A hydropower station feeder fault detection system and method

Abstract

The invention discloses a feeder fault detection system and method for a hydropower station, and specifically relates to the technical field of feeder detection. By real-time acquisition of the hydropower station feeder fault traveling wave signal and the amplitude change during its propagation process, combined with an established theoretical propagation model, the traveling wave attenuation law is calculated, the rationality of the signal transmission path is judged, and for signals with unreasonable paths, the spectrum characteristics are extracted through frequency analysis, matched with a preset fault traveling wave feature library, the authenticity of the signal source is verified, and the accuracy of fault point positioning is predicted according to the rationality of the signal path and the authenticity of the source, the traveling wave propagation speed and line impedance are dynamically adjusted, the deviation caused by clock synchronization error is corrected, and the positioning accuracy is improved, thereby effectively solving the problem of inaccurate positioning caused by synchronization signal interference in the prior art, and greatly improving the stability and economic benefits of the hydropower station power supply system.

Description

Technical Field

[0001] The present invention relates to the technical field of feeder detection, and in particular to a feeder fault detection system and method for a hydropower station. Background Art

[0002] Hydropower station feeder fault detection refers to the identification and location of faults in the feeder (i.e., the cable line that transmits power from the substation or distribution center to the user or other network nodes) in the hydropower station transmission system through specific technologies and equipment, such as the use of traveling wave detection technology. The purpose of this type of detection is to ensure the safety and stability of the power system, quickly isolate the faulty line and restore normal power supply, and prevent the fault from expanding and causing a wider range of power outages. Common fault types include short circuits, broken lines, ground faults, and overload faults.

[0003] Traveling wave detection is a high-precision fault location technology that determines the fault location by monitoring the propagation characteristics of high-speed transient electromagnetic waves (traveling waves) generated when a fault occurs in the feeder and analyzing their propagation time difference. When a fault occurs, the traveling wave will propagate on the power line at a speed close to the speed of light. By arranging high-precision clock-synchronized monitoring devices at both ends of the feeder, the time when the traveling wave arrives at both ends is recorded, and the specific location of the fault point is calculated based on the line length and wave speed. This method has the advantages of fast response speed and high positioning accuracy, and is particularly suitable for long-distance high-voltage transmission lines. In addition, combined with protection relays and communication technologies (such as the IEC 61850 standard), the traveling wave method can achieve rapid fault isolation and line reconstruction, greatly improving the intelligence level and power supply reliability of the distribution system.

[0004] The prior art has the following deficiencies:

[0005] The traveling wave method relies on high-precision clock synchronization of the monitoring devices at both ends of the feeder (usually using GPS or other synchronization technologies), but if the synchronization signal is interfered with (such as electromagnetic interference or satellite signal blocking), it will cause time recording errors, which will directly affect the accuracy of fault location. In addition, inaccurate fault point location will cause maintenance personnel to spend more time troubleshooting the line, thereby extending the fault recovery time. This will lead to an expansion of the power outage scope or a longer duration, affecting the power supply stability and economic benefits of the hydropower station. Summary of the invention

[0006] The purpose of the present invention is to provide a hydropower station feeder fault detection system and method to solve the deficiencies in the background technology.

[0007] In order to achieve the above object, the present invention provides the following technical solution: a method for detecting a feeder fault in a hydropower station, comprising the following steps:

[0008] S1: High-speed transient monitoring devices are arranged at both ends of the hydropower station feeder to collect the traveling wave signals generated when a fault occurs, and signal monitoring devices are arranged at multiple nodes of the feeder to record the amplitude changes of the traveling wave signals during the transmission process;

[0009] S2: By establishing a theoretical propagation model, the traveling wave attenuation law of the feeder is calculated, and the actual measured attenuation data is compared with the theoretical model to determine the rationality of the signal transmission path;

[0010] S3: Perform frequency analysis on the traveling wave signal with unreasonable signal transmission path, extract its frequency spectrum characteristics, match the extracted frequency spectrum with the preset fault traveling wave feature library, and verify the authenticity of the signal source;

[0011] S4: According to the rationality of the signal transmission path and the authenticity of the signal source, the accuracy of the feeder fault point location is predicted, and according to the prediction result, the accuracy of the feeder fault point location is divided into accurate location and inaccurate location;

[0012] S5: For inaccurate positioning, the positioning deviation caused by clock synchronization error is continuously corrected according to the prediction results to improve the accuracy of fault point positioning, including dynamically adjusting the traveling wave propagation speed and line impedance according to the prediction results;

[0013] S6: Combine the location information of the hydropower station feeder fault point with the geographic information system to generate a visual location map of the fault point, and link it with the protection device to achieve rapid fault isolation and line reconstruction, shorten the fault recovery time, and reduce the scope of power outage.

