Power grid broadband signal processing method, system, device and medium

Abstract

The present application provides a method, system, device and medium for processing power grid broadband signals. The method obtains a power grid broadband signal within a preset detection period at a target detection node of a power grid line to be detected, and then determines a first power grid line feature for characterizing the transient process characteristics of the power grid broadband signal within the preset detection period based on a broadband voltage signal and a broadband current signal in the power grid broadband signal, and then uses a preset power grid traveling wave signal threshold to extract a power grid traveling wave signal segment in the power grid broadband signal to generate a power grid traveling wave signal segment sequence, and determines a second power grid line feature for characterizing the energy overflow characteristics within the preset detection period based on the power grid traveling wave signal segment sequence, and then determines the power grid line state of the power grid line to be detected based on the first power grid line feature and the second power grid line feature, thereby realizing power grid line fault monitoring based on power grid broadband signals.

Description

Technical Field

[0001] The present application relates to data processing technology, and in particular to a method, system, device and medium for processing broadband signals of a power grid. Background Art

[0002] With the continuous development of power systems, the complexity and scale of power grids are increasing, placing higher demands on the safety and stability of grid operations. Traditional grid monitoring methods rely primarily on monitoring single parameters, such as voltage or current stability, which often proves inadequate when faced with complex grid faults.

[0003] Furthermore, with the development of broadband measurement technology, the application of broadband signals in power grids is gaining increasing attention. Broadband signals contain rich information about the grid's operating status and can more comprehensively reflect the grid's dynamic characteristics. However, how to effectively process and utilize these broadband signals and extract valuable information for grid fault diagnosis remains a pressing technical challenge in the field of power grid monitoring. Summary of the Invention

[0004] The present application provides a method, system, device and medium for processing power grid broadband signals, thereby realizing power grid line fault monitoring based on power grid broadband signals.

[0005] In a first aspect, the present application provides a method for processing a broadband power grid signal, comprising:

[0006] At a target detection node of the power grid line to be detected, a power grid broadband signal within a preset detection period is obtained, wherein the power grid broadband signal includes a broadband voltage signal and a broadband current signal;

[0007] determining a first power grid line characteristic according to the broadband voltage signal and the broadband current signal, wherein the first power grid line characteristic is used to characterize a transient process characteristic of the broadband power grid signal within the preset detection period;

[0008] Utilizing a preset power grid traveling wave signal threshold, extracting a power grid traveling wave signal segment from the power grid broadband signal to generate a power grid traveling wave signal segment sequence, wherein the power grid traveling wave signal segment is a signal segment in the power grid broadband signal having a voltage greater than a preset power frequency voltage threshold and / or a current greater than a preset power frequency current threshold, wherein the preset power grid traveling wave signal threshold includes the preset power frequency voltage threshold and the preset power frequency current threshold;

[0009] determining a second grid line characteristic according to the grid traveling wave signal segment sequence, wherein the second grid line characteristic is used to characterize energy overflow characteristics within the preset detection period;

[0010] The grid line state of the grid line to be detected is determined according to the first grid line characteristic and the second grid line characteristic.

[0011] In the above scheme, by simultaneously acquiring broadband voltage and current signals and performing analysis based on these signals, the operating status of the power grid within a preset detection period is comprehensively reflected. This helps detect various potential abnormal conditions within the power grid, including but not limited to short circuits, overloads, equipment failures, and impedance anomalies. Specifically, by analyzing the broadband voltage and current signals, a first power grid line characteristic is determined. This characteristic accurately characterizes the transient characteristics of the power grid within the preset detection period, thereby extracting the behavioral patterns of the power grid during dynamic changes and proactively identifying potential instability factors. Using a preset power grid traveling wave signal threshold, traveling wave signal segments are accurately extracted from the broadband power grid signal and a corresponding segment sequence is generated. These traveling wave signal segments reflect energy overflow in the power grid. Further analysis of these segments allows the determination of a second power grid line characteristic, namely, the energy overflow characteristic, which provides an important basis for assessing power grid stability and security. The first and second power grid line characteristics are then combined to comprehensively determine the current status of the power grid line to be detected. Furthermore, by setting different characteristic thresholds, grid line conditions can be categorized into normal conditions, short circuit or overload risks, equipment failure risks, and impedance anomaly risks. This provides grid operators with timely and accurate fault warnings and status monitoring information, improving the overall efficiency and safety of grid operations. Furthermore, by monitoring and analyzing broadband grid signals in real time, potential grid issues can be promptly identified and addressed, preventing the occurrence or escalation of faults, reducing outage duration and economic losses, and providing data support for grid optimization and renovation.

[0012] Optionally, determining the first power grid line characteristic according to the broadband voltage signal and the broadband current signal includes:

[0013] Determine a transient process duration according to a broadband voltage waveform corresponding to the broadband voltage signal and a broadband current waveform corresponding to the broadband current signal, wherein the transient process duration is the smaller duration between a first characteristic duration and a second characteristic duration, the first characteristic duration being the duration of a process from one voltage calibration state to another voltage calibration state in the broadband voltage waveform, and the second characteristic duration being the duration of a process from one current calibration state to another current calibration state in the broadband current waveform;

[0014] The first power grid line characteristic is determined according to the duration of the transient process, the broadband voltage signal, and the broadband current signal.

[0015] In the above scheme, by analyzing broadband voltage and current waveforms, the transient state of the power grid within a preset detection period can be accurately captured. This includes the complete transition from one nominal voltage or current state to another, ensuring the accuracy and comprehensiveness of the transient analysis. By comparing the characteristic durations (i.e., the transition duration from one nominal voltage state to another) in the broadband voltage and current waveforms and selecting the smaller duration as the transient duration, this effectively avoids the potential time deviation caused by relying solely on a single signal (voltage or current), thereby improving the accuracy and reliability of transient duration determination and enhancing the efficiency of fault diagnosis. Furthermore, based on the transient duration and broadband voltage and current signals, the characteristics of the first power grid line can be more accurately determined. This characteristic not only reflects the transient characteristics of the power grid within the preset detection period but also provides an important basis for subsequent power grid status diagnosis and fault warning.

[0016] Before determining the duration of the transient process according to the broadband voltage waveform corresponding to the broadband voltage signal and the broadband current waveform corresponding to the broadband current signal, the method further includes:

[0017] determining a broadband voltage transient process sequence according to the broadband voltage waveform diagram, wherein each broadband voltage transient process in the broadband voltage transient process sequence is a transition process from one voltage calibration state to another voltage calibration state in the broadband voltage waveform diagram, and the one voltage calibration state and the another voltage calibration state are two adjacent voltage calibration states in the broadband voltage waveform diagram;

[0018] determining a broadband current transient process sequence according to the broadband current waveform diagram, wherein each broadband current transient process in the broadband current transient process sequence is a transition process from one current calibration state to another current calibration state in the broadband current waveform diagram, and the one current calibration state and the another current calibration state are two adjacent current calibration states in the broadband current waveform diagram;

[0019] Correspondingly, determining the duration of the transient process according to the broadband voltage waveform corresponding to the broadband voltage signal and the broadband current waveform corresponding to the broadband current signal includes:

[0020] determining the first characteristic duration according to the broadband voltage transient process sequence, wherein the first characteristic duration is the duration corresponding to the broadband voltage transient process with the shortest duration in the broadband voltage transient process sequence;

[0021] determining the second characteristic duration according to the broadband current transient process sequence, wherein the second characteristic duration is the duration corresponding to the broadband current transient process with the shortest duration in the broadband current transient process sequence;

[0022] The smaller duration between the first characteristic duration and the second characteristic duration is determined as the transient process duration.

[0023] In the above scheme, a wideband voltage transient sequence and a wideband current transient sequence are constructed. By analyzing the complete transition from one calibrated state to another in the voltage and current waveforms, the transients are captured and recorded, providing the basis for subsequent transient duration calculation and determination of the first grid line characteristics. Furthermore, when determining the transient duration, the system does not simply select a single transient duration. Instead, the shortest transient in the wideband voltage transient sequence and the shortest transient in the wideband current transient sequence are identified as the first and second characteristic durations, respectively. This "shortest" strategy effectively avoids deviations in the overall duration calculation caused by the duration of individual abnormal processes, thereby improving the accuracy of transient duration determination and, consequently, the precision of fault diagnosis. Furthermore, by analyzing the shortest transient duration, the system can gain greater sensitivity to subtle dynamic changes in the power grid. These subtle changes are often precursors to grid failures or instability, thus helping to identify and address potential problems earlier and prevent them from escalating.

[0024] It's worth noting that while the aforementioned approach includes the step of constructing a transient process sequence during the initial analysis, this step actually provides more accurate and effective input data for subsequent calculations. Therefore, overall, this approach improves computational accuracy without significantly increasing computational complexity. Instead, it improves overall computational efficiency by optimizing input data.

