Power quality disturbance signal positioning method and device, equipment and storage medium

Abstract

The invention relates to a power quality disturbance signal positioning method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: acquiring an electric energy quality signal corresponding to electric energy sensing equipment; performing signal reconstruction processing on the electric energy quality signal to obtain a reconstructed electric energy quality signal; and extracting a plurality of amplitude fluctuation characteristics corresponding to the reconstructed electric energy quality signal, and performing clustering processing on each amplitude fluctuation characteristic to determine a spatial position of an electric energy quality disturbance signal, the electric energy quality disturbance signal being a signal having amplitude fluctuation in the electric energy quality signals. By adopting the method, the electric energy quality disturbance signal can be accurately positioned.

Description

Technical Field

[0001] The present application relates to the technical field of signal positioning, and in particular to a method, device, computer equipment, computer-readable storage medium and computer program product for positioning a power quality disturbance signal. Background Art

[0002] Photovoltaic power generation is a technology that uses the photovoltaic effect of semiconductor interfaces to directly convert light energy into electrical energy. The high proportion of photovoltaic power generation access has brought many challenges to the operation of the distribution network, especially in terms of power quality. Usually, the access of photovoltaic systems relies on power electronic converters. During the grid connection process, power electronic converters may introduce a variety of power quality problems, such as harmonics, voltage fluctuations, frequency fluctuations, and flicker. In addition, photovoltaic power generation is intermittent and volatile, and its output power is greatly affected by factors such as weather conditions and sunshine intensity, which can easily lead to instability of grid voltage and frequency, and then cause power quality disturbances. These disturbances not only affect the power consumption experience of end users, but may also pose a threat to the operating safety of power equipment and the overall stability of the system. Therefore, in order to ensure the power quality of the distribution network, the monitoring and positioning of power quality disturbances are particularly important.

[0003] In traditional technologies, disturbance location is mainly performed through rule-based analysis methods, model-based analysis methods, and signal processing-based analysis methods. However, in a complex power grid environment with a high proportion of photovoltaic access, the operation state of the distribution network is more complicated, and traditional disturbance location methods are difficult to accurately locate power quality disturbance signals. Summary of the invention

[0004] Based on this, it is necessary to provide a method, device, computer equipment, computer-readable storage medium and computer program product for locating power quality disturbance signals, which can accurately locate power quality disturbance signals, in order to solve the above technical problems.

[0005] In a first aspect, the present application provides a method for locating a power quality disturbance signal. The method comprises:

[0006] Obtaining power quality signals corresponding to power sensing equipment;

[0007] Performing signal reconstruction processing on the power quality signal to obtain a reconstructed power quality signal;

[0008] Extract multiple amplitude fluctuation features corresponding to the reconstructed power quality signal, and perform clustering processing on each of the amplitude fluctuation features to determine the spatial position of the power quality disturbance signal, wherein the power quality disturbance signal is a signal with amplitude fluctuation in the power quality signal.

[0009] In one embodiment, the amplitude fluctuation feature is a spectrum feature or a transmission path feature, and clustering the fluctuation features to determine the spatial position of the power quality disturbance signal includes:

[0010] Performing clustering processing on each of the frequency spectrum features in the multiple amplitude fluctuation features to obtain an initial clustering result;

[0011] Performing clustering processing on the initial clustering result according to each of the transmission path features in the multiple amplitude fluctuation features to obtain the clustering result;

[0012] The cluster center in the clustering result is determined as the spatial position.

[0013] In one of the embodiments, the spectrum feature is determined according to the spectrum scale, signal transmission rate, sampling time window scale, sampling delay time and preset disturbance parameters of the reconstructed power quality signal;

[0014] The transmission path characteristics are determined according to the signal transmission distance, the transformation parameters and the transmission parameters of the power quality disturbance signal during the reconstruction process.

[0015] In one embodiment, obtaining a power quality signal corresponding to a power sensor device includes:

[0016] Acquire the original power quality signal monitored by the power sensor device, and perform multi-scale decomposition processing on the original power quality signal to obtain the decomposed original power quality signal;

[0017] The high-frequency signal and the low-frequency signal in the decomposed original power quality signal are denoised using a noise coefficient judgment threshold to obtain the power quality signal.

[0018] In one embodiment, the performing signal reconstruction processing on the power quality signal to obtain a reconstructed power quality signal includes:

[0019] generating a measurement matrix using the power quality signal;

[0020] Obtaining an observation matrix of a sparse vector corresponding to the power quality signal according to the measurement matrix;

[0021] The reconstructed power quality signal is obtained according to the observation matrix of the sparse vector and the preset reconstruction parameters.

[0022] In one of the embodiments, before generating a measurement matrix using the power quality signal, the method further includes:

[0023] Generating a time series corresponding to the power quality signal;

[0024] Eliminating null values ​​and repeated values ​​in the time series to obtain a power quality signal after redundancy processing;

[0025] The step of generating a measurement matrix using the power quality signal comprises:

[0026] The measurement matrix is ​​generated using the redundantly processed power quality signal.

[0027] In a second aspect, the present application also provides a device for locating a power quality disturbance signal. The device comprises:

[0028] An acquisition module, used for acquiring a power quality signal corresponding to a power sensor device;

[0029] A reconstruction module, used for performing signal reconstruction processing on the power quality signal to obtain a reconstructed power quality signal;

[0030] A determination module is used to extract multiple amplitude fluctuation features corresponding to the reconstructed power quality signal, and cluster each of the amplitude fluctuation features to determine the spatial position of the power quality disturbance signal, wherein the power quality disturbance signal is a signal with amplitude fluctuation in the power quality signal.