[0014] Preferably, the actually measured attenuation data is compared with the theoretical model to determine the rationality of the signal transmission path. Specifically, the actually measured attenuation data is compared with the calculation results of the theoretical propagation model to obtain the traveling wave signal attenuation deviation index. The method for obtaining the traveling wave signal attenuation deviation index is as follows: The theoretical attenuation model of the traveling wave signal amplitude is expressed as: ;in, is the theoretically calculated signal amplitude, is the initial amplitude of the traveling wave signal, α is the attenuation coefficient, which indicates the exponential decay rate of the signal amplitude with the propagation distance, and x is the propagation distance of the traveling wave signal; the actual measured data is: p sampling points on the signal propagation path ,in: is the propagation distance of the sampling point, is the signal amplitude measured at the sampling point. The least square method fits the attenuation coefficient α by minimizing the residual square sum between the theoretical value and the actual measured value. Defined as: ; The objective function is: ; S is the residual sum of squares, which indicates the overall deviation between the theoretical and actual values, and p is the number of sampling points. By minimizing the objective function S, we can obtain the optimal attenuation coefficient α, and take the derivative of α: ; Set the derivative to zero: ; Solve this equation to get the optimal attenuation coefficient α; According to the optimal fitting parameter α, calculate the theoretical value , the traveling wave signal attenuation deviation index is defined as the average relative error between the theoretical value and the actual value, and the expression is: ; Where SXC is the attenuation deviation index of the traveling wave signal.

[0015] Preferably, the extracted frequency spectrum is matched with a preset fault wave feature library to verify the authenticity of the signal source. Specifically, the extracted actual signal frequency feature is compared with the template in the feature library, and the main frequency deviation anomaly index is generated after analyzing the relative deviation of the main frequency. The main frequency deviation anomaly index is obtained by extracting the main frequency point from the actual signal to form a feature vector. : ;in: Represents the nth main frequency of the actual signal, n is the number of main frequency feature points, T represents the transposition operation, converting the row vector into a column vector; construct the template frequency feature vector , extract the template frequency features corresponding to the fault type from the preset fault traveling wave feature library: ;in: Represents the nth main frequency of the template signal; based on the sample set of the template frequency feature library, calculate the covariance matrix Σ: ; Where: m is the number of template samples, is the mean vector of the template sample, defined as: ; k = 1, 2, ..., n; Calculate the actual frequency feature vector f and the template frequency feature vector The Mahalanobis distance , the formula is: ;in: is the inverse matrix of the covariance matrix, and the calculated Mahalanobis distance is Normalize and generate the main frequency deviation anomaly index: ; In the formula, is the main frequency deviation anomaly index, The abnormal threshold is set based on historical data.

[0016] Preferably, the accuracy of feeder fault point locating is predicted based on the rationality of the signal transmission path and the authenticity of the signal source, specifically: the traveling wave signal attenuation deviation index and the main frequency deviation anomaly index are normalized and mapped to the interval of [0,1], and the accuracy coefficient of feeder fault point locating is calculated by the normalized traveling wave signal attenuation deviation index and the main frequency deviation anomaly index.

[0017] Preferably, based on the prediction results, the accuracy of feeder fault point locating is divided into accurate locating and inaccurate locating, specifically: the calculated accuracy coefficient of feeder fault point locating is compared with a reference threshold of the accuracy coefficient pre-set according to historical data; if the accuracy coefficient of feeder fault point locating is greater than or equal to the pre-set reference threshold of the accuracy coefficient, it indicates that the accuracy of feeder fault point locating is high, and it is classified as accurate locating; if the accuracy coefficient of feeder fault point locating is less than the pre-set reference threshold of the accuracy coefficient, it indicates that the accuracy of feeder fault point locating is low, and it is classified as inaccurate locating.

[0018] Preferably, when the accuracy coefficient of the feeder fault point location is less than a preset reference threshold of the accuracy coefficient, it indicates that the positioning deviation is large and needs to be compensated by lowering or increasing the traveling wave propagation velocity v, specifically including: adjusting v by the accuracy coefficient, and the adjustment formula is: ;in: is the adjusted traveling wave propagation speed, is the initial setting of the traveling wave propagation speed, is the wave propagation velocity adjustment coefficient, AC is the calculated feeder fault point location accuracy coefficient, is the reference threshold of the accuracy coefficient;

[0019] When the accuracy coefficient of the feeder fault point location is less than the preset reference threshold of the accuracy coefficient, it indicates that the line impedance deviates from the theoretical value. The error is compensated by adjusting the line impedance Z, specifically including: dynamically adjusting Z through AC, and the adjustment formula is: ;in, is the adjusted line impedance, is the initial set line impedance, is the line impedance adjustment factor.