[0025] Furthermore, by analyzing voltage and current transient processes separately and determining their minimum durations, the dynamic changes in the power grid within a preset detection period can be more comprehensively reflected. This detailed data not only helps determine the characteristics of the initial power grid lines, but also provides richer and more accurate information support for subsequent grid status assessment and fault warning.

[0026] Optionally, the extracting the grid traveling wave signal segment from the grid broadband signal by using a preset grid traveling wave signal threshold to generate a grid traveling wave signal segment sequence includes:

[0027] Extracting characteristic voltage signal segments from the broadband voltage waveform using the preset power frequency voltage threshold to generate a characteristic voltage signal segment sequence, wherein the voltage value of each characteristic voltage signal segment in the characteristic voltage signal segment sequence is greater than the preset power frequency voltage threshold;

[0028] Determine a characteristic voltage time segment sequence according to the characteristic voltage signal segment sequence, wherein each characteristic voltage time segment in the characteristic voltage time segment sequence is a duration range corresponding to a characteristic voltage signal segment in the characteristic voltage signal segment sequence;

[0029] Extracting characteristic current signal segments from the broadband current waveform using the preset power frequency current threshold to generate a characteristic current signal segment sequence, wherein the current value of each characteristic current signal segment in the characteristic current signal segment sequence is greater than the preset power frequency current threshold;

[0030] Determining a characteristic current time segment sequence according to the characteristic current signal segment sequence, wherein each characteristic current time segment in the characteristic current time segment sequence is a duration range corresponding to a characteristic current signal segment in the characteristic current signal segment sequence;

[0031] determining a characteristic signal time segment sequence according to the characteristic voltage time segment sequence and the characteristic current time segment sequence, and extracting a power grid traveling wave signal segment in the power grid broadband signal according to the characteristic signal time segment sequence to generate the power grid traveling wave signal segment sequence, wherein the characteristic signal time segment sequence includes the characteristic voltage time segment sequence and the characteristic current time segment sequence;

[0032] The grid traveling wave signal segment sequence is determined according to the characteristic signal time segment sequence and the grid broadband signal.

[0033] In this solution, by using preset power frequency voltage and current thresholds, signal segments where the voltage or current exceeds the normal threshold, namely the grid traveling wave signal segments, can be accurately extracted from the broadband voltage and current waveforms. This extraction method, based on the physical characteristics of the actual signals, effectively filters out voltage and current fluctuations under normal conditions and focuses on detecting abnormal fluctuations that may cause grid failures. After determining the characteristic voltage and current signal segments, these signal segments are further converted into time segment sequences. This process not only records the presence of abnormal signals but also records their time range in detail, providing important time dimension information for subsequent analysis and diagnosis.

[0034] Then, by combining the characteristic time segments of both voltage and current, a comprehensive characteristic signal time segment sequence is constructed. This comprehensive consideration of voltage and current variations enhances fault detection sensitivity, accurately capturing even small abnormal fluctuations and improving the reliability of power grid fault detection. The generated power grid traveling wave signal segment sequence directly reflects possible fault points or abnormal areas in the power grid. This sequence not only provides data support for subsequent fault type determination but also provides important time markers for further fault location, enabling faster and more accurate troubleshooting and repair.

[0035] Optionally, determining the characteristic signal time segment sequence according to the characteristic voltage time segment sequence and the characteristic current time segment sequence includes:

[0036] If a first characteristic voltage time segment in the characteristic voltage time segment sequence and a first characteristic current time segment in the characteristic current time segment sequence have a time segment intersection, merging the first characteristic voltage time segment and the first characteristic current time segment to generate a first characteristic signal time segment;

[0037] If the second characteristic voltage time segment in the characteristic voltage time segment sequence and the second characteristic current time segment in the characteristic current time segment sequence do not have a time segment intersection, then a second characteristic signal time segment is generated based on the second characteristic voltage time segment, and a third characteristic signal time segment is generated based on the second characteristic current time segment. The characteristic signal time segment sequence includes the first characteristic signal time segment, the second characteristic signal time segment and the third characteristic signal time segment.

[0038] In the above scheme, by determining whether there is a time intersection between the characteristic voltage time segment and the characteristic current time segment, the relevant voltage and current abnormal time segments can be intelligently merged to form a unified characteristic signal time segment. This processing method simplifies the subsequent analysis process, avoids repeated processing of data within the same time range, and improves processing efficiency. Merging voltage and current time segments that have a time intersection means that the voltage and current changes within these time segments are synchronized and correlated. This processing method can more accurately identify abnormal signals in the power grid, reduce the misjudgment of single signal fluctuations, and improve the accuracy of signal recognition.

[0039] For voltage and current time segments that do not overlap, this method generates independent characteristic signal time segments. This ensures that even if the voltage and current changes do not occur simultaneously, their respective abnormal information is fully preserved, providing comprehensive data support for subsequent analysis.

[0040] By simultaneously considering the time segments of voltage and current, and separately processing the presence and absence of temporal overlap, it is possible to fully capture abnormal signals in the power grid. This comprehensive detection approach helps detect multiple types of power grid faults, including those that may only affect voltage or current.

[0041] The characteristic signal time segment sequence generated by the above scheme contains detailed voltage and current anomaly information, which provides important data support for subsequent fault type judgment, fault point location and fault cause analysis, making fault analysis more detailed and accurate.

[0042] Optionally, determining the second power grid line characteristic according to the power grid traveling wave signal segment sequence includes:

[0043] The second power grid line characteristic is determined according to the power grid traveling wave signal segment sequence and the characteristic signal time segment sequence.

[0044] In this approach, by combining the grid traveling wave signal segment sequence with the characteristic signal time segment sequence, the second grid line characteristic of the grid traveling wave signal can be accurately quantified. This quantification method, based on actual detected traveling wave signal data, provides reliable data support for evaluating the energy spillover characteristics of the grid line. Because grid traveling wave signals are often closely associated with faults or abnormal conditions in the power grid, extracting and analyzing these signals can more accurately identify fault characteristics in the power grid, providing an important basis for subsequent fault location and type determination.

[0045] Furthermore, the energy characteristics of power grid traveling wave signals can directly reflect the severity of power grid faults. By determining the characteristics of the second power grid line, this method can further assess the potential impact and damage of power grid faults. Real-time monitoring and processing of broadband power grid signals enables timely detection and response to abnormalities in the power grid, helping to reduce the impact of power grid faults on normal power supply and improve the stability and reliability of power grid operations. Furthermore, long-term monitoring and analysis of power grid signal data can identify potential risk points in power grid operations, enabling proactive intervention and repair measures.

[0046] Optionally, determining the grid line state of the grid line to be detected according to the first grid line characteristic and the second grid line characteristic includes:

[0047] If the first power grid line characteristic is greater than a preset first characteristic threshold, and the second power grid line characteristic is greater than a preset second characteristic threshold, determining that the power grid line state of the power grid to be detected is a first fault state, where the first fault state is used to indicate that the power grid to be detected has a short circuit or overload risk;

[0048] If the first power grid line characteristic is greater than the preset first characteristic threshold, and the second power grid line characteristic is less than the preset second characteristic threshold, determining that the power grid line state of the power grid to be detected is a second fault state, where the second fault state is used to indicate that there is a risk of equipment failure in the power grid to be detected;

[0049] If the first power grid line characteristic is less than the preset first characteristic threshold, and the second power grid line characteristic is greater than the preset second characteristic threshold, determining that the power grid line state of the power grid to be detected is a third fault state, and the third fault state is used to indicate that there is an impedance abnormality risk in the power grid to be detected;

[0050] If the first grid line characteristic is smaller than the preset first characteristic threshold, and the second grid line characteristic is smaller than the preset second characteristic threshold, it is determined that the grid line state of the grid line to be detected is normal.

[0051] In the above scheme, by comprehensively analyzing the first grid line characteristics (characterizing transient process characteristics) and the second grid line characteristics (characterizing energy overflow characteristics), the current state of the grid line to be detected can be accurately determined. This multi-feature fusion analysis method improves the accuracy and reliability of fault detection.

[0052] It is worth noting that by setting different characteristic thresholds, various fault conditions of power grid lines can be identified, including short circuit or overload risks, equipment failure risks, and impedance abnormality risks.

[0053] Furthermore, once a grid line fault is detected, an appropriate alarm or emergency response mechanism can be immediately triggered. This rapid response capability helps reduce the impact of faults on grid operations and ensures the stability and reliability of power supply. By monitoring and accurately determining the status of grid lines in real time, this method can provide strong support for grid operations and maintenance personnel. Based on system prompts, operators can quickly locate the fault point and take appropriate remedial measures, thereby improving operation and maintenance efficiency and overall grid performance.