[0031] In a third aspect, the present application further provides a computer device, wherein the computer device comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the method described in the first aspect are implemented.

[0032] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of the method described in the first aspect are implemented.

[0033] In a fifth aspect, the present application further provides a computer program product, wherein the computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of the method described in the first aspect are implemented.

[0034] In the above-mentioned method, device, computer equipment, computer-readable storage medium and computer program product for locating power quality disturbance signals, the terminal first obtains the power quality signal corresponding to the power sensor device, then reconstructs the power quality signal to obtain a reconstructed power quality signal, and then extracts multiple amplitude fluctuation characteristics corresponding to the reconstructed power quality signal, and clusters each amplitude fluctuation characteristic to determine the spatial position of the power quality disturbance signal. Since the power quality signal is reconstructed, a reconstructed power quality signal that can eliminate signal interference and contain information such as frequency, amplitude and phase of the power quality signal is obtained, so that multiple amplitude fluctuation characteristics can be extracted from the reconstructed power quality signal, overcoming the limitations of a single fluctuation characteristic, and can identify complex and multiple power quality disturbance signals, and then can locate the power quality disturbance signal according to multiple amplitude fluctuation characteristics, can achieve accurate positioning of the power quality disturbance signal, and improve the accuracy of positioning the power quality disturbance signal. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments of the present application or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0036] FIG1 is a diagram showing an application environment of a method for locating a power quality disturbance signal in one embodiment;

[0037] FIG2 is a schematic flow chart of a method for locating a power quality disturbance signal in one embodiment;

[0038] FIG3 is a schematic diagram of a flow chart of step 203 in one embodiment;

[0039] FIG4 is a schematic diagram of a flow chart of step 201 in one embodiment;

[0040] FIG5 is a schematic diagram of a flow chart of step 202 in one embodiment;

[0041] FIG6 is a schematic flow chart of a method for locating a power quality disturbance signal in another embodiment;

[0042] FIG7 is a structural block diagram of a device for locating a power quality disturbance signal in one embodiment;

[0043] FIG. 8 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0044] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0045] In the application of locating power quality disturbance signals, traditional technologies mainly use rule-based analysis methods, model-based analysis methods and signal processing-based analysis methods to locate disturbances through signal features. The signal features extracted by these methods are relatively simple and can only be applied to single disturbance problems. However, in a complex power grid environment with a high proportion of photovoltaic access, the operating state of the distribution network is more complex, the types of power quality signals generated are many, and the amount of data is huge. It is difficult for traditional methods to efficiently process and analyze power quality signals. Moreover, the power quality disturbance signals introduced by the photovoltaic power generation system have complex characteristics of multiple frequencies and multiple modes. The accuracy of traditional methods in identifying and distinguishing different types of power quality disturbance signals is low, and it is difficult to meet the needs of accurately locating power quality disturbance signals in complex power grid environments. In view of this, the present application proposes a method for locating power quality disturbance signals that can accurately locate power quality disturbance signals.

[0046] The method for locating a power quality disturbance signal provided in an embodiment of the present application can be applied in an application environment as shown in FIG1. ​​The terminal 102 communicates with the power sensor device 104 through a network. The terminal 102 obtains a power quality signal corresponding to the power sensor device 104, and then the terminal 102 performs signal reconstruction processing on the power quality signal to obtain a reconstructed power quality signal. Then, the terminal 102 extracts multiple amplitude fluctuation features corresponding to the reconstructed power quality signal, and performs clustering processing on each amplitude fluctuation feature to determine the spatial position of the power quality disturbance signal, and the power quality disturbance signal is a signal with amplitude fluctuation in the power quality signal. The terminal 102 can be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, Internet of Things devices and portable wearable devices, and the Internet of Things devices can be smart speakers, smart TVs, smart air conditioners, smart car-mounted devices, etc. The portable wearable device can be a smart watch, a smart bracelet, a head-mounted device, etc. The power sensor device 104 can include a current sensor, a voltage sensor, a transformer, a power meter, etc.

[0047] In an exemplary embodiment, as shown in FIG2 , a method for locating a power quality disturbance signal is provided, which is described by taking the method applied to the terminal in FIG1 as an example, and includes the following steps:

[0048] Step 201: Acquire a power quality signal corresponding to a power sensor device.

[0049] Among them, the power sensing device refers to the equipment used to monitor and measure the parameters of the power system, mainly including sensors, signal processing and data acquisition components, and data analysis software, such as voltage sensors and current sensors. The power sensing device can be applied to the fields of smart grid, energy management and power monitoring. The power quality signal refers to the power signal monitored and measured by the power sensing device, and the power quality of the power equipment can be monitored through the power signal. For example, whether the operating state of the power equipment is stable can be determined by whether the voltage or current fluctuates. It can be understood that in the power monitoring scenario, there can be multiple power sensing devices, each of which can continuously monitor the signal, or can also periodically monitor the signal, so each power sensing device can correspond to multiple power quality signals. Optionally, the power quality signal can be a continuous signal, or the power quality signal can also be a discrete signal.

[0050] Optionally, in this embodiment, the terminal may receive a power quality signal uploaded by the power sensor device according to a preset period; or, the terminal may also send a power quality signal acquisition instruction to the power sensor device to instruct the power sensor device to upload the power quality signal.

[0051] As an optional implementation, the power quality signal monitored by the power sensor device may contain a noise signal. Therefore, after receiving the original power quality signal sent by the power sensor device, the terminal may also perform denoising on the received original power quality signal and use the denoised original power quality signal as the power quality signal.