[0020] Preferably, the corrected fault point location calculation formula is: ; Where: D is the adjusted fault point location, L is the total length of the line, is the dynamically adjusted traveling wave propagation speed, and ΔT is the time difference between the traveling wave signal arriving at both ends of the feeder.

[0021] The present invention also provides a hydropower station feeder fault detection system, comprising a data acquisition module, a signal transmission analysis module, a signal authenticity verification module, a positioning accuracy prediction module, a positioning correction module, and a fault visualization and linkage module;

[0022] Data acquisition module: high-speed transient monitoring devices are arranged at both ends of the hydropower station feeder to collect the traveling wave signals generated when a fault occurs; signal monitoring devices are arranged at multiple nodes of the feeder to record the amplitude changes of the traveling wave signals during the transmission process;

[0023] The signal transmission analysis module calculates the traveling wave attenuation law of the feeder by establishing a theoretical propagation model, and compares the actual measured attenuation data with the theoretical model to determine the rationality of the signal transmission path;

[0024] The signal authenticity verification module performs frequency analysis on the traveling wave signal with unreasonable signal transmission path, extracts its frequency spectrum characteristics, matches the extracted frequency spectrum with the preset fault traveling wave feature library, and verifies the authenticity of the signal source;

[0025] The positioning accuracy prediction module predicts the accuracy of feeder fault point positioning based on the rationality of the signal transmission path and the authenticity of the signal source; based on the prediction results, the accuracy of feeder fault point positioning is divided into accurate positioning and inaccurate positioning;

[0026] Positioning correction module: for inaccurate positioning, it continuously corrects the positioning deviation caused by clock synchronization error according to the prediction results to improve the accuracy of fault point positioning, including dynamically adjusting the traveling wave propagation speed and line impedance according to the prediction results;

[0027] The fault visualization and linkage module combines the location information of the hydropower station feeder fault point with the geographic information system to generate a visual location map of the fault point; it is linked with the protection device to achieve rapid fault isolation and line reconstruction, shorten the fault recovery time, and reduce the scope of power outage.

[0028] In the above technical solution, the technical effects and advantages provided by the present invention are:

[0029] 1. The present invention arranges a high-speed transient monitoring device and a signal monitoring device, and calculates the traveling wave attenuation law in combination with a theoretical propagation model, thereby realizing the rationality analysis of the signal transmission path; at the same time, the authenticity of the signal source is verified by matching the frequency spectrum extraction with the fault traveling wave feature library, effectively overcoming the technical defect of the existing traveling wave method that the positioning is inaccurate due to the interference of the synchronization signal. In addition, the accuracy coefficient of the feeder fault point positioning is calculated based on the signal attenuation deviation index and the main frequency deviation anomaly index, and the traveling wave propagation speed and line impedance are dynamically adjusted to correct the positioning deviation, which greatly improves the accuracy and robustness of the fault point positioning.

[0030] 2. The present invention combines with the geographic information system to generate a visual fault location map, and links with the protection device to quickly isolate the fault section and reconstruct the line, significantly shorten the fault recovery time, reduce the scope of power outage, and improve the operating efficiency and economic benefits of the hydropower station power supply system. The present invention not only solves the problem of inaccurate positioning caused by clock synchronization errors, but also improves the automation level of fault detection and processing by optimizing positioning parameters and system linkage, providing reliable technical support for the intelligent operation and maintenance of hydropower stations. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0032] Figure 1 The figure is a flow chart of the method of the present invention.

[0033] Figure 2 It is a system module diagram of the present invention. DETAILED DESCRIPTION

[0034] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0035] Example 1, please refer to Figure 1 As shown, a method for detecting a feeder fault in a hydropower station described in this embodiment includes the following steps:

[0036] S1: High-speed transient monitoring devices are arranged at both ends of the hydropower station feeder to collect the traveling wave signals generated when a fault occurs, and signal monitoring devices are arranged at multiple nodes of the feeder to record the amplitude changes of the traveling wave signals during the transmission process;

[0037] S2: By establishing a theoretical propagation model, the traveling wave attenuation law of the feeder is calculated, and the actual measured attenuation data is compared with the theoretical model to determine the rationality of the signal transmission path;

[0038] S3: Perform frequency analysis on the traveling wave signal with unreasonable signal transmission path, extract its frequency spectrum characteristics, match the extracted frequency spectrum with the preset fault traveling wave feature library, and verify the authenticity of the signal source;

[0039] S4: According to the rationality of the signal transmission path and the authenticity of the signal source, the accuracy of the feeder fault point location is predicted, and according to the prediction result, the accuracy of the feeder fault point location is divided into accurate location and inaccurate location;

[0040] S5: For inaccurate positioning, the positioning deviation caused by clock synchronization error is continuously corrected according to the prediction results to improve the accuracy of fault point positioning, including dynamically adjusting the traveling wave propagation speed and line impedance according to the prediction results;

[0041] S6: Combine the location information of the hydropower station feeder fault point with the geographic information system to generate a visual location map of the fault point, and link it with the protection device to achieve rapid fault isolation and line reconstruction, shorten the fault recovery time, and reduce the scope of power outage.

