering and denoising are performed on the preprocessed low-frequency oscillation signal data through a pre-constructed composite filter to generate low-frequency filtered signal data. The composite filter is constructed based on morphology and can detect low-frequency oscillation information in real time, distinguish and discriminate between low-frequency oscillation data and normal load fluctuations, and filter the low-frequency oscillation data, effectively eliminating various noise signals, having a wide range of applications and improving filtering accuracy. The amount of calculation is controlled, and the stability and reliability of the calculation results are improved, thereby providing an effective data basis for subsequent early warning and identification of low-frequency oscillations.

[0153] The systems, devices, modules, or units illustrated in the above embodiments may be specifically implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer device. Specifically, the computer device may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or any combination of these devices.

[0154] An embodiment of the present invention provides a computer device, including a memory and a processor. The memory is used to store information including program instructions, and the processor is used to control the execution of the program instructions. When the program instructions are loaded and executed by the processor, the steps of the above embodiments of the low-frequency oscillation data filtering method for thermal power units are implemented. For specific descriptions, reference may be made to the embodiments of the low-frequency oscillation data filtering method for thermal power units.

[0155] Reference is made below to Figure 7 , which shows a schematic structural diagram of a computer device 600 suitable for implementing the embodiments of the present application.

[0156] As Figure 7 shown, the computer device 600 includes a central processing unit (CPU) 601, which can perform various appropriate operations and processes according to the program stored in the read-only memory (ROM) 602 or the program loaded from the storage section 608 into the random access memory (RAM) 603. In the RAM 603, various programs and data required for the operation of the computer device 600 are also stored. The CPU 601, ROM 602, and RAM 603 are connected to each other via a bus 604. The input / output (I / O) interface 605 is also connected to the bus 604.

[0157] The following components are connected to the I / O interface 605: an input section 606 including a keyboard, a mouse, etc.; an output section 607 including, for example, a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker; a storage section 608 including a hard disk, etc.; and a communication section 609 including a network interface card such as a LAN card, a modem, etc. The communication section 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the I / O interface 605 as needed. A removable medium 611, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 610 as needed, so that the computer program read from it can be installed into the storage section 608 as needed.

[0158] In particular, according to an embodiment of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, an embodiment of the present invention includes a computer program product that includes a computer program tangibly embodied on a machine-readable medium, the computer program including program code for performing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 609, and / or installed from the removable medium 611.

[0159] Computer-readable media includes both permanent and non-permanent, removable and non-removable media implemented by any method or technology for storage of information such as computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read only memory (ROM), electrically erasable programmable read only memory (EEPROM), flash memory or other memory technologies, compact disc read only memory (CD-ROM), digital versatile discs (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices or any other non-transitory media that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transitory media such as modulated data signals and carrier waves.

[0160] For convenience of description, the above-described apparatus is described by dividing it into various units according to functions. Of course, when implementing the present application, the functions of each unit can be implemented in one or more pieces of software and / or hardware.

[0161] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and combinations of flows and / or blocks in the flowcharts 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 device to produce a machine such that the instructions executed by the processor of the computer or other programmable data processing device produce means for implementing the functions specified in one Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0162] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0163] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0164] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0165] The acquisition, storage, use, and processing of data in this application's technical solution comply with relevant national laws and regulations.

[0166] It should be noted that in the embodiments of the present application, certain software, components, models and other existing solutions in the industry may be mentioned. They should be regarded as exemplary. Their purpose is only to illustrate the feasibility of implementing the technical solution of the present application, but it does not mean that the applicant has or will necessarily use the solution.

[0167] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0168] This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. This application can also be practiced in a distributed computing environment where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0169] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other, and the key point of each embodiment is to illustrate the differences from other embodiments. In particular, for system embodiments, since they are basically similar to method embodiments, the description is relatively simple, and for the relevant parts, reference can be made to the description of the method embodiments.

[0170] The above are only the embodiments of this application and are not intended to limit this application. For those skilled in the art, various changes and modifications can be made to this application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of this application shall be included within the scope of the claims of this application.

Claims

1. A low-frequency oscillation data filtering method for a thermal power unit, characterized in that The method includes: Obtaining the original synchronized vector measurement data of a thermal power unit; Performing signal conversion on the original synchronized vector measurement data through a preset sliding window data area to generate symmetric signal data; Performing data preprocessing on the symmetric signal data to generate preprocessed low-frequency oscillation signal data; Performing filtering and denoising processing on the preprocessed low-frequency oscillation signal data through a pre-constructed composite filter to generate low-frequency filtered signal data, where the composite filter is constructed based on morphology.

2. The low-frequency oscillation data filtering method for a thermal power unit according to claim 1, wherein The original synchronized vector measurement data includes active power data; The performing signal conversion on the original synchronized vector measurement data through a preset sliding window to generate symmetric signal data includes: Obtaining an input load command signal; If the status of the load command signal is available, subtracting the active power data in the sliding window data area from the load command signal to generate the symmetric signal data; If the status of the load command signal is unavailable, calculating the extreme values of the active power data in the sliding window data area, and determining the upper and lower envelope lines of the sliding window data area according to the active power extreme values; Generating the symmetric signal data according to the actual power values of the upper and lower envelope lines and the mean value of the upper and lower envelope lines.