[0052] Step 202: Perform signal reconstruction processing on the power quality signal to obtain a reconstructed power quality signal.

[0053] Among them, signal reconstruction processing refers to the process of recovering the entire signal from a known partial signal. This process includes steps such as sampling, interpolation and filtering, thereby achieving data compression and eliminating signal interference.

[0054] In this embodiment, the terminal can first sample the power quality signal to obtain a sampled power quality signal, then use the sampled power quality signal to perform signal interpolation processing to restore the approximate value of the original power quality signal, and then use a low-pass filter to remove the high-frequency signal in the approximate value of the original power quality signal to restore the complete power quality signal, and use the restored complete power quality signal as the reconstructed power quality signal.

[0055] Step 203, extract multiple amplitude fluctuation features corresponding to the reconstructed power quality signal, and perform clustering processing on each amplitude fluctuation feature to determine the spatial position of the power quality disturbance signal, where the power quality disturbance signal is a signal with amplitude fluctuation in the power quality signal.

[0056] The amplitude fluctuation feature refers to the characteristic information of the power quality signal with a relatively large amplitude change. For example, if the power quality signal is a voltage, the amplitude fluctuation feature can indicate a sudden increase or decrease in the voltage value. It should be noted that by extracting different signal features from the reconstructed power quality signal, multiple amplitude fluctuation features can be obtained. For example, the amplitude fluctuation feature can be an energy feature, an amplitude feature, a phase feature, a spectrum feature, a transmission path feature, etc.

[0057] Among them, clustering processing refers to a processing method for classifying data according to data features when the category is uncertain. Clustering processing can divide a data set into different classes or clusters according to a specific standard. The similarity of data objects in the same cluster is as large as possible, and the difference of data objects in different clusters is as large as possible. In this embodiment, a clustering algorithm can be used to perform clustering processing on multiple amplitude fluctuation features. Optionally, the clustering algorithm can be a k-means algorithm, a hierarchical clustering algorithm, etc., which is not limited in this embodiment.

[0058] Among them, power quality disturbance refers to the fluctuation phenomenon in the power system, where parameters such as voltage and current suddenly change or deviate from their expected values. The power quality signal that produces the fluctuation phenomenon is regarded as the power quality disturbance signal. The power quality disturbance signal may have an adverse effect on the normal operation of the power equipment, and even cause equipment failure or damage, thereby affecting the reliability and stability of the power system. Power quality disturbance signals can include harmonics, flicker, temporary sag, temporary swell, transient pulses and other types.

[0059] In this embodiment, the terminal can take the signal with peaks or troughs appearing in the envelope curve corresponding to the reconstructed power quality signal as the fluctuation signal, extract the amplitude fluctuation characteristics from the fluctuation signal through signal processing methods such as amplitude domain analysis, time domain analysis, and Fourier transform, and then use the clustering algorithm to cluster the amplitude fluctuation characteristics to obtain the clustering results, and then determine the spatial position of the power quality disturbance signal according to the clustering results to locate the power quality disturbance signal.

[0060] In the above-mentioned method for locating the power quality disturbance signal, the terminal first obtains the power quality signal corresponding to the power sensor device, then reconstructs the power quality signal to obtain the reconstructed power quality signal, and then extracts multiple amplitude fluctuation characteristics corresponding to the reconstructed power quality signal, and clusters each amplitude fluctuation characteristic to determine the spatial position of the power quality disturbance signal. Since the signal reconstruction processing is performed on the power quality signal, a reconstructed power quality signal is obtained that can eliminate signal interference and contain information such as frequency, amplitude and phase of the power quality signal, so that multiple amplitude fluctuation characteristics can be extracted from the reconstructed power quality signal, overcoming the limitations of a single fluctuation characteristic, and can identify complex and multiple power quality disturbance signals, and then the power quality disturbance signal can be located according to the multiple amplitude fluctuation characteristics, so that the accurate positioning of the power quality disturbance signal can be achieved, and the accuracy of positioning the power quality disturbance signal is improved.

[0061] In the above scenario where the amplitude fluctuation features are clustered to determine the spatial position of the power quality disturbance signal, the amplitude fluctuation features are spectrum features or transmission path features, and the spectrum features and the transmission path features can be clustered respectively, and the spatial position of the power quality disturbance signal can be determined according to the clustering results. In an exemplary embodiment, as shown in FIG3 , the above step 203 includes:

[0062] Step 301 , clustering is performed on each frequency spectrum feature in a plurality of amplitude fluctuation features to obtain an initial clustering result.

[0063] Among them, the spectrum characteristics refer to the signal characteristics related to the frequency spectrum of the power quality signal, such as the discrete type, harmonicity and convergence of the spectrum, continuous spectrum, discrete spectrum, baseband spectrum, etc. The spectrum characteristics can be used to analyze the change characteristics of the power quality signal from the frequency perspective. Among them, the initial clustering results can characterize the type information of the spectrum characteristics.

[0064] As an optional implementation, the spectrum feature may be determined according to the spectrum scale of the reconstructed power quality signal, the signal transmission rate, the sampling time window scale, the sampling delay time, and the preset disturbance parameters.

[0065] Among them, the spectrum characteristics can be expressed as:

[0066]

[0067] Where D represents the spectrum scale of the power quality disturbance signal, Represents the signal transmission rate, represents the preset disturbance parameters, represents the sampling time window scale of the reconstructed power quality signal, Represents the sampling delay time of the reconstructed power quality signal.