[0042] In S1, high-speed transient monitoring devices are arranged at both ends of the hydropower station feeder to collect the traveling wave signals generated when the fault occurs and record their arrival time to calculate the preliminary location of the fault point.

[0043] Selection of monitoring device: Use high-frequency and high-speed transient sampling equipment, with a sampling rate of several MHz or more, to ensure that the detailed characteristics of the traveling wave (such as the wavefront mutation point) can be captured. The equipment includes a voltage sensor and a current transformer, which are used to collect the voltage and current components of the traveling wave signal respectively.

[0044] Clock synchronization: Each transient monitoring device is equipped with a high-precision clock synchronization module (such as a GPS synchronization device or an IEEE1588 protocol synchronization module) to ensure that the timestamps recorded at both ends have nanosecond accuracy. In special environments (such as underground lines), optical fiber synchronization technology can be used instead of GPS synchronization.

[0045] Installation location: The monitoring device is usually installed in the substation at both ends of the feeder and directly connected to the transmission line. The protection device communicates with the central control system to achieve real-time data transmission and fault analysis.

[0046] Signal monitoring devices are arranged at multiple nodes of the feeder to record the amplitude changes of the traveling wave signal during the transmission process, analyze the attenuation characteristics of the signal, and verify the rationality of the transmission path.

[0047] Selection of monitoring device: Highly sensitive voltage and current sensors are used to accurately measure the amplitude change and waveform characteristics of the traveling wave signal. The monitoring device supports multi-point synchronous acquisition and can accurately record the signal amplitude and time characteristics of each point.

[0048] Node layout strategy: Signal monitoring devices are placed at key locations of the line (such as the middle point, branch point, and near the grounding equipment of long-distance lines). The number of points is determined based on the line length, branch structure, and signal attenuation characteristics to ensure coverage of the key paths of signal propagation.

[0049] Data acquisition and transmission: The monitoring device records the amplitude of the traveling wave signal in real time, and analyzes whether the actual signal attenuation meets expectations based on the theoretical model of the line. The monitoring data is transmitted to the central processing system through optical fiber communication or wireless transmission, and compared with the data of the transient monitoring devices at both ends.

[0050] Combining data from both ends and multiple nodes: Combine the arrival time of the traveling wave collected at both ends with the amplitude change data recorded by multiple nodes to establish a full-path characteristic model of the traveling wave signal. By comparing the attenuation model with the actual data, the positioning deviation caused by line impedance, reflection or branch structure can be corrected.

[0051] Abnormal signal identification: Multi-node data analysis is used to identify whether abnormal signals (such as high-order harmonics, equipment noise, etc.) interfere with the positioning process, further improving detection accuracy.

[0052] In this application, by arranging high-speed transient monitoring devices at both ends of the feeder and signal monitoring devices at multiple nodes, comprehensive collection and analysis of traveling wave signals can be achieved. On the one hand, the timeliness of the initial positioning of the fault point is ensured; on the other hand, the positioning error is corrected through the attenuation characteristics of the signal, thereby improving the accuracy and reliability of fault detection.

[0053] S2: Establish a mathematical model for the propagation of traveling wave signals in the feeder and calculate the theoretical attenuation law as a benchmark for signal analysis, including:

[0054] Line parameter extraction: Collect key parameters of the feeder, including line length, conductor cross section, resistance, inductance, capacitance, characteristic impedance, and branch location. Consider the actual environment of the transmission line (such as geographical location, temperature and humidity conditions) and adjust the model parameters.

[0055] Based on transmission line theory, construct traveling wave propagation The calculation formula is: ; Among them, α is the attenuation coefficient, β is the phase change coefficient, x is the propagation distance, is the initial signal amplitude. The calculation of the attenuation coefficient α and the phase change coefficient β needs to consider parameters such as line impedance Z, propagation velocity v, and frequency f.

[0056] Simulate the influence of branching and reflection: Introduce the characteristic impedance changes of the feeder branch point and terminal equipment into the model, calculate the reflection and transmission coefficients caused by impedance mismatch. Simulate the superposition effect of reflected signals to ensure that the model can reflect the complex characteristics of the actual line.