[0054] In a second aspect, the present application provides a power grid broadband signal processing system, comprising:

[0055] An acquisition module is configured to acquire a broadband signal of a power grid within a preset detection period at a target detection node of the power grid line to be detected, wherein the broadband signal of the power grid includes a broadband voltage signal and a broadband current signal;

[0056] a processing module, configured to determine a first power grid line characteristic based on the broadband voltage signal and the broadband current signal, wherein the first power grid line characteristic is used to characterize a transient process characteristic of the broadband power grid signal within the preset detection period;

[0057] The processing module is further configured to extract a grid traveling wave signal segment from the grid broadband signal using a preset grid traveling wave signal threshold to generate a grid traveling wave signal segment sequence, wherein the grid traveling wave signal segment is a signal segment in the grid broadband signal having a voltage greater than a preset power frequency voltage threshold and / or a current greater than a preset power frequency current threshold, wherein the preset grid traveling wave signal threshold includes the preset power frequency voltage threshold and the preset power frequency current threshold;

[0058] The processing module is further configured to determine a second grid line characteristic based on the grid traveling wave signal segment sequence, wherein the second grid line characteristic is used to characterize energy overflow characteristics within the preset detection period;

[0059] The processing module is further configured to determine the grid line status of the grid line to be detected based on the first grid line characteristics, the grid traveling wave signal segment, and the second grid line characteristics.

[0060] In a third aspect, the present application provides an electronic device, comprising:

[0061] processor; and,

[0062] a memory for storing executable instructions of the processor;

[0063] The processor is configured to perform any possible method described in the first aspect by executing the executable instructions.

[0064] In a fourth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by a processor, they are used to implement any possible method described in the first aspect.

[0065] The power grid broadband signal processing method, system, device and medium provided in the present application obtain a power grid broadband signal within a preset detection period at a target detection node of the power grid line to be detected, and then determine a first power grid line characteristic used to characterize the transient process characteristics of the power grid broadband signal within the preset detection period based on the broadband voltage signal and the broadband current signal in the power grid broadband signal. Then, using a preset power grid traveling wave signal threshold, the power grid traveling wave signal segment in the power grid broadband signal is extracted to generate a power grid traveling wave signal segment sequence, and the second power grid line characteristic used to characterize the energy overflow characteristics within the preset detection period is determined based on the power grid traveling wave signal segment sequence. Then, the power grid line status of the power grid line to be detected is determined based on the first power grid line characteristic and the second power grid line characteristic, thereby realizing power grid line fault monitoring based on the power grid broadband signal. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0067] Figure 1 This is a flow chart of a method for processing a power grid broadband signal according to an exemplary embodiment of the present application;

[0068] Figure 2 is a flow chart of a method for processing a power grid broadband signal according to another exemplary embodiment of the present application;

[0069] Figure 3 is a schematic structural diagram of a power grid broadband signal processing system according to an exemplary embodiment of the present application;

[0070] Figure 4 2 is a schematic structural diagram of an electronic device according to an exemplary embodiment of the present application.

[0071] The above drawings illustrate specific embodiments of the present application, which will be described in more detail below. These drawings and the textual description are not intended to limit the scope of the present application in any way, but rather to illustrate the concepts of the present application to those skilled in the art by reference to specific embodiments. DETAILED DESCRIPTION

[0072] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

[0073] To solve the above problems, the embodiments provided in this application achieve real-time monitoring and accurate judgment of the power grid line status by comprehensively analyzing the broadband voltage and current signals in the power grid. The specific inventive concepts are as follows:

[0074] First, at the target detection node of the power grid line to be detected, the embodiments provided in this application acquire the power grid broadband signals, including broadband voltage signals and broadband current signals, within a preset detection period. These signals can fully reflect the operating status of the power grid during that time period.

[0075] Next, based on the acquired broadband voltage and current waveforms, the duration of the grid's transient process, which reflects the transition from one stable state to another, is determined. By comparing the transient durations in the voltage and current waveforms, the smaller duration is selected as the final transient duration to ensure analysis accuracy.

[0076] Based on the duration of the transient process, broadband voltage signal and broadband current signal, the first grid line characteristic is determined. This characteristic can accurately characterize the transient process characteristics of the grid within a preset detection period, and then extract the key behavioral patterns of the grid during dynamic changes.

[0077] To deeply analyze abnormal fluctuations in the power grid, the embodiments provided in this application utilize preset power-frequency traveling wave signal thresholds (including preset power-frequency voltage and current thresholds) to extract traveling wave signal segments from broadband voltage and current signals and generate corresponding segment sequences. These traveling wave signal segments directly reflect energy overflows in the power grid and are an important indicator for determining grid stability.

[0078] During the extraction process, characteristic signal segments are first identified from the broadband voltage and current waveforms based on preset voltage and current thresholds. These segments are then converted into time segment sequences. The relationship between the voltage and current time segment sequences is then analyzed (to determine if there is any temporal overlap), and these segments are merged or processed separately to generate the final characteristic signal time segment sequence. This process ensures accurate and comprehensive extraction of traveling wave signal segments.

[0079] Based on the extracted grid traveling wave signal segment sequence and characteristic signal time segment sequence, the embodiment provided in this application characterizes the energy overflow characteristics of the grid within a preset detection period by calculating the second grid line characteristics, providing an important basis for evaluating the stability and security of the grid.

[0080] The embodiments provided herein combine the first and second grid line characteristics to comprehensively determine the current state of the grid line to be detected. By setting different feature thresholds, the grid line status is classified into different categories, including normal state, short circuit or overload risk, equipment failure risk, and impedance anomaly risk. This multi-feature fusion analysis method improves the accuracy and reliability of fault detection.

[0081] Furthermore, once a power grid line fault is detected, the embodiments provided herein can further determine the location of the fault. By comparing the grid traveling wave signal segment sequences at different detection nodes, the fault identification signal segment is identified, and the specific location of the fault point relative to the target detection node is determined accordingly. This process provides strong support for subsequent fault detection and repair work.

[0082] In summary, the embodiments provided in this application propose an innovative method for processing broadband signals of power grids. By comprehensively analyzing broadband voltage and current signals, it can achieve accurate monitoring and judgment of the status of power grid lines, which not only improves the accuracy and reliability of fault detection, but also provides strong support for the operation, maintenance and management of the power grid.

[0083] Figure 1 FIG. 1 is a flow chart of a method for processing a broadband signal of a power grid according to an exemplary embodiment of the present application. Figure 1 As shown, the method provided in this embodiment includes:

[0084] S101: Acquire a power grid broadband signal within a preset detection period.

[0085] In this step, a grid broadband signal within a preset detection period is acquired at a target detection node of the grid line to be detected, wherein the grid broadband signal includes a broadband voltage signal and a broadband current signal.

[0086] Specifically, a target detection node is selected within the power grid to be inspected. High-precision data acquisition equipment is then used to continuously collect broadband signals from the grid at this node over a preset detection period (e.g., ten seconds, one minute, five minutes, etc.). These signals, including broadband voltage and current signals, comprehensively reflect the grid's operating status during this time period. The collected data should also be of high fidelity and resolution to facilitate subsequent analysis and processing.

[0087] S102: Determine a first power grid line characteristic according to the broadband voltage signal and the broadband current signal.

[0088] In this step, the first grid line characteristic may be determined based on the broadband voltage signal and the broadband current signal, wherein the first grid line characteristic is used to characterize transient process characteristics of the broadband grid signal within a preset detection period.

[0089] Optionally, the collected broadband voltage and current signals can be filtered and denoised to improve the signal-to-noise ratio. Then, broadband voltage and current waveforms are plotted, and the transition process from one calibrated state (such as a baseline value of voltage or current) to another calibrated state in the waveforms is analyzed, i.e., the transient process. The shortest duration of each transient process is determined in the voltage and current waveforms, and the smaller value of the two is taken as the transient process duration of the power grid. Based on the transient process duration, broadband voltage signal, and broadband current signal, a specific algorithm model is used to calculate the first power grid line characteristic, thereby characterizing the transient process characteristics of the power grid within a preset detection period through this characteristic.

[0090] S103 : Extracting a power grid traveling wave signal segment from the power grid broadband signal to generate a power grid traveling wave signal segment sequence.

[0091] In this step, a preset grid traveling wave signal threshold is used to extract grid traveling wave signal segments from the grid broadband signal to generate a grid traveling wave signal segment sequence. The grid traveling wave signal segments are signal segments in the grid broadband signal in which the voltage is greater than the preset power frequency voltage threshold and / or the current is greater than the preset power frequency current threshold. The preset grid traveling wave signal threshold includes a preset power frequency voltage threshold and a preset power frequency current threshold.

[0092] Specifically, the preset power frequency voltage threshold and power frequency current threshold can be set according to the actual situation and operating experience of the power grid. In the broadband voltage and current waveform diagram, the signal segments with voltage values ​​greater than the preset power frequency voltage threshold and current values ​​greater than the preset power frequency current threshold are extracted respectively to generate characteristic voltage signal segment sequences and characteristic current signal segment sequences. The characteristic signal segments are converted into time segment sequences, and the start and end time of each characteristic signal segment is recorded. Then, the characteristic voltage time segment sequence and the characteristic current time segment sequence are analyzed. If there is a time intersection, they are merged, otherwise they are retained separately, and finally a power grid traveling wave signal segment sequence is generated.