[0068] In this embodiment, the terminal may perform clustering processing on each spectrum feature by using a clustering algorithm to obtain an initial clustering result, so as to determine the signal in which the spectrum information in the reconstructed power quality signal fluctuates according to the initial clustering result.

[0069] Step 302: performing clustering processing on the initial clustering results according to each transmission path feature in the plurality of amplitude fluctuation features to obtain a clustering result.

[0070] Among them, the transmission path characteristics may include characteristic impedance, delay, multipath effect, fast fading and slow fading, etc. Characteristic impedance refers to the resistance of the transmission line to current limiting; delay refers to the time required for the signal to be transmitted; multipath effect refers to the signal passing through multiple paths during the propagation process to reach the receiving end, resulting in changes in signal strength and phase; fast fading is the rapid change of signal amplitude caused by multipath effect, while slow fading is the long-term signal attenuation caused by the obstruction of larger objects (such as buildings).

[0071] The transmission path characteristics may be determined according to the signal transmission distance, the transformation parameters and the transmission parameters of the power quality disturbance signal during the reconstruction process.

[0072] Among them, the transmission path characteristics can be expressed as:

[0073]

[0074] in, represents the transformation parameters of the power quality disturbance signal during the reconstruction process, It represents the transmission parameter of the power quality disturbance signal during the reconstruction process, and d represents the signal transmission distance.

[0075] In this embodiment, the terminal can use a clustering algorithm to cluster multiple transmission path features. During the clustering process, new cluster centers are obtained through continuous iteration until the distance within the same cluster is the shortest and the distance between different clusters is the farthest, and the clustering results are obtained to determine the signal with transmission path fluctuations from the signal with spectrum information fluctuations based on the clustering results.

[0076] Step 303: determine the cluster center in the clustering result as the spatial position.

[0077] It can be understood that the clustering result can represent a signal in which the spectrum information in the reconstructed power quality signal fluctuates and the transmission path fluctuates. The clustering result can be used to characterize the disturbance source that generates the power quality disturbance signal. Therefore, the clustering center can be determined as the spatial position.

[0078] In this embodiment, the terminal may determine the cluster center in the clustering result as the location of the disturbance source generating the power quality disturbance signal, thereby determining the cluster center as the spatial location of the power quality disturbance signal.

[0079] As a possible implementation, after obtaining the clustering result, the node information of the power equipment that is the signal source of the power quality disturbance signal may be calculated according to the cluster center, so as to obtain the spatial position according to the node information.

[0080] In this embodiment, the terminal obtains an initial clustering result by clustering each spectral feature in a plurality of amplitude fluctuation features, and then obtains a clustering result by clustering the initial clustering result according to each transmission path feature in the plurality of amplitude fluctuation features. Since the clustering result can represent a signal in which the spectral information in the reconstructed power quality signal fluctuates and the transmission path fluctuates, the disturbance source generating the power quality disturbance signal can be accurately determined according to the clustering center, and the clustering center is determined as the spatial position of the power quality disturbance signal, so that the power quality disturbance signal can be accurately located.

[0081] In the above scenario of obtaining the power quality signal corresponding to the power sensor device, the terminal can perform denoising on the original power quality signal and determine the original power quality signal after denoising as the power quality signal corresponding to the power sensor device. In an exemplary embodiment, as shown in FIG4 , the above step 201 includes:

[0082] Step 401, obtaining an original power quality signal monitored by a power sensor device, and performing multi-scale decomposition processing on the original power quality signal to obtain a decomposed original power quality signal.

[0083] Among them, the original power quality signal is the power quality signal monitored by the power sensor device. It can be understood that in the process of the power sensor device monitoring the power equipment, due to the noise generated by the internal components of the power equipment during operation, or the atmospheric noise and rainfall noise in the external environment, or the noise caused by the poor operation of the power system, there will be noise interference signals in the monitored original power quality signal. Since the noise interference signal will cause signal distortion, affect the accuracy and stability of the signal, or cause equipment failure, resulting in the problem of equipment performance degradation, therefore, before analyzing and processing the original power quality signal, the noise signal of the original power quality signal can be denoised.

[0084] Among them, multi-scale decomposition processing refers to decomposing the original power quality signal into multiple frequency components, so that the high-frequency signal and the low-frequency signal are separated, which facilitates more accurate noise removal.

[0085] Among them, the original power quality signal can be expressed as:

[0086]

[0087] in, Represents the raw power quality signal, Represents a pure power quality signal, represents the noise interference signal, and k represents the number of samples in the original power quality signal sequence.

[0088] In this embodiment, the terminal can obtain the original power quality signal transmitted by the power sensor device through the transmission network, and then use the wavelet decomposition algorithm to perform multi-scale decomposition processing on the original power quality signal, separate the high-frequency signal and the low-frequency signal in the original power quality signal, and obtain the decomposed original power quality signal.

[0089] Step 402: De-noising the high-frequency signal and the low-frequency signal in the decomposed original power quality signal using the noise coefficient judgment threshold to obtain a power quality signal.

[0090] It should be noted that the denoising factor during denoising needs to be greater than the amplitude of the noise interference signal coefficient. Therefore, the noise coefficient determination threshold can be set according to the amplitude of the noise interference signal coefficient.

[0091] In this embodiment, the decomposed original power quality signal can be de-noised by combining the wavelet transform method to obtain the power quality signal. Therefore, the noise coefficient judgment threshold can be determined according to the wavelet transform and the amplitude of the noise interference signal coefficient.

[0092] Among them, wavelet transform can be expressed as:

[0093]

[0094] Where a represents the signal scaling parameter, b represents the signal coordinate translation parameter, and t represents the sampling period of the power quality signal. represents the wavelet basis function.