[0057] The actual traveling wave signal is collected through the monitoring device, and its amplitude changes at different positions are recorded to obtain the actual attenuation characteristics, which specifically includes: arranging monitoring devices at both ends and intermediate nodes of the feeder to record the amplitude change data of the same traveling wave signal with distance. The sampling rate of the monitoring device is higher than the main frequency range of the traveling wave (such as more than several MHz) to ensure that the detailed characteristics of the signal are captured.

[0058] The collected signals are processed for noise reduction to eliminate environmental interference and equipment noise. Signal filtering technology (such as bandpass filtering or wavelet denoising) is used to extract the main frequency component of the traveling wave to ensure the validity of the analysis data.

[0059] The attenuation deviation index of the traveling wave signal is obtained by comparing and analyzing the actual measured attenuation data with the calculation results of the theoretical propagation model to judge the rationality of the signal transmission path. The method for obtaining the attenuation deviation index of the traveling wave signal is as follows:

[0060] The theoretical attenuation model of the traveling wave signal amplitude is expressed as: ;in, is the theoretically calculated signal amplitude in volts (V). is the initial amplitude of the traveling wave signal (the amplitude when it is generated at the fault point). α is the attenuation coefficient, which represents the exponential decay rate of the signal amplitude with the propagation distance, and the unit is 1 / m. x is the distance that the traveling wave signal propagates, and the unit is meter (m).

[0061] The actual measured data is: p sampling points on the signal propagation path ,in: is the propagation distance of the sampling point, is the signal amplitude measured at the sampling point. The least squares method fits the attenuation coefficient α by minimizing the residual sum of squares between the theoretical value and the actual measured value. Defined as: ; The objective function is: ; S is the residual sum of squares, which indicates the overall deviation between the theoretical and actual values, and p is the number of sampling points. By minimizing the objective function S, we can obtain the optimal attenuation coefficient α, and take the derivative of α: ; Set the derivative to zero: ; Solving this equation can obtain the optimal attenuation coefficient α.

[0062] According to the optimal fitting parameter α, the theoretical value is calculated , the traveling wave signal attenuation deviation index is defined as the average relative error between the theoretical value and the actual value, and the expression is: ; Where SXC is the attenuation deviation index of the traveling wave signal.

[0063] Based on the calculated traveling wave signal attenuation deviation index, the rationality of the signal transmission path can be judged: if the attenuation deviation index is small (such as within the acceptable threshold range, usually 5%-10%), it means that the theoretical propagation model is consistent with the actual measured data, the signal attenuation law conforms to the line characteristics, and the transmission path is reasonable and has no obvious abnormalities; if the deviation index is large, it may indicate that the signal has abnormal attenuation in certain path sections (such as equipment aging, branch point impedance mismatch or line fault), and it is necessary to further analyze the specific reasons and calibrate the model parameters or detection equipment to ensure that the signal transmission characteristics are consistent with the actual working conditions.

[0064] S3: Perform frequency analysis on the traveling wave signal with unreasonable signal transmission path, extract its characteristic frequency component, and determine whether it meets the characteristics of normal fault traveling wave.

[0065] Extract the frequency spectrum characteristics of the traveling wave signal and Filter to eliminate low-frequency environmental noise (such as electromagnetic interference) and high-frequency spike noise.

[0066] Filter type: Bandpass filter: Set the frequency range to the main frequency band of the traveling wave signal (such as 1kHz-1MHz). Wavelet denoising: Decompose the multi-scale components of the signal and remove noise signals in non-target frequency bands.

[0067] Perform fast Fourier transform (FFT) on the processed signal to extract the frequency spectrum characteristics: ; Where F(f) is the frequency spectrum density, f is the frequency component, is the kernel function of Fourier transform, It is the actual time domain representation of the signal, that is, the original signal collected from the device. Record the main frequency component and its amplitude, such as the frequency peak with a large amplitude (fault characteristic frequency).

[0068] Extract the spectrum characteristic parameters of the signal, including: Main frequency: the frequency component with the largest amplitude in the spectrum, reflecting the main propagation characteristics of the signal. Frequency distribution width: the range of significant frequency components in the spectrum, used to determine the frequency band characteristics of the signal. Harmonic characteristics: whether there are harmonics or high-order components that are not the source of the fault in the signal.

[0069] Match the frequency spectrum with the fault traveling wave feature library, establish the fault traveling wave feature library, and construct the frequency spectrum feature library corresponding to different fault types (such as short circuit, grounding, and high resistance fault) based on theoretical analysis or experimental data. The content includes: the main frequency range of common fault signals; frequency distribution patterns of different fault types; and the characteristic differences between multiple reflection signals and actual fault signals.