[0093] S104 . Determine a second grid line characteristic of the grid traveling wave signal according to the grid traveling wave signal segment sequence.

[0094] In this step, a second grid line feature of the grid traveling wave signal may be determined according to the grid traveling wave signal segment sequence, wherein the second grid line feature is used to characterize energy overflow characteristics within a preset detection period.

[0095] For each segment in the grid's traveling wave signal segment sequence, the energy value of the broadband voltage and current signals within that segment is calculated. Then, using a specific algorithm model, the energy values ​​of each segment are aggregated and quantified to derive a second grid line characteristic, which is used to characterize the grid's energy overflow characteristics within a preset detection period.

[0096] S105 . Determine a grid line status of the grid line to be detected according to the first grid line characteristic and the second grid line characteristic.

[0097] Specifically, the first characteristic threshold and the second characteristic threshold can be preset according to the actual operation of the power grid and the safety standard. The calculated first power grid line characteristic and the second power grid line characteristic are compared with the preset thresholds:

[0098] If both are greater than their respective thresholds, the grid line state is determined to be a first fault state (short circuit or overload risk).

[0099] If the first characteristic is greater than the threshold and the second characteristic is less than the threshold, it is determined to be a second fault state (equipment failure risk).

[0100] If the first characteristic is smaller than the threshold and the second characteristic is larger than the threshold, it is determined to be a third fault state (impedance abnormality risk).

[0101] If both are smaller than the threshold, it is considered to be a normal state.

[0102] In this embodiment, a grid broadband signal within a preset detection period is obtained at a target detection node of the grid line to be detected. Then, a first grid line characteristic for characterizing the transient process characteristics of the grid broadband signal within the preset detection period is determined based on the broadband voltage signal and the broadband current signal in the grid broadband signal. Then, a preset grid traveling wave signal threshold is used to extract the grid traveling wave signal segment from the grid broadband signal to generate a grid traveling wave signal segment sequence. Then, a second grid line characteristic for characterizing the energy overflow characteristics within the preset detection period is determined based on the grid traveling wave signal segment sequence. Then, the grid line state of the grid line to be detected is determined based on the first grid line characteristic and the second grid line characteristic, thereby realizing grid line fault monitoring based on the grid broadband signal.

[0103] Figure 2 FIG. 1 is a flow chart of a method for processing a broadband signal of a power grid according to another exemplary embodiment of the present application. Figure 2 As shown, the method provided in this embodiment includes:

[0104] S201: Acquire a power grid broadband signal within a preset detection period.

[0105] In this step, a grid broadband signal within a preset detection period is acquired at a target detection node of the grid line to be detected, wherein the grid broadband signal includes a broadband voltage signal and a broadband current signal.

[0106] Specifically, a target detection node is selected within the power grid to be inspected. High-precision data acquisition equipment is then used to continuously collect broadband signals from the grid at this node over a preset detection period (e.g., ten seconds, one minute, five minutes, etc.). These signals, including broadband voltage and current signals, comprehensively reflect the grid's operating status during this time period. The collected data should also be of high fidelity and resolution to facilitate subsequent analysis and processing.

[0107] S202: Determine a first power grid line characteristic according to the broadband voltage signal and the broadband current signal.

[0108] In this step, the first grid line characteristic may be determined based on the broadband voltage signal and the broadband current signal, wherein the first grid line characteristic is used to characterize transient process characteristics of the broadband grid signal within a preset detection period.

[0109] Optionally, the collected broadband voltage and current signals can be filtered and denoised to improve the signal-to-noise ratio. Then, broadband voltage and current waveforms are plotted, and the transition process from one calibrated state (such as a baseline value of voltage or current) to another calibrated state in the waveforms is analyzed, i.e., the transient process. The shortest duration of each transient process is determined in the voltage and current waveforms, and the smaller value of the two is taken as the transient process duration of the power grid. Based on the transient process duration, broadband voltage signal, and broadband current signal, a specific algorithm model is used to calculate the first power grid line characteristic, thereby characterizing the transient process characteristics of the power grid within a preset detection period through this characteristic.

[0110] In one possible implementation, the transient process duration is determined based on a broadband voltage waveform corresponding to the broadband voltage signal and a broadband current waveform corresponding to the broadband current signal. The transient process duration is the smaller duration between a first characteristic duration and a second characteristic duration. The first characteristic duration is the duration of a process from one voltage calibration state to another voltage calibration state in the broadband voltage waveform, and the second characteristic duration is the duration of a process from one current calibration state to another current calibration state in the broadband current waveform.

[0111] Using formula 1, the first power grid line characteristics are determined based on the transient process duration, broadband voltage signal, and broadband current signal. , Formula 1 is:

[0112] in, For the preset detection cycle, is the duration of the transient process, For the A broadband voltage signal within the duration of a transient process, For the A broadband current signal within the duration of a transient process.

[0113] Specifically, a data acquisition system can be used to acquire broadband voltage and current signals, and corresponding waveforms can be plotted. In the waveforms, the calibration states of the voltage and current are clearly defined, and these calibration states can be preset reference values ​​or normal ranges.

[0114] In the broadband voltage waveform, identify all transitions from one nominal voltage state to another. These transitions are known as voltage transients. Record the start and end times of each transient to determine its duration. Similarly, in the broadband current waveform, identify transitions from one nominal current state to another and record the duration of each transient.

[0115] From all recorded voltage transients, select the one with the shortest duration as the first characteristic duration. From all recorded current transients, select the one with the shortest duration as the second characteristic duration. Then, take the smaller of the first and second characteristic durations as the transient duration.

[0116] Then, based on the determined duration of the transient process, the broadband voltage signal and the broadband current signal within the preset detection period are respectively divided into multiple intervals of time length. It is worth noting that if the preset detection period is not an integer multiple of the duration of the transient process, the last interval may be shorter than the duration of the transient process. During processing, truncation or padding (for example, using the data of the last complete interval) can be performed according to the actual situation.

[0117] It's worth noting that Equation 1 quantifies the dynamic behavior of the power grid during transients by comprehensively considering the preset detection period, the duration of the transient process, and the broadband voltage and current signals within that duration. This quantification directly constitutes the first grid line characteristic, which effectively reflects the transient characteristics of the power grid within the preset detection period and provides a solid numerical foundation for subsequent grid status assessment and fault warning.

[0118] The first grid line characteristic calculated using Equation 1 can capture subtle dynamic changes in the grid, which are often precursors to grid instability or impending failure. Therefore, this method improves the sensitivity of grid fault detection, allowing operations and maintenance personnel to identify potential problems earlier and take appropriate preventive or countermeasure measures.

[0119] Furthermore, the first grid line characteristic not only reflects the transient characteristics of the grid but also indirectly relates to various grid failure modes. For example, when a short circuit or overload occurs, the transient characteristics change significantly. These changes are precisely quantified using Equation 1 and reflected in the first grid line characteristic. Operations and maintenance personnel can use this characteristic value change, combined with other monitoring data, to more accurately determine the type and severity of grid failures.

[0120] Furthermore, the first grid line feature calculated by Equation 1 serves as a crucial input for subsequent multi-feature fusion analysis. By combining it with the second grid line feature derived from the traveling wave signal, a comprehensive assessment of the grid's status can be achieved. This multi-feature fusion analysis method not only improves fault detection accuracy but also provides grid operators with a richer range of information, helping them better understand the grid's operating status.

[0121] Based on the first grid line characteristics calculated by Formula 1, grid operators can develop more scientific and reasonable O&M strategies. For example, they can strengthen monitoring and inspection efforts in areas with abnormal transient process characteristics. They can also conduct preventive maintenance or replace equipment or lines prone to failure in advance. These measures help improve the stability and reliability of grid operations and reduce the probability of failures and losses.

[0122] Optionally, before determining the transient process duration based on the broadband voltage waveform corresponding to the broadband voltage signal and the broadband current waveform corresponding to the broadband current signal, a broadband voltage transient process sequence can also be determined based on the broadband voltage waveform, where each broadband voltage transient process in the broadband voltage transient process sequence is a transition process from one voltage calibration state to another voltage calibration state in the broadband voltage waveform, and one voltage calibration state and another voltage calibration state are two adjacent voltage calibration states in the broadband voltage waveform. A first characteristic duration is determined based on the broadband voltage transient process sequence, where the first characteristic duration is the process duration corresponding to the broadband voltage transient process with the shortest process duration in the broadband voltage transient process sequence. A broadband current transient process sequence is determined based on the broadband current waveform, where each broadband current transient process in the broadband current transient process sequence is a process duration from one current calibration state to another current calibration state in the broadband current waveform, and one current calibration state and another current calibration state are two adjacent current calibration states in the broadband current waveform. The second characteristic duration is determined according to the broadband current transient process sequence, where the second characteristic duration is the transition process corresponding to the broadband current transient process with the shortest duration in the broadband current transient process sequence.