[0095] The noise factor judgment threshold can be expressed as:

[0096]

[0097] in, represents the noise factor judgment threshold, represents the detail factor, represents the standard deviation of the judgment threshold, Represents the noise fluctuation amplitude parameter.

[0098] In this embodiment, the terminal can determine the noise coefficient judgment threshold in advance based on the amplitude of the noise interference signal coefficient and the wavelet transform, and then use the noise coefficient judgment threshold to remove the high-frequency signal and the low-frequency signal in the decomposed original power quality signal, thereby realizing denoising processing of the original power quality signal.

[0099] In an embodiment of the present application, the terminal obtains an original power quality signal monitored by an electric power sensor device, and performs multi-scale decomposition processing on the original power quality signal to obtain a decomposed original power quality signal. Since the high-frequency signal and the low-frequency signal are separated in the decomposed original power quality signal, the high-frequency signal and the low-frequency signal in the decomposed original power quality signal are denoised using a noise coefficient judgment threshold, so that noise interference signals of different frequencies can be removed, thereby improving the accuracy of the denoising processing and thus improving the accuracy of the obtained power quality signal.

[0100] In the above scenario of performing signal reconstruction processing on the power quality signal to obtain the reconstructed power quality signal, the reconstructed power quality signal can be obtained by constructing a measurement matrix and using the measurement matrix. In an exemplary embodiment, as shown in FIG5 , the above step 202 includes:

[0101] Step 501: Generate a measurement matrix using a power quality signal.

[0102] Among them, the measurement matrix refers to a matrix of a specific size, through which the high-dimensional signal can be projected into a low-dimensional space, while reducing the amount of data and retaining the main characteristic information of the signal. In the process of signal reconstruction, the measurement matrix can be used to obtain the observation matrix corresponding to the power quality signal through projection, and then the sparse reconstruction algorithm is used to obtain the reconstructed power quality signal from the observation matrix. It should be noted that the measurement matrix must meet certain mathematical properties to ensure the effect of signal reconstruction. For example, the measurement matrix needs to be orthogonal to the sparse basis and meet consistency to ensure that the original signal can be reconstructed from the low-dimensional observation matrix.

[0103] In this embodiment, the terminal can use the power quality signal to generate a two-dimensional measurement matrix, wherein each row in the two-dimensional measurement matrix represents a different power device node, and each column represents the power quality signal at different time points corresponding to each power device node. The two-dimensional measurement matrix can satisfy the following formula:

[0104]

[0105] in, represents the normalization parameter, ensuring that the measurement matrix can provide good observations for different sparse vectors. x represents the perturbation signal vector. It is a measurement matrix, through which the observation matrices of different sparse vectors can be obtained to realize signal reconstruction.

[0106] Step 502: Obtain an observation matrix of a sparse vector corresponding to the power quality signal according to the measurement matrix.

[0107] Among them, a sparse vector refers to a vector in which most of the elements are zero or close to zero, and only a few elements are meaningful non-zero values. Among them, the observation matrix can directly obtain the state vector of the power quality signal.

[0108] In this embodiment, the terminal may perform linear projection on the measurement matrix, project the measurement matrix into a two-dimensional space, and obtain an observation matrix.

[0109] Step 503: Obtain a reconstructed power quality signal according to the sparse vector measurement matrix and preset reconstruction parameters.

[0110] Among them, the reconstruction parameters may include sampling rate, embedding dimension, time delay parameter, etc. The embedding dimension determines the dimension in the phase space, and the time delay parameter affects the distribution density of the phase points.

[0111] In this embodiment, the reconstructed power quality signal can be obtained by solving the measurement value in the observation matrix:

[0112]

[0113] in, represents the reconstructed signal of power quality disturbance, S represents the sparse vector of power quality signal obtained after denoising, Represents the reconstruction parameters.

[0114] In this embodiment, the terminal generates a measurement matrix using the power quality signal. Since the measurement matrix can project the high-dimensional signal into a low-dimensional space, the observation matrix of the sparse vector corresponding to the power quality signal can be obtained according to the measurement matrix, and then the reconstructed power quality signal can be obtained according to the observation matrix of the sparse vector and the preset reconstruction parameters, thereby ensuring the reliability of the reconstructed power quality signal.

[0115] In the above scenario of using power quality signals to generate a measurement matrix, the power quality signals may be first subjected to redundancy processing to avoid the influence of the redundant signals on the reconstructed power quality signals. In an exemplary embodiment, as shown in FIG6 , before using power quality signals to generate a measurement matrix, the above method further includes:

[0116] Step 601: Generate a time series corresponding to a power quality signal.

[0117] It should be noted that in order to ensure the coherence of the power quality signal time series, it can be assumed that the sampling time of the power quality signal of the power equipment is a constant, and the time series corresponding to the power quality signal will also show a certain change pattern.

[0118] Among them, time series refers to observation points arranged in chronological order, and time series can be used to characterize the changes of power quality signals in the time dimension.

[0119] In this embodiment, the terminal may sequentially sort the power quality signals belonging to the same power equipment according to the monitoring time corresponding to the power quality signals, thereby obtaining the time series corresponding to the power quality signals.

[0120] Step 602: Remove null values ​​and repeated values ​​in the time series to obtain a power quality signal after redundancy processing.

[0121] Among them, null values ​​refer to missing values ​​in the data, and duplicate values ​​refer to values ​​that are repeatedly collected in the data. It is understandable that in the time series data, there may be missing or unmonitored data points. Therefore, null values ​​and duplicate values ​​in the time series can be removed to delete the redundant parts in the time series.