3. The low-frequency oscillation data filtering method for a thermal power unit according to claim 1, characterized in that The performing data preprocessing on the symmetric signal data to generate preprocessed low-frequency oscillation signal data includes: Performing abnormal data detection on the symmetric signal data, and removing the abnormal data to generate cleaned symmetric signal data; Performing missing value processing on the cleaned symmetric signal data to generate preprocessed low-frequency oscillation signal data.

4. The low-frequency oscillation data filtering method for a thermal power unit according to claim 1, characterized in that The composite filter includes a morphological opening-closing maximum filter and a morphological closing-opening minimum filter; The performing filtering and denoising processing on the preprocessed low-frequency oscillation signal data through a pre-constructed composite filter to generate low-frequency filtered signal data includes: Generating a morphological opening-closing maximum filtered signal through the morphological opening-closing maximum filter according to the preprocessed low-frequency oscillation signal data and a preset structural element sequence; Generating a morphological closing-opening minimum filtered signal through the morphological closing-opening minimum filter according to the preprocessed low-frequency oscillation signal data and a preset structural element sequence; Generating the low-frequency filtered signal data according to the morphological opening-closing maximum filtered signal and the morphological closing-opening minimum filtered signal.

5. The low-frequency oscillation data filtering method for a thermal power unit according to claim 1, characterized in that, The method further includes: Performing suppression processing on a constructed noisy signal through the composite filter to generate a sample filtered signal; Generating a filtering coefficient according to the sample filtered signal and the noisy signal; Adjusting and updating the parameters of the composite filter according to the filtering coefficient to generate an updated composite filter.

6. A low-frequency oscillation data filtering device for a thermal power unit, characterized in that The device includes: An acquisition unit for acquiring the original synchronized vector measurement data of a thermal power unit; A signal conversion unit for performing signal conversion on the original synchronized vector measurement data through a preset sliding window data area to generate symmetric signal data; A data preprocessing unit for performing data preprocessing on the symmetric signal data to generate preprocessed low-frequency oscillation signal data; A filtering unit, configured to perform filtering and denoising processing on the preprocessed low-frequency oscillation signal data through a pre-constructed composite filter to generate low-frequency filtered signal data, where the composite filter is constructed based on morphology.

7. The low-frequency oscillation data filtering device for a thermal power unit according to claim 6, characterized in that, The original synchronized vector measurement data includes active power data; The signal conversion unit is specifically configured to obtain an input load command signal; if the status of the load command signal is available, subtract the active power data in the sliding window data area from the load command signal to generate the symmetric signal data; if the status of the load command signal is unavailable, perform extreme value calculation on the active power data in the sliding window data area, and determine the upper and lower envelope lines of the sliding window data area according to the active power extreme values; generate the symmetric signal data according to the actual power values of the upper and lower envelope lines and the mean value of the upper and lower envelope lines.

8. The low-frequency oscillation data filtering device for a thermal power unit according to claim 6, characterized in that The data preprocessing unit is specifically configured to perform abnormal data detection on the symmetric signal data, remove the abnormal data, and generate the symmetric signal data after cleaning; perform missing value processing on the symmetric signal data after cleaning to generate the preprocessed low-frequency oscillation signal data.

9. The low-frequency oscillation data filtering device for a thermal power unit according to claim 6, characterized in that, The composite filter includes a morphological opening-closing maximum filter and a morphological closing-opening minimum filter; The filtering unit is specifically configured to generate a morphological opening-closing maximum filtered signal through the morphological opening-closing maximum filter according to the preprocessed low-frequency oscillation signal data and a preset structural element sequence; generate a morphological closing-opening minimum filtered signal through the morphological closing-opening minimum filter according to the preprocessed low-frequency oscillation signal data and a preset structural element sequence; Generate the low-frequency filtered signal data according to the morphological opening-closing maximum filtered signal and the morphological closing-opening minimum filtered signal.

10. The low-frequency oscillation data filtering device for a thermal power unit according to claim 6, characterized in that, The device further includes: A suppression unit, configured to perform suppression processing on a constructed noisy signal through the composite filter to generate a sample filtered signal; A coefficient generation unit, configured to generate a filtering coefficient according to the sample filtered signal and the noisy signal; An update unit, configured to adjust and update the parameters of the composite filter according to the filtering coefficient to generate an updated composite filter.

11. A computer-readable medium having a computer program stored thereon, characterized in that, When the program is executed by a processor, it implements the low-frequency oscillation data filtering method of the thermal power unit according to any one of claims 1 to 5.

12. A computer device, comprising a memory and a processor, the memory being used for storing information including program instructions, and the processor being used for controlling the execution of the program instructions, characterized in that, When the program instructions are loaded and executed by a processor, it implements the low-frequency oscillation data filtering method of the thermal power unit according to any one of claims 1 to 5.

13. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by a processor, it implements the low-frequency oscillation data filtering method of the thermal power unit according to any one of claims 1 to 5.

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