[0123] Specifically, a broadband voltage signal within a preset detection period is acquired from a target detection node on the power grid line to be inspected and plotted as a broadband voltage waveform graph. Within the broadband voltage waveform graph, all voltage calibration states are identified. Voltage calibration states can be peaks, troughs, or set thresholds in the voltage waveform; these states represent significant change points in the voltage waveform graph. The broadband voltage waveform graph is then traversed to identify the entire transition from one voltage calibration state to another, recording the start and end points of each transition to determine each broadband voltage transient. Each transient corresponds to the time period during which the voltage changes from one stable state to another. All identified broadband voltage transients are arranged in chronological order to construct a broadband voltage transient sequence. For each transient in the broadband voltage transient sequence, its duration is calculated, i.e., the time difference between the start and end points. Within the broadband voltage transient sequence, the transient with the shortest duration is identified; its corresponding duration is the first characteristic duration. This duration represents the fastest dynamic change in the voltage waveform. Then, similar to the steps for constructing a broadband voltage transient sequence, a broadband current transient sequence is constructed for the broadband current signal. Calculate the process duration: Similar to the voltage transient process, calculate the process duration of each transient process in the broadband current transient sequence. Find the transient process with the shortest process duration in the broadband current transient sequence. This process duration is the second characteristic duration. This duration represents the fastest dynamic change in the current waveform.

[0124] The first characteristic duration is then compared with the second characteristic duration, and the smaller of the two is selected as the final transient process duration, thereby ensuring that the determination of the transient process duration is based on the fastest dynamic change process in the voltage and current waveforms.

[0125] S203 : Extracting a power grid traveling wave signal segment from the power grid broadband signal to generate a power grid traveling wave signal segment sequence.

[0126] In this step, a preset grid traveling wave signal threshold is used to extract grid traveling wave signal segments from the grid broadband signal to generate a grid traveling wave signal segment sequence. The grid traveling wave signal segments are signal segments in the grid broadband signal in which the voltage is greater than the preset power frequency voltage threshold and / or the current is greater than the preset power frequency current threshold. The preset grid traveling wave signal threshold includes a preset power frequency voltage threshold and a preset power frequency current threshold.

[0127] Specifically, the preset power frequency voltage threshold and power frequency current threshold can be set according to the actual situation and operating experience of the power grid. In the broadband voltage and current waveform diagram, the signal segments with voltage values ​​greater than the preset power frequency voltage threshold and current values ​​greater than the preset power frequency current threshold are extracted respectively to generate characteristic voltage signal segment sequences and characteristic current signal segment sequences. The characteristic signal segments are converted into time segment sequences, and the start and end time of each characteristic signal segment is recorded. Then, the characteristic voltage time segment sequence and the characteristic current time segment sequence are analyzed. If there is a time intersection, they are merged, otherwise they are retained separately, and finally a power grid traveling wave signal segment sequence is generated.

[0128] In one possible implementation, a preset power frequency voltage threshold may be used to extract characteristic voltage signal segments from a broadband voltage waveform to generate a characteristic voltage signal segment sequence, wherein the voltage value of each characteristic voltage signal segment in the characteristic voltage signal segment sequence is greater than the preset power frequency voltage threshold.

[0129] Determine a characteristic voltage time segment sequence according to the characteristic voltage signal segment sequence, wherein each characteristic voltage time segment in the characteristic voltage time segment sequence is a duration range corresponding to a characteristic voltage signal segment in the characteristic voltage signal segment sequence;

[0130] Using a preset power frequency current threshold, extracting a characteristic current signal segment from a broadband current waveform diagram to generate a characteristic current signal segment sequence, wherein the current value of each characteristic current signal segment in the characteristic current signal segment sequence is greater than the preset power frequency current threshold;

[0131] Determine a characteristic current time segment sequence according to the characteristic current signal segment sequence, wherein each characteristic current time segment in the characteristic current time segment sequence is a duration range corresponding to a characteristic current signal segment in the characteristic current signal segment sequence;

[0132] Determining a characteristic signal time segment sequence based on the characteristic voltage time segment sequence and the characteristic current time segment sequence, and extracting a power grid traveling wave signal segment from the power grid broadband signal based on the characteristic signal time segment sequence to generate a power grid traveling wave signal segment sequence, wherein the characteristic signal time segment sequence includes the characteristic voltage time segment sequence and the characteristic current time segment sequence;

[0133] The grid traveling wave signal segment sequence is determined according to the characteristic signal time segment sequence and the grid broadband signal.

[0134] Furthermore, when determining the grid traveling wave signal segment sequence based on the characteristic signal time segment sequence and the grid broadband signal, if there is a time segment intersection between a first characteristic voltage time segment in the characteristic voltage time segment sequence and a first characteristic current time segment in the characteristic current time segment sequence, the first characteristic voltage time segment and the first characteristic current time segment are merged to generate a first characteristic signal time segment;

[0135] If the second characteristic voltage time segment in the characteristic voltage time segment sequence and the second characteristic current time segment in the characteristic current time segment sequence do not have a time segment intersection, then the second characteristic signal time segment is generated based on the second characteristic voltage time segment, and the third characteristic signal time segment is generated based on the second characteristic current time segment. The characteristic signal time segment sequence includes the first characteristic signal time segment, the second characteristic signal time segment, and the third characteristic signal time segment.

[0136] S204 : Determine a second grid line characteristic of the grid traveling wave signal according to the grid traveling wave signal segment sequence.

[0137] In this step, a second grid line feature of the grid traveling wave signal may be determined according to the grid traveling wave signal segment sequence, wherein the second grid line feature is used to characterize energy overflow characteristics within a preset detection period.

[0138] For each segment in the grid's traveling wave signal segment sequence, the energy value of the broadband voltage and current signals within that segment is calculated. Then, using a specific algorithm model, the energy values ​​of each segment are aggregated and quantified to derive a second grid line characteristic, which is used to characterize the grid's energy overflow characteristics within a preset detection period.

[0139] In a possible implementation, the second power grid line characteristic can be determined using Formula 2 according to the power grid traveling wave signal segment sequence and the characteristic signal time segment sequence. , Formula 2 is:

[0140] in, is the number of grid traveling wave signal segments in the grid traveling wave signal segment sequence, is the first in the characteristic signal time segment sequence A broadband voltage signal within a characteristic signal time segment, is the first in the characteristic signal time segment sequence A broadband current signal within a characteristic signal time segment.

[0141] It's worth noting that Formula 2 calculates the second grid line characteristic by calculating the sum of the products of the broadband voltage signal and the broadband current signal within each characteristic signal time segment in the grid traveling wave signal segment sequence, and dividing the sum by the number of traveling wave signal segments. This process accurately quantifies energy overflow during dynamic grid changes, particularly when traveling wave signals are present. This is crucial for assessing grid stability and security, as energy overflow is often a direct indicator of potential faults or instability within the grid. Because Formula 2 comprehensively considers changes in both voltage and current signals, it can capture subtle energy fluctuations within the grid. This high sensitivity enables immediate early warning of early signs of grid faults, preventing further development and expansion. This is crucial for maintaining stable grid operation and reducing power outage duration. By calculating the second grid line characteristic, it can be combined with other grid line characteristics (such as the first grid line characteristic) to perform multi-dimensional fault analysis. This approach not only identifies specific fault types within the grid (such as short circuits, overloads, equipment failures, or impedance anomalies), but also provides precise data support for fault location and repair. Furthermore, based on the second grid line characteristics derived from Equation 2, grid operators can develop more scientific and rational O&M strategies. For example, in areas with severe energy overflow, monitoring and maintenance efforts can be strengthened; equipment or lines with frequent energy overflows can be upgraded or replaced. This helps improve the overall operational efficiency and reliability of the grid.

[0142] S205 : Determine the grid line status of the grid line to be detected according to the first grid line characteristic and the second grid line characteristic.

[0143] Specifically, if the first grid line characteristic is greater than a preset first characteristic threshold, and the second grid line characteristic is greater than a preset second characteristic threshold, the grid line status of the detected grid line is determined to be a first fault state. The first fault state indicates that the detected grid line is at risk of a short circuit or overload. It is worth noting that the first grid line characteristic being greater than the preset threshold indicates that the grid experienced a relatively severe transient process within the preset detection period, possibly due to a sudden increase in current or voltage fluctuation within the grid. Such a severe transient process is often a sign that the grid has experienced a significant shock or sudden change. Simultaneously, the second grid line characteristic is also greater than the preset threshold, indicating that significant energy overflow has been detected in the grid traveling wave signal. Energy overflow is often closely related to short circuits or overloads within the grid, as these conditions can cause a sudden increase in current, resulting in a large amount of energy release. By combining significant changes in transient process characteristics and energy overflow characteristics, the system can comprehensively determine whether the grid line is at risk of a short circuit or overload. A short circuit causes a sharp increase in current, while an overload causes the grid to experience a current load exceeding its design capacity for a prolonged period. Both conditions can cause dramatic changes in grid transients and significant energy overflow.