[0070] The extracted actual signal frequency feature is compared with the template in the feature library, and the main frequency deviation anomaly index is generated after analyzing the relative deviation of the main frequency. The main frequency deviation anomaly index is obtained as follows:

[0071] Extract the main frequency points from the actual signal to form a feature vector : ;in: It represents the nth main frequency of the actual signal, n is the number of main frequency feature points, and T represents the transposition operation, which converts the row vector into a column vector;

[0072] Constructing template frequency feature vector , extract the template frequency features corresponding to the fault type from the preset fault traveling wave feature library: ;in: Indicates the nth main frequency of the template signal;

[0073] According to the sample set of the template frequency feature library, the covariance matrix Σ is calculated: ; Where: m is the number of template samples, is the mean vector of the template sample, defined as: ; k = 1, 2, ..., n; Calculate the actual frequency feature vector f and the template frequency feature vector The Mahalanobis distance , the formula is: ;in: is the inverse matrix of the covariance matrix, and the calculated Mahalanobis distance is Normalize and generate the main frequency deviation anomaly index: ; In the formula, is the main frequency deviation anomaly index, It is an abnormality threshold set according to historical data (for example, the upper limit of the 95% confidence interval obtained from the statistics of normal samples).

[0074] Main frequency deviation abnormality index <100%: The frequency feature matches the template well, the deviation is within the normal range, and the signal source is credible. Main frequency deviation abnormality index ≥100%: The frequency feature deviates significantly from the template, and there may be interference signals or abnormal signal sources.

[0075] S4: According to the rationality of the signal transmission path and the authenticity of the signal source, the accuracy of the feeder fault point location is predicted, and according to the prediction result, the accuracy of the feeder fault point location is divided into accurate location and inaccurate location;

[0076] The traveling wave signal attenuation deviation index and the main frequency deviation anomaly index are normalized and mapped to the interval of [0,1]. The accuracy coefficient of feeder fault point location is calculated by the normalized traveling wave signal attenuation deviation index and the main frequency deviation anomaly index. The calculation expression is: ; In the formula, is the accuracy coefficient of feeder fault location, SXC is the traveling wave signal attenuation deviation index, is the main frequency deviation anomaly index, are the proportional coefficients of the output frequency fluctuation index and the grid frequency deviation index, respectively, and Both are greater than 0.

[0077] The calculated accuracy coefficient of the feeder fault point location is compared with the reference threshold of the accuracy coefficient pre-set according to historical data. If the accuracy coefficient of the feeder fault point location is greater than or equal to the pre-set reference threshold of the accuracy coefficient, it means that the accuracy of the feeder fault point location is high, and it is classified as accurate location; if the accuracy coefficient of the feeder fault point location is less than the pre-set reference threshold of the accuracy coefficient, it means that the accuracy of the feeder fault point location is low, and it is classified as inaccurate location.

[0078] S5: For inaccurate positioning, the positioning deviation caused by clock synchronization error is continuously corrected according to the prediction results to improve the accuracy of fault point positioning, including dynamically adjusting the traveling wave propagation speed and line impedance according to the prediction results;

[0079] When the accuracy coefficient of the feeder fault location is less than the preset reference threshold of the accuracy coefficient, it indicates that the positioning deviation is large and needs to be compensated by lowering or increasing the traveling wave propagation velocity v, including:

[0080] The traveling wave propagation velocity v is a key parameter for locating fault points, which often deviates from the theoretical value due to actual line characteristics or external factors (such as temperature, humidity, medium characteristics, etc.). v is adjusted by the accuracy coefficient AC: ;in: is the adjusted traveling wave propagation speed, is the initial set traveling wave propagation speed (theoretical value). is the wave propagation velocity adjustment coefficient, which is set according to the experimental or simulation results and reflects the sensitivity of velocity to the accuracy coefficient. AC is the calculated feeder fault location accuracy coefficient. is the reference threshold of the accuracy coefficient.

[0081] When the accuracy coefficient of the feeder fault point location is less than the preset reference threshold of the accuracy coefficient, it indicates that the line impedance may deviate from the theoretical value. The error is compensated by adjusting the line impedance Z, including:

[0082] The adjustment direction is related to the deviation of AC, ensuring that the line parameters are closer to the actual working conditions. Line impedance Z is a key parameter that determines the propagation characteristics of traveling waves. Its deviation may come from equipment aging, line failure or environmental changes. Dynamic adjustment of Z through AC: ;in, is the adjusted line impedance, is the initial set line impedance (theoretical value), It is the line impedance adjustment coefficient, which is set according to the experimental or simulation results and reflects the sensitivity of impedance to the accuracy coefficient.

[0083] The calculation formula of the corrected fault point location is: ; Where: D is the adjusted fault point location, L is the total length of the line, is the dynamically adjusted traveling wave propagation speed, and ΔT is the time difference between the traveling wave signal arriving at both ends of the feeder.