[0122] In this embodiment, each value in the time series can be detected and identified. If a value is empty or repeated values ​​appear, the empty value and repeated values ​​are removed, and the time series after the removal is used as a power quality signal after redundant processing.

[0123] Correspondingly, the above step 501 includes: generating a measurement matrix using the power quality signal after redundancy processing.

[0124] In this embodiment, after obtaining the redundantly processed power quality signal, the terminal may generate a measurement matrix according to the redundantly processed power quality signal.

[0125] In this embodiment, the terminal can eliminate null values ​​and repeated values ​​in the time series by generating a time series corresponding to the power quality signal, thereby removing the redundant part in the power quality signal and obtaining the power quality signal after redundant processing, and then using the power quality signal after redundant processing to form a measurement matrix, which can avoid the influence of the redundant part on the measurement matrix and improve the accuracy of the generated measurement matrix.

[0126] To facilitate understanding by those skilled in the art, the method for locating the power quality disturbance signal provided by the present application is described in detail below. The method may include:

[0127] S1, obtain the original power quality signal monitored by the power sensor equipment.

[0128] S2, performing multi-scale decomposition processing on the original power quality signal to obtain a decomposed original power quality signal.

[0129] S3, using a noise coefficient judgment threshold to perform denoising on the high-frequency signal and the low-frequency signal in the decomposed original power quality signal to obtain a power quality signal.

[0130] S4, generating a measurement matrix using the power quality signal.

[0131] S5, obtaining an observation matrix of a sparse vector corresponding to the power quality signal according to the measurement matrix.

[0132] S6, obtaining a reconstructed power quality signal according to the sparse vector observation matrix and preset reconstruction parameters.

[0133] S7, extracting multiple amplitude fluctuation features corresponding to the reconstructed power quality signal.

[0134] S8, performing clustering processing on each frequency spectrum feature in the multiple amplitude fluctuation features to obtain an initial clustering result.

[0135] S9, performing clustering processing on the initial clustering results according to each transmission path feature in the multiple amplitude fluctuation features to obtain a clustering result.

[0136] S10, determining the cluster center in the clustering result as the spatial position.

[0137] It should be noted that for the description in the above S1-S10, reference may be made to the relevant description in the above embodiment, and the effects are similar, which will not be repeated in this embodiment.

[0138] It should be understood that, although the steps in the flowcharts involved in the above embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0139] Based on the same inventive concept, the embodiment of the present application also provides a device for locating a power quality disturbance signal for implementing the method for locating a power quality disturbance signal involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in the embodiments of one or more power quality disturbance signal locating devices provided below can be referred to the limitations of the method for locating a power quality disturbance signal above, and will not be repeated here.

[0140] In one embodiment, as shown in FIG. 7 , a device for locating a power quality disturbance signal is provided, comprising: an acquisition module 701 , a reconstruction module 702 and a determination module 703 , wherein:

[0141] The acquisition module 701 is used to acquire the power quality signal corresponding to the power sensor device.

[0142] The reconstruction module 702 is used to perform signal reconstruction processing on the power quality signal to obtain a reconstructed power quality signal.

[0143] The determination module 703 is used to extract multiple amplitude fluctuation features corresponding to the reconstructed power quality signal, and cluster each amplitude fluctuation feature to determine the spatial position of the power quality disturbance signal. The power quality disturbance signal is a signal with amplitude fluctuation in the power quality signal.

[0144] The device for locating a power quality disturbance signal provided in this embodiment can execute the above method embodiment, and its implementation principle and technical effect are similar, which will not be described in detail here.

[0145] In one embodiment, the amplitude fluctuation feature is a spectrum feature or a transmission path feature, and the above 703 determination module includes: a first clustering unit, a second clustering unit and a determination unit, wherein:

[0146] A first clustering unit is used to perform clustering processing on each spectrum feature in the plurality of amplitude fluctuation features to obtain an initial clustering result;

[0147] Optionally, the spectrum characteristics are determined according to the spectrum scale of the reconstructed power quality signal, the signal transmission rate, the sampling time window scale, the sampling delay time and the preset disturbance parameters.

[0148] A second clustering unit is used to perform clustering processing on the initial clustering result according to each transmission path feature in the plurality of amplitude fluctuation features to obtain a clustering result;

[0149] Optionally, the transmission path characteristics are determined based on the signal transmission distance, transformation parameters and transmission parameters of the power quality disturbance signal during the reconstruction process.

[0150] The determination unit is used to determine the cluster center in the clustering result as a spatial position.

[0151] The device for locating a power quality disturbance signal provided in this embodiment can execute the above method embodiment, and its implementation principle and technical effect are similar, which will not be described in detail here.

[0152] In one embodiment, the acquisition module 701 includes: a decomposition unit and a denoising unit, wherein:

[0153] The decomposition unit is used to obtain the original power quality signal monitored by the power sensor device, and perform multi-scale decomposition processing on the original power quality signal to obtain the decomposed original power quality signal.

[0154] The denoising unit is used to perform denoising processing on the high-frequency signal and the low-frequency signal in the decomposed original power quality signal by using the noise coefficient judgment threshold to obtain the power quality signal.

[0155] The device for locating a power quality disturbance signal provided in this embodiment can execute the above method embodiment, and its implementation principle and technical effect are similar, which will not be described in detail here.

[0156] In one embodiment, the reconstruction module 702 includes: a generation unit, a first acquisition unit and a second acquisition unit, wherein:

[0157] The generating unit is used for generating a measurement matrix using the power quality signal.