[0144] If the first grid line characteristic is greater than a preset first characteristic threshold and the second grid line characteristic is less than a preset second characteristic threshold, the grid line status of the detected grid line is determined to be a second fault state. The second fault state indicates that the detected grid line faces a risk of equipment failure. It is worth noting that, similar to the first fault state, an increase in the first grid line characteristic indicates that the grid experienced a significant transient process within the preset detection period, potentially involving voltage or current fluctuations within the grid. However, the second grid line characteristic did not exceed the preset threshold, indicating that no significant energy overflow was detected in the grid traveling wave signal. This indicates that while dynamic changes exist in the grid, these changes do not result in a significant energy release. Combining these two points, the system infers that a fault or anomaly in a device within the grid (such as a transformer or circuit breaker) may have caused the transient process. However, since the faulty device itself did not cause a significant energy overflow within the entire grid, it is determined to be an equipment failure risk.

[0145] If the first grid line characteristic is less than a preset first characteristic threshold, and the second grid line characteristic is greater than a preset second characteristic threshold, the grid line status of the detected grid line is determined to be in the third fault state. This third fault state indicates that the detected grid line has an impedance anomaly risk. It is worth noting that the first grid line characteristic does not exceed the preset threshold, indicating that the grid transient process during the preset detection period was relatively stable, with no significant voltage or current fluctuations. However, the second grid line characteristic is greater than the preset threshold, indicating that significant energy overflow was detected in the grid traveling wave signal. This situation is often closely related to impedance changes in the grid. Impedance is a key factor affecting current distribution and energy transmission in the grid. When a grid line has an impedance anomaly (such as line aging or poor contact), even if the transient process is not obvious, it can lead to uneven energy distribution in the grid, causing local energy overflow. Therefore, the system identifies this situation as an impedance anomaly risk.

[0146] If the first grid line characteristic is smaller than a preset first characteristic threshold, and the second grid line characteristic is smaller than a preset second characteristic threshold, it is determined that the grid line state of the grid line to be detected is a normal state.

[0147] S206 : Determine a candidate power grid traveling wave signal segment sequence according to the power grid traveling wave signal segment sequence.

[0148] It is worth noting that a detection node sequence can be set on the above-mentioned power grid line to be detected, and the detection node sequence includes a target detection node and a preset power transmission direction along the power grid line to be detected, wherein the previous detection node of the target detection node in the detection node sequence is the first detection node, and the next detection node is the second detection node.

[0149] In this step, if it is determined that the grid line state of the grid line to be detected is a fault state, a candidate grid traveling wave signal segment sequence is determined based on the grid traveling wave signal segment sequence, and the time segment corresponding to the candidate grid traveling wave signal segment in the candidate grid traveling wave signal segment sequence is greater than the preset time range threshold, and the fault state is one of the first fault state, the second fault state and the third fault state.

[0150] Specifically, candidate power grid traveling wave signal segments are first screened from the generated power grid traveling wave signal segment sequence. The time interval corresponding to these candidate segments should be greater than a preset time range threshold. This step aims to remove short-lived traveling wave signals that may be caused by accidental factors and focus on those with longer durations that are more likely to be caused by actual faults.

[0151] The method may be to traverse the grid traveling wave signal segment sequence, and for each segment, check whether its time length exceeds a preset time range threshold. If so, add the segment to the candidate grid traveling wave signal segment sequence.

[0152] S207 . Determine a power grid traveling wave identification signal segment according to the candidate power grid traveling wave signal segment sequence.

[0153] In this step, the grid traveling wave identification signal segment can be determined according to the candidate grid traveling wave signal segment sequence. The grid traveling wave identification signal segment is the grid traveling wave signal segment with the largest voltage peak or the largest current peak in the candidate grid traveling wave signal segment sequence.

[0154] Specifically, in the candidate grid traveling wave signal segment sequence, the grid traveling wave signal segment with the largest voltage peak or current peak is selected as the grid traveling wave identification signal segment. This step further narrows the possible range of the fault point by identifying the segment with the largest signal strength.

[0155] The candidate power grid traveling wave signal segment sequence can be traversed, the voltage peak value or current peak value of each segment is calculated, and these peak values ​​are compared, and the segment with the largest peak value is selected as the power grid traveling wave identification signal segment.

[0156] S208 : Generate a first power grid traveling wave signal segment sequence according to the first power grid broadband signal of the first detection node.

[0157] Using a preset grid traveling wave signal threshold, a first grid traveling wave signal segment sequence is generated according to a first grid broadband signal of a first detection node, and a second grid traveling wave signal segment sequence is generated according to a second grid broadband signal of a second detection node.

[0158] In this step, the grid broadband signals of the first and second detection nodes within the same preset detection period are processed using the preset grid traveling wave signal threshold. For each detection node, the grid broadband signal is processed using the previously described method (i.e., using the preset power frequency voltage threshold and the preset power frequency current threshold to extract characteristic voltage and current signal segments, and then generating corresponding characteristic signal time segment sequences and grid traveling wave signal segment sequences) to generate the corresponding grid traveling wave signal segment sequences.

[0159] S209 : Determine the position of the fault point relative to the target detection node according to the power grid traveling wave identification signal segment, the first power grid traveling wave signal segment sequence, and the second power grid traveling wave signal segment sequence.

[0160] A waveform comparison is performed between the power grid traveling wave identification signal segment and the power grid traveling wave signal segment sequences of the first detection node and the second detection node.

[0161] If the waveform corresponding to the grid traveling wave identification signal segment does not exist in the first grid traveling wave signal segment sequence, and the waveform corresponding to the grid traveling wave identification signal segment exists in the second grid traveling wave signal segment sequence, it is determined that the fault point is located between the first detection node and the target detection node;

[0162] If the waveform corresponding to the grid traveling wave identification signal segment exists in the first grid traveling wave signal segment sequence, and the waveform corresponding to the grid traveling wave identification signal segment does not exist in the second grid traveling wave signal segment sequence, then it is determined that the fault point is located before the first detection node;

[0163] If the waveform corresponding to the grid traveling wave identification signal segment exists in both the first grid traveling wave signal segment sequence and the second grid traveling wave signal segment sequence, determining the identification time node corresponding to the grid traveling wave identification signal segment, the waveform corresponding to the grid traveling wave identification signal segment is at the first time node in the first grid traveling wave signal segment sequence, and the waveform corresponding to the grid traveling wave identification signal segment is at the second time node in the second grid traveling wave signal segment sequence;

[0164] The position of the fault point relative to the target detection node is determined according to the identified time node, the first time node, and the second time node.

[0165] It's worth noting that in the above steps, candidate power-wave signal segments are screened by analyzing the power-wave signal segment sequence. These segments correspond to time periods exceeding a preset time range threshold, effectively filtering out brief fluctuations that may be caused by accidental factors, thereby improving the accuracy of fault identification. Next, the power-wave identification signal segment is determined—that is, the signal segment with the largest voltage or current peak among the candidate power-wave signal segments. This helps quickly identify significant energy fluctuations caused by faults.

[0166] By using the preset grid traveling wave signal threshold and combining the grid broadband signals of the first detection node and the second detection node, the first grid traveling wave signal segment sequence and the second grid traveling wave signal segment sequence are generated respectively, realizing comprehensive monitoring of different positions of the grid line.

[0167] By comparing the grid's traveling wave signal segments at different detection nodes, the specific location of the fault point can be determined. This multi-dimensional, multi-node data comparison method significantly improves the accuracy and reliability of fault point location.

[0168] Furthermore, three different fault location scenarios are provided, including the fault point located between the first detection node and the target detection node, located before the first detection node, and located between the first and second detection nodes. This comprehensive coverage strategy ensures accurate and rapid fault location in various fault scenarios.

[0169] When the grid traveling wave identification signal segment does not exist in the first grid traveling wave signal segment sequence, but exists in the second grid traveling wave signal segment sequence, this logical judgment accurately locates the fault point between the first detection node and the target detection node, narrowing the investigation scope and improving operation and maintenance efficiency.

[0170] If the grid traveling wave identification signal segment exists in the first grid traveling wave signal segment sequence but not in the second grid traveling wave signal segment sequence, it is determined that the fault point is located before the first detection node, which provides a clear direction for troubleshooting of long-distance transmission lines.