[0084] Dynamically adjusted and Closer to the actual line characteristics, significantly reducing positioning deviations caused by parameter errors. By calculating AC and adjusting parameters in real time, closed-loop optimization of the fault location algorithm is achieved, continuously improving positioning accuracy.

[0085] S6: The GIS system contains information such as the spatial distribution of transmission lines, tower locations, equipment numbers, branch structures, topography, etc. The corresponding geographic coordinates (x, y) are found in the GIS data through the line number and the distance D from the fault point. If the line is a branch structure, the specific branch of the fault point is further confirmed in combination with the branch path information.

[0086] The location of the hydropower station feeder fault point is marked with a prominent mark (such as a red dot) on the GIS interface, and its related information is displayed at the same time: the distance D from the feeder starting point. The time of the fault. Adjacent equipment information (such as circuit breakers, switch positions). The fault point information is superimposed on the multi-layer information of the GIS map to display the transmission line, equipment status, power outage area, etc. The fault impact range and equipment status are dynamically displayed through color, icons or animations to facilitate quick analysis.

[0087] According to the fault point location D, the line section where the fault is located is determined, and the switchgear adjacent to the fault point is determined. Protection device linkage: Command transmission: Fault information is transmitted to adjacent protection devices (such as circuit breakers, section switches) through the communication system. Execution isolation: The adjacent protection device performs rapid tripping according to the received command to isolate the fault section.

[0088] Automated protection equipment: Modern switchgear supports remote control and automatic tripping functions (such as protection equipment based on the IEC 61850 communication protocol). Low-latency communication: Utilize high-speed communication networks (such as fiber-optic communication) to transmit fault information to protection devices in real time, ensuring that fault isolation time is completed within tens to hundreds of milliseconds.

[0089] Through GIS system analysis, the affected lines and loads are identified and feasible power supply paths are planned. Based on the status of available lines in GIS data (current capacity, switch position, etc.), the optimal path is selected to restore power supply.

[0090] The reconstruction plan is implemented through the automated switch and dispatch system, including: starting the backup line power supply; adjusting the transformer load distribution; and restoring normal power supply. Based on the real-time load data, the stable operation of the power supply system after line reconstruction is ensured.

[0091] Through rapid fault isolation, only the faulty section of the hydropower station is disconnected, and the remaining areas continue to be powered through backup lines. The fault isolation time is significantly shortened (from minutes to milliseconds). Automated reconstruction quickly restores normal power supply, reduces power outage time, and improves user satisfaction.

[0092] In this embodiment, high-speed transient monitoring devices are arranged at both ends of the hydropower station feeder and multiple nodes to collect traveling wave signals and record changes in signal amplitude. By establishing a theoretical propagation model, the traveling wave attenuation law is calculated, and the actual attenuation data is compared with the theoretical model to evaluate the rationality of the signal transmission path. The frequency analysis of unreasonable traveling wave signals is performed, the frequency spectrum characteristics are extracted, and they are matched with the fault traveling wave feature library to verify the authenticity of the signal source. According to the rationality of the path and the authenticity of the signal, the accuracy of the fault point positioning is predicted and divided into accurate positioning and inaccurate positioning. Correct the inaccurate positioning, and dynamically adjust the traveling wave propagation speed and line impedance to improve the positioning accuracy. Finally, the fault point location information is combined with the geographic information system to generate a visual positioning map, which is linked with the protection device to achieve rapid fault isolation and line reconstruction, shorten the fault recovery time and reduce the scope of power outage.

[0093] Example 2, please refer to Figure 2 As shown, a hydropower station feeder fault detection system described in this embodiment includes a data acquisition module, a signal transmission analysis module, a signal authenticity verification module, a positioning accuracy prediction module, a positioning correction module, and a fault visualization and linkage module;

[0094] Data acquisition module: high-speed transient monitoring devices are arranged at both ends of the hydropower station feeder to collect the traveling wave signals generated when a fault occurs; signal monitoring devices are arranged at multiple nodes of the feeder to record the amplitude changes of the traveling wave signals during the transmission process;

[0095] The signal transmission analysis module calculates the traveling wave attenuation law of the feeder by establishing a theoretical propagation model, and compares the actual measured attenuation data with the theoretical model to determine the rationality of the signal transmission path;

[0096] The signal authenticity verification module performs frequency analysis on the traveling wave signal with unreasonable signal transmission path, extracts its frequency spectrum characteristics, matches the extracted frequency spectrum with the preset fault traveling wave feature library, and verifies the authenticity of the signal source;

[0097] The positioning accuracy prediction module predicts the accuracy of feeder fault point positioning based on the rationality of the signal transmission path and the authenticity of the signal source; based on the prediction results, the accuracy of feeder fault point positioning is divided into accurate positioning and inaccurate positioning;

[0098] Positioning correction module: for inaccurate positioning, it continuously corrects the positioning deviation caused by clock synchronization error according to the prediction results to improve the accuracy of fault point positioning, including dynamically adjusting the traveling wave propagation speed and line impedance according to the prediction results;

[0099] The fault visualization and linkage module combines the location information of the hydropower station feeder fault point with the geographic information system to generate a visual location map of the fault point; it is linked with the protection device to achieve rapid fault isolation and line reconstruction, shorten the fault recovery time, and reduce the scope of power outage.