[0158] The first acquisition unit is used to obtain an observation matrix of a sparse vector corresponding to the power quality signal according to the measurement matrix.

[0159] The second acquisition unit is used to obtain the reconstructed power quality signal according to the observation matrix of the sparse vector and the preset reconstruction parameters.

[0160] The device for locating a power quality disturbance signal provided in this embodiment can execute the above method embodiment, and its implementation principle and technical effect are similar, which will not be described in detail here.

[0161] In one embodiment, the above device further includes: a generation module and a rejection module, wherein:

[0162] The generation module is used to generate a time series corresponding to the power quality signal.

[0163] The elimination module is used to eliminate null values ​​and repeated values ​​in the time series to obtain the power quality signal after redundant processing.

[0164] The generating unit is specifically used to generate a measurement matrix using the power quality signal after redundant processing.

[0165] The device for locating a power quality disturbance signal provided in this embodiment can execute the above method embodiment, and its implementation principle and technical effect are similar, which will not be described in detail here.

[0166] Each module in the above-mentioned power quality disturbance signal positioning device can be implemented in whole or in part by software, hardware and a combination thereof. Each of the above-mentioned modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0167] In an exemplary embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be shown in FIG8. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit, and an input device. The processor, the memory, and the input / output interface are connected via a system bus, and the communication interface, the display unit, and the input device are connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner may be implemented through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a method for locating a power quality disturbance signal is implemented. The display unit of the computer device is used to form a visually visible picture, which may be a display screen, a projection device, or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.

[0168] Those skilled in the art will understand that the structure shown in FIG. 8 is merely a block diagram of a partial structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0169] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0170] Obtaining power quality signals corresponding to power sensing equipment;

[0171] Performing signal reconstruction processing on the power quality signal to obtain a reconstructed power quality signal;

[0172] A plurality of amplitude fluctuation features corresponding to the reconstructed power quality signal are extracted, and each amplitude fluctuation feature is clustered to determine the spatial position of the power quality disturbance signal. The power quality disturbance signal is a signal with amplitude fluctuation in the power quality signal.

[0173] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0174] Performing clustering processing on each spectrum feature in the multiple amplitude fluctuation features to obtain an initial clustering result;

[0175] Optionally, the spectrum characteristics are determined according to the spectrum scale of the reconstructed power quality signal, the signal transmission rate, the sampling time window scale, the sampling delay time and the preset disturbance parameters;

[0176] According to each transmission path feature in the multiple amplitude fluctuation features, clustering processing is performed on the initial clustering results to obtain a clustering result;

[0177] Optionally, the transmission path characteristics are determined according to the signal transmission distance, the transformation parameters and the transmission parameters of the power quality disturbance signal during the reconstruction process;

[0178] The cluster centers in the clustering results are determined as spatial locations.

[0179] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0180] Acquire the original power quality signal monitored by the power sensor device, and perform multi-scale decomposition processing on the original power quality signal to obtain the decomposed original power quality signal;

[0181] The noise coefficient judgment threshold is used to perform denoising on the high-frequency signal and the low-frequency signal in the decomposed original power quality signal to obtain the power quality signal.

[0182] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0183] Generate measurement matrix using power quality signals;

[0184] Obtaining an observation matrix of a sparse vector corresponding to the power quality signal according to the measurement matrix;

[0185] According to the observation matrix of the sparse vector and the preset reconstruction parameters, a reconstructed power quality signal is obtained.

[0186] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0187] Generate a time series corresponding to the power quality signal;

[0188] Eliminate the null values ​​and repeated values ​​in the time series to obtain the power quality signal after redundant processing;

[0189] Generate a measurement matrix using power quality signals, including:

[0190] The measurement matrix is ​​generated using the redundantly processed power quality signals.

[0191] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0192] Obtaining power quality signals corresponding to power sensing equipment;

[0193] Performing signal reconstruction processing on the power quality signal to obtain a reconstructed power quality signal;

[0194] A plurality of amplitude fluctuation features corresponding to the reconstructed power quality signal are extracted, and each amplitude fluctuation feature is clustered to determine the spatial position of the power quality disturbance signal. The power quality disturbance signal is a signal with amplitude fluctuation in the power quality signal.

[0195] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0196] Performing clustering processing on each spectrum feature in the multiple amplitude fluctuation features to obtain an initial clustering result;

[0197] Optionally, the spectrum characteristics are determined according to the spectrum scale of the reconstructed power quality signal, the signal transmission rate, the sampling time window scale, the sampling delay time and the preset disturbance parameters;

[0198] According to each transmission path feature in the multiple amplitude fluctuation features, clustering processing is performed on the initial clustering results to obtain a clustering result;

[0199] Optionally, the transmission path characteristics are determined according to the signal transmission distance, the transformation parameters and the transmission parameters of the power quality disturbance signal during the reconstruction process;

[0200] The cluster center in the clustering result is determined as the spatial position. In one embodiment, when the computer program is executed by the processor, the following steps are also implemented:

[0201] Acquire the original power quality signal monitored by the power sensor device, and perform multi-scale decomposition processing on the original power quality signal to obtain the decomposed original power quality signal;

[0202] The noise coefficient judgment threshold is used to perform denoising on the high-frequency signal and the low-frequency signal in the decomposed original power quality signal to obtain the power quality signal.

[0203] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0204] Generate measurement matrix using power quality signals;

[0205] Obtaining an observation matrix of a sparse vector corresponding to the power quality signal according to the measurement matrix;

[0206] According to the observation matrix of the sparse vector and the preset reconstruction parameters, a reconstructed power quality signal is obtained.