[0171] In the case where both detection nodes have grid traveling wave identification signal segments, the specific direction of the fault point relative to the target detection node can be calculated by calculating and comparing the time nodes, for example, whether it is in the upstream line or the downstream line. Then, further analysis can be performed in combination with the grid broadband signals of other detection nodes in the detection node sequence.

[0172] Figure 3 FIG. 1 is a schematic diagram of a power grid broadband signal processing system according to an exemplary embodiment of the present application. Figure 3 As shown, the power grid broadband signal processing system 300 provided in this embodiment includes:

[0173] An acquisition module 310 is configured to acquire a broadband signal of a power grid within a preset detection period at a target detection node of the power grid line to be detected, wherein the broadband signal of the power grid includes a broadband voltage signal and a broadband current signal;

[0174] a processing module 320 configured to determine a first power grid line characteristic based on the broadband voltage signal and the broadband current signal, wherein the first power grid line characteristic is used to characterize a transient process characteristic of the broadband power grid signal within the preset detection period;

[0175] The processing module 320 is further configured to extract a grid traveling wave signal segment from the grid broadband signal using a preset grid traveling wave signal threshold to generate a grid traveling wave signal segment sequence, wherein the grid traveling wave signal segment is a signal segment in the grid broadband signal having a voltage greater than a preset power frequency voltage threshold and / or a current greater than a preset power frequency current threshold, wherein the preset grid traveling wave signal threshold includes the preset power frequency voltage threshold and the preset power frequency current threshold;

[0176] The processing module 320 is further configured to determine a second grid line characteristic based on the grid traveling wave signal segment sequence, wherein the second grid line characteristic is used to characterize energy overflow characteristics within the preset detection period;

[0177] The processing module 320 is further configured to determine the grid line status of the to-be-detected grid line according to the first grid line characteristic, the grid traveling wave signal segment, and the second grid line characteristic.

[0178] Optionally, the processing module 320 is specifically configured to:

[0179] Determine a transient process duration according to a broadband voltage waveform corresponding to the broadband voltage signal and a broadband current waveform corresponding to the broadband current signal, wherein the transient process duration is the smaller duration between a first characteristic duration and a second characteristic duration, the first characteristic duration being the duration of a process from one voltage calibration state to another voltage calibration state in the broadband voltage waveform, and the second characteristic duration being the duration of a process from one current calibration state to another current calibration state in the broadband current waveform;

[0180] The first power grid line characteristic is determined according to the duration of the transient process, the broadband voltage signal, and the broadband current signal.

[0181] Optionally, the processing module 320 is specifically configured to:

[0182] Before determining the duration of the transient process according to the broadband voltage waveform corresponding to the broadband voltage signal and the broadband current waveform corresponding to the broadband current signal, the method further includes:

[0183] determining a broadband voltage transient process sequence according to the broadband voltage waveform diagram, wherein each broadband voltage transient process in the broadband voltage transient process sequence is a transition process from one voltage calibration state to another voltage calibration state in the broadband voltage waveform diagram, and the one voltage calibration state and the another voltage calibration state are two adjacent voltage calibration states in the broadband voltage waveform diagram;

[0184] determining a broadband current transient process sequence according to the broadband current waveform diagram, wherein each broadband current transient process in the broadband current transient process sequence is a transition process from one current calibration state to another current calibration state in the broadband current waveform diagram, and the one current calibration state and the another current calibration state are two adjacent current calibration states in the broadband current waveform diagram;

[0185] determining the first characteristic duration according to the broadband voltage transient process sequence, wherein the first characteristic duration is the duration corresponding to the broadband voltage transient process with the shortest duration in the broadband voltage transient process sequence;

[0186] determining the second characteristic duration according to the broadband current transient process sequence, wherein the second characteristic duration is the duration corresponding to the broadband current transient process with the shortest duration in the broadband current transient process sequence;

[0187] The smaller duration between the first characteristic duration and the second characteristic duration is determined as the transient process duration.

[0188] Optionally, the processing module 320 is specifically configured to:

[0189] Extracting characteristic voltage signal segments from the broadband voltage waveform using the preset power frequency voltage threshold to generate a characteristic voltage signal segment sequence, wherein the voltage value of each characteristic voltage signal segment in the characteristic voltage signal segment sequence is greater than the preset power frequency voltage threshold;

[0190] Determine a characteristic voltage time segment sequence according to the characteristic voltage signal segment sequence, wherein each characteristic voltage time segment in the characteristic voltage time segment sequence is a duration range corresponding to a characteristic voltage signal segment in the characteristic voltage signal segment sequence;

[0191] Extracting characteristic current signal segments from the broadband current waveform using the preset power frequency current threshold to generate a characteristic current signal segment sequence, wherein the current value of each characteristic current signal segment in the characteristic current signal segment sequence is greater than the preset power frequency current threshold;

[0192] Determining a characteristic current time segment sequence according to the characteristic current signal segment sequence, wherein each characteristic current time segment in the characteristic current time segment sequence is a duration range corresponding to a characteristic current signal segment in the characteristic current signal segment sequence;

[0193] determining a characteristic signal time segment sequence according to the characteristic voltage time segment sequence and the characteristic current time segment sequence, and extracting a power grid traveling wave signal segment in the power grid broadband signal according to the characteristic signal time segment sequence to generate the power grid traveling wave signal segment sequence, wherein the characteristic signal time segment sequence includes the characteristic voltage time segment sequence and the characteristic current time segment sequence;

[0194] The grid traveling wave signal segment sequence is determined according to the characteristic signal time segment sequence and the grid broadband signal.

[0195] Optionally, the processing module 320 is specifically configured to:

[0196] If a first characteristic voltage time segment in the characteristic voltage time segment sequence and a first characteristic current time segment in the characteristic current time segment sequence have a time segment intersection, merging the first characteristic voltage time segment and the first characteristic current time segment to generate a first characteristic signal time segment;

[0197] If the second characteristic voltage time segment in the characteristic voltage time segment sequence and the second characteristic current time segment in the characteristic current time segment sequence do not have a time segment intersection, then a second characteristic signal time segment is generated based on the second characteristic voltage time segment, and a third characteristic signal time segment is generated based on the second characteristic current time segment. The characteristic signal time segment sequence includes the first characteristic signal time segment, the second characteristic signal time segment and the third characteristic signal time segment.

[0198] Optionally, the processing module 320 is specifically configured to:

[0199] The second power grid line characteristic is determined according to the power grid traveling wave signal segment sequence and the characteristic signal time segment sequence.

[0200] Optionally, the processing module 320 is specifically configured to:

[0201] If the first power grid line characteristic is greater than a preset first characteristic threshold, and the second power grid line characteristic is greater than a preset second characteristic threshold, determining that the power grid line state of the power grid to be detected is a first fault state, where the first fault state is used to indicate that the power grid to be detected has a short circuit or overload risk;

[0202] If the first power grid line characteristic is greater than the preset first characteristic threshold, and the second power grid line characteristic is less than the preset second characteristic threshold, determining that the power grid line state of the power grid to be detected is a second fault state, where the second fault state is used to indicate that there is a risk of equipment failure in the power grid to be detected;

[0203] If the first power grid line characteristic is less than the preset first characteristic threshold, and the second power grid line characteristic is greater than the preset second characteristic threshold, determining that the power grid line state of the power grid to be detected is a third fault state, and the third fault state is used to indicate that there is an impedance abnormality risk in the power grid to be detected;

[0204] If the first grid line characteristic is smaller than the preset first characteristic threshold, and the second grid line characteristic is smaller than the preset second characteristic threshold, it is determined that the grid line state of the grid line to be detected is normal.

[0205] Figure 4 FIG. 1 is a schematic diagram of the structure of an electronic device according to an exemplary embodiment of the present application. Figure 4 As shown, this embodiment provides an electronic device 400 including: a processor 401 and a memory 402; wherein:

[0206] The memory 402 is used to store computer programs. The memory may also be a flash memory.

[0207] The processor 401 is configured to execute the execution instructions stored in the memory to implement each step in the above method. For details, please refer to the relevant description in the above method embodiment.

[0208] Optionally, the memory 402 may be independent or integrated with the processor 401 .

[0209] When the memory 402 is a device independent of the processor 401, the electronic device 400 may further include:

[0210] The bus 403 is used to connect the memory 402 and the processor 401 .

[0211] This embodiment further provides a readable storage medium, in which a computer program is stored. When at least one processor of an electronic device executes the computer program, the electronic device executes the methods provided in the various aforementioned embodiments.

[0212] This embodiment further provides a program product, which includes a computer program stored in a readable storage medium. At least one processor of an electronic device can read the computer program from the readable storage medium, and at least one processor can execute the computer program to cause the electronic device to implement the methods provided in the various embodiments described above.

[0213] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present application that follow the general principles of the present application and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered merely as exemplary, and the true scope and spirit of the present application are indicated by the claims.

[0214] It should be understood that the present application is not limited to the exact structure described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A method for processing broadband signals of a power grid, characterized in that: include: At a target detection node of the power grid line to be detected, a power grid broadband signal within a preset detection period is obtained, wherein the power grid broadband signal includes a broadband voltage signal and a broadband current signal; Determine a first power grid line characteristic according to the broadband voltage signal and the broadband current signal, wherein the first power grid line characteristic is used to characterize a transient process characteristic of the broadband power grid signal within the preset detection period; Using a preset power frequency voltage threshold, extracting a characteristic voltage signal segment in a broadband voltage waveform diagram corresponding to the broadband voltage signal to generate a characteristic voltage signal segment sequence; Determining a characteristic voltage time segment sequence according to the characteristic voltage signal segment sequence; Using a preset power frequency current threshold, extracting a characteristic current signal segment in a broadband current waveform diagram corresponding to the broadband current signal to generate a characteristic current signal segment sequence; Determining a characteristic current time segment sequence according to the characteristic current signal segment sequence; Determine a characteristic signal time segment sequence according to the characteristic voltage time segment sequence and the characteristic current time segment sequence; Determine a power grid traveling wave signal segment sequence according to the characteristic signal time segment sequence and the power grid broadband signal, wherein the power grid traveling wave signal segment in the power grid traveling wave signal segment sequence is a signal segment in the power grid broadband signal where the voltage is greater than a preset power frequency voltage threshold and / or the current is greater than a preset power frequency current threshold; Determine a second power grid line feature according to the power grid traveling wave signal segment sequence, wherein the second power grid line feature is used to characterize energy overflow characteristics within the preset detection period; The grid line state of the grid line to be detected is determined according to the first grid line characteristic and the second grid line characteristic.

2. The method for processing power grid broadband signals according to claim 1, characterized in that: The determining of the first power grid line characteristic according to the broadband voltage signal and the broadband current signal comprises: Determine the duration of the transient process according to the broadband voltage waveform corresponding to the broadband voltage signal and the broadband current waveform corresponding to the broadband current signal, wherein the duration of the transient process is the smaller duration between the first characteristic duration and the second characteristic duration, wherein the first characteristic duration is the duration of the process from one voltage calibration state to another voltage calibration state in the broadband voltage waveform, and the second characteristic duration is the duration of the process from one current calibration state to another current calibration state in the broadband current waveform; The first power grid line characteristic is determined according to the duration of the transient process, the broadband voltage signal, and the broadband current signal.

3. The method for processing power grid broadband signals according to claim 2, characterized in that: Before determining the duration of the transient process according to the broadband voltage waveform corresponding to the broadband voltage signal and the broadband current waveform corresponding to the broadband current signal, the method further includes: Determine a broadband voltage transient process sequence according to the broadband voltage waveform diagram, wherein each broadband voltage transient process in the broadband voltage transient process sequence is a process duration from one voltage calibration state to another voltage calibration state in the broadband voltage waveform diagram, and the one voltage calibration state and the another voltage calibration state are two adjacent voltage calibration states in the broadband voltage waveform diagram; determining the first characteristic duration according to the broadband voltage transient process sequence, wherein the first characteristic duration is the process duration corresponding to the broadband voltage transient process with the shortest process duration in the broadband voltage transient process sequence; Determine a broadband current transient process sequence according to the broadband current waveform diagram, each broadband current transient process in the broadband current transient process sequence is a process duration from one current calibration state to another current calibration state in the broadband current waveform diagram, and the one current calibration state and the another current calibration state are two adjacent current calibration states in the broadband current waveform diagram; The second characteristic duration is determined according to the broadband current transient process sequence, where the second characteristic duration is the process duration corresponding to the broadband current transient process with the shortest process duration in the broadband current transient process sequence.

4. The method for processing power grid broadband signals according to claim 3, characterized in that: The voltage value of each characteristic voltage signal segment in the characteristic voltage signal segment sequence is greater than the preset power frequency voltage threshold; Each characteristic voltage time segment in the characteristic voltage time segment sequence is a duration range corresponding to a characteristic voltage signal segment in the characteristic voltage signal segment sequence; The current value of each characteristic current signal segment in the characteristic current signal segment sequence is greater than the preset power frequency current threshold; Each characteristic current time segment in the characteristic current time segment sequence is a duration range corresponding to a characteristic current signal segment in the characteristic current signal segment sequence; The grid traveling wave signal segments in the grid broadband signal are extracted according to the characteristic signal time segment sequence to generate the grid traveling wave signal segment sequence, wherein the characteristic signal time segment sequence includes the characteristic voltage time segment sequence and the characteristic current time segment sequence.

5. The method for processing power grid broadband signals according to claim 4, characterized in that: The determining of the characteristic signal time segment sequence according to the characteristic voltage time segment sequence and the characteristic current time segment sequence comprises: If there is a time segment intersection between a first characteristic voltage time segment in the characteristic voltage time segment sequence and a first characteristic current time segment in the characteristic current time segment sequence, merging the first characteristic voltage time segment with the first characteristic current time segment to generate a first characteristic signal time segment; If the second characteristic voltage time segment in the characteristic voltage time segment sequence and the second characteristic current time segment in the characteristic current time segment sequence do not have a time segment intersection, a second characteristic signal time segment is generated based on the second characteristic voltage time segment, and a third characteristic signal time segment is generated based on the second characteristic current time segment, and the characteristic signal time segment sequence includes the first characteristic signal time segment, the second characteristic signal time segment and the third characteristic signal time segment.

6. The method for processing power grid broadband signals according to claim 5, characterized in that: The determining of the second power grid line characteristic according to the power grid traveling wave signal segment sequence comprises: The second power grid line characteristic is determined according to the power grid traveling wave signal segment sequence and the characteristic signal time segment sequence.

7. The method for processing broadband signals of a power grid according to any one of claims 1 to 6, characterized in that: The determining the grid line state of the to-be-detected grid line according to the first grid line characteristic and the second grid line characteristic comprises: If the first power grid line characteristic is greater than a preset first characteristic threshold, and the second power grid line characteristic is greater than a preset second characteristic threshold, it is determined that the power grid line state of the power grid to be detected is a first fault state, and the first fault state is used to indicate that the power grid to be detected has a short circuit or overload risk; If the first power grid line characteristic is greater than the preset first characteristic threshold, and the second power grid line characteristic is less than the preset second characteristic threshold, it is determined that the power grid line state of the power grid to be detected is a second fault state, and the second fault state is used to indicate that there is a risk of equipment failure in the power grid to be detected; If the first power grid line characteristic is less than the preset first characteristic threshold, and the second power grid line characteristic is greater than the preset second characteristic threshold, it is determined that the power grid line state of the power grid to be detected is a third fault state, and the third fault state is used to indicate that the power grid to be detected has an impedance abnormality risk; If the first power grid line characteristic is smaller than the preset first characteristic threshold, and the second power grid line characteristic is smaller than the preset second characteristic threshold, it is determined that the power grid line state of the power grid to be detected is a normal state.

8. A power grid broadband signal processing system, characterized in that: include: An acquisition module, used to acquire a broadband signal of a power grid within a preset detection period at a target detection node of the power grid line to be detected, wherein the broadband signal of the power grid includes a broadband voltage signal and a broadband current signal; A processing module, used to determine a first power grid line characteristic according to the broadband voltage signal and the broadband current signal, wherein the first power grid line characteristic is used to characterize a transient process characteristic of the broadband power grid signal within the preset detection period; The processing module is further used to extract the characteristic voltage signal segment in the broadband voltage waveform corresponding to the broadband voltage signal by using a preset power frequency voltage threshold value to generate a characteristic voltage signal segment sequence; determine a characteristic voltage time segment sequence according to the characteristic voltage signal segment sequence; extract the characteristic current signal segment in the broadband current waveform corresponding to the broadband current signal by using a preset power frequency current threshold value to generate a characteristic current signal segment sequence; determine a characteristic current time segment sequence according to the characteristic current signal segment sequence; determine a characteristic signal time segment sequence according to the characteristic voltage time segment sequence and the characteristic current time segment sequence; determine a power grid traveling wave signal segment sequence according to the characteristic signal time segment sequence and the power grid broadband signal, the power grid traveling wave signal segment in the power grid traveling wave signal segment sequence being a signal segment in the power grid broadband signal where the voltage is greater than the preset power frequency voltage threshold value and / or the current is greater than the preset power frequency current threshold value; The processing module is further used to determine a second power grid line feature according to the power grid traveling wave signal segment sequence, wherein the second power grid line feature is used to characterize energy overflow characteristics within the preset detection period; The processing module is further used to determine the grid line state of the grid line to be detected according to the first grid line characteristics, the grid traveling wave signal segment and the second grid line characteristics.

9. An electronic device, characterized in that: include: processor; as well as, A memory, configured to store executable instructions of the processor; The processor is configured to perform the method of any one of claims 1 to 7 by executing the executable instructions.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 7 when executed by a processor.

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