[0207] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0208] Generate a time series corresponding to the power quality signal;

[0209] Eliminate the null values ​​and repeated values ​​in the time series to obtain the power quality signal after redundant processing;

[0210] Generate a measurement matrix using power quality signals, including:

[0211] The measurement matrix is ​​generated using the redundantly processed power quality signals.

[0212] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:

[0213] Obtaining power quality signals corresponding to power sensing equipment;

[0214] Performing signal reconstruction processing on the power quality signal to obtain a reconstructed power quality signal;

[0215] A plurality of amplitude fluctuation features corresponding to the reconstructed power quality signal are extracted, and each amplitude fluctuation feature is clustered to determine the spatial position of the power quality disturbance signal. The power quality disturbance signal is a signal with amplitude fluctuation in the power quality signal.

[0216] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0217] Performing clustering processing on each spectrum feature in the multiple amplitude fluctuation features to obtain an initial clustering result;

[0218] Optionally, the spectrum characteristics are determined according to the spectrum scale of the reconstructed power quality signal, the signal transmission rate, the sampling time window scale, the sampling delay time and the preset disturbance parameters;

[0219] According to each transmission path feature in the multiple amplitude fluctuation features, clustering processing is performed on the initial clustering results to obtain a clustering result;

[0220] Optionally, the transmission path characteristics are determined according to the signal transmission distance, the transformation parameters and the transmission parameters of the power quality disturbance signal during the reconstruction process;

[0221] The cluster center in the clustering result is determined as the spatial position. In one embodiment, when the computer program is executed by the processor, the following steps are also implemented:

[0222] Acquire the original power quality signal monitored by the power sensor device, and perform multi-scale decomposition processing on the original power quality signal to obtain the decomposed original power quality signal;

[0223] The noise coefficient judgment threshold is used to perform denoising on the high-frequency signal and the low-frequency signal in the decomposed original power quality signal to obtain the power quality signal.

[0224] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0225] Generate measurement matrix using power quality signals;

[0226] Obtaining an observation matrix of a sparse vector corresponding to the power quality signal according to the measurement matrix;

[0227] According to the observation matrix of the sparse vector and the preset reconstruction parameters, a reconstructed power quality signal is obtained.

[0228] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0229] Generate a time series corresponding to the power quality signal;

[0230] Eliminate the null values ​​and repeated values ​​in the time series to obtain the power quality signal after redundant processing;

[0231] Generate a measurement matrix using power quality signals, including:

[0232] The measurement matrix is ​​generated using the redundantly processed power quality signals.

[0233] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0234] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0235] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for locating a power quality disturbance signal, characterized in that: The method comprises: Obtaining power quality signals corresponding to power sensing equipment; Performing signal reconstruction processing on the power quality signal to obtain a reconstructed power quality signal; Extract multiple amplitude fluctuation features corresponding to the reconstructed power quality signal, and perform clustering processing on each of the amplitude fluctuation features to determine the spatial position of the power quality disturbance signal, wherein the power quality disturbance signal is a signal with amplitude fluctuation in the power quality signal.

2. The method according to claim 1, characterized in that The amplitude fluctuation feature is a spectrum feature or a transmission path feature, and clustering the fluctuation features to determine the spatial position of the power quality disturbance signal includes: Performing clustering processing on each of the frequency spectrum features in the multiple amplitude fluctuation features to obtain an initial clustering result; Performing clustering processing on the initial clustering result according to each of the transmission path features in the multiple amplitude fluctuation features to obtain the clustering result; The cluster center in the clustering result is determined as the spatial position.

3. The method according to claim 2, characterized in that The spectrum feature is determined according to the spectrum scale, signal transmission rate, sampling time window scale, sampling delay time and preset disturbance parameters of the reconstructed power quality signal; The transmission path characteristics are determined according to the signal transmission distance, the transformation parameters and the transmission parameters of the power quality disturbance signal during the reconstruction process.

4. The method according to claim 1, characterized in that: The obtaining of the power quality signal corresponding to the power sensor device includes: Acquire the original power quality signal monitored by the power sensor device, and perform multi-scale decomposition processing on the original power quality signal to obtain the decomposed original power quality signal; The high-frequency signal and the low-frequency signal in the decomposed original power quality signal are denoised using a noise coefficient judgment threshold to obtain the power quality signal.

5. The method according to claim 1, characterized in that The performing signal reconstruction processing on the power quality signal to obtain a reconstructed power quality signal includes: generating a measurement matrix using the power quality signal; Obtaining an observation matrix of a sparse vector corresponding to the power quality signal according to the measurement matrix; The reconstructed power quality signal is obtained according to the observation matrix of the sparse vector and the preset reconstruction parameters.

6. The method according to claim 5, characterized in that Before generating a measurement matrix using the power quality signal, the method further includes: Generating a time series corresponding to the power quality signal; Eliminating null values ​​and repeated values ​​in the time series to obtain a power quality signal after redundancy processing; The step of generating a measurement matrix using the power quality signal comprises: The measurement matrix is ​​generated using the redundantly processed power quality signal.

7. A device for locating power quality disturbance signals, characterized in that: The device comprises: An acquisition module, used for acquiring a power quality signal corresponding to a power sensor device; A reconstruction module, used for performing signal reconstruction processing on the power quality signal to obtain a reconstructed power quality signal; A determination module is used to extract multiple amplitude fluctuation features corresponding to the reconstructed power quality signal, and cluster each of the amplitude fluctuation features to determine the spatial position of the power quality disturbance signal, wherein the power quality disturbance signal is a signal with amplitude fluctuation in the power quality signal.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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