[0100] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A method for detecting feeder faults in a hydropower station, characterized in that: The following steps are involved: S1: High-speed transient monitoring devices are arranged at both ends of the hydropower station feeder to collect the traveling wave signals generated when a fault occurs, and signal monitoring devices are arranged at multiple nodes of the feeder to record the amplitude changes of the traveling wave signals during the transmission process; S2: By establishing a theoretical propagation model, the traveling wave attenuation law of the feeder is calculated, and the actual measured attenuation data is compared with the theoretical model to determine the rationality of the signal transmission path. Specifically, the traveling wave signal attenuation deviation index is obtained by comparing and analyzing the actual measured attenuation data with the calculation results of the theoretical propagation model. The method for obtaining the traveling wave signal attenuation deviation index is as follows: The theoretical attenuation model of the traveling wave signal amplitude is expressed as: ;in, is the theoretically calculated signal amplitude, is the initial amplitude of the traveling wave signal, α is the attenuation coefficient, which indicates the exponential decay rate of the signal amplitude with the propagation distance, and x is the propagation distance of the traveling wave signal; the actual measured data is: p sampling points on the signal propagation path ,in: is the propagation distance of the sampling point, is the signal amplitude measured at the sampling point. The least squares method fits the attenuation coefficient α by minimizing the residual sum of squares between the theoretical value and the actual measured value; the residual is defined as: ; The objective function is: ; S is the residual sum of squares, which indicates the overall deviation between the theoretical and actual values, and p is the number of sampling points. By minimizing the objective function S, we can obtain the optimal attenuation coefficient α, and take the derivative of α: ; Set the derivative to zero: ; Solve this equation to get the optimal attenuation coefficient α; According to the optimal fitting parameter α, calculate the theoretical value , the traveling wave signal attenuation deviation index is defined as the average relative error between the theoretical value and the actual value, and the expression is: ; Where SXC is the attenuation deviation index of the traveling wave signal; S3: Perform frequency analysis on the traveling wave signal with unreasonable signal transmission path, extract its frequency spectrum characteristics, match the extracted frequency spectrum with the preset fault traveling wave feature library, and verify the authenticity of the signal source. Specifically, compare the extracted actual signal frequency characteristics with the template in the feature library, analyze the relative deviation of the main frequency, and then generate the main frequency deviation abnormality index. The main frequency deviation abnormality index is obtained by extracting the main frequency point from the actual signal to form a feature vector : ;in: Represents the nth main frequency of the actual signal, n is the number of main frequency feature points, T represents the transposition operation, converting the row vector into a column vector; construct the template frequency feature vector , extract the template frequency features corresponding to the fault type from the preset fault traveling wave feature library: ;in: Represents the nth main frequency of the template signal; based on the sample set of the template frequency feature library, calculate the covariance matrix Σ: ; Where: m is the number of template samples, is the mean vector of the template sample, defined as: ; k = 1, 2, ..., n; Calculate the actual frequency feature vector f and the template frequency feature vector The Mahalanobis distance , the formula is: ;in: is the inverse matrix of the covariance matrix, and the calculated Mahalanobis distance is Normalize and generate the main frequency deviation anomaly index: ; In the formula, is the main frequency deviation anomaly index, is an abnormal threshold set based on historical data; S4: According to the rationality of the signal transmission path and the authenticity of the signal source, the accuracy of the feeder fault point location is predicted, and according to the prediction result, the accuracy of the feeder fault point location is divided into accurate location and inaccurate location; The traveling wave signal attenuation deviation index and the main frequency deviation anomaly index are normalized and mapped to the interval of [0,1], and the accuracy coefficient of feeder fault point location is calculated by the normalized traveling wave signal attenuation deviation index and the main frequency deviation anomaly index; S5: For inaccurate positioning, the positioning deviation caused by clock synchronization error is continuously corrected according to the prediction results to improve the accuracy of fault point positioning, including dynamically adjusting the traveling wave propagation speed and line impedance according to the prediction results; S6: Combine the location information of the hydropower station feeder fault point with the geographic information system to generate a visual location map of the fault point, and link it with the protection device to achieve rapid fault isolation and line reconstruction, shorten the fault recovery time, and reduce the scope of power outage.

2. A method for detecting feeder faults in a hydropower station according to claim 1, characterized in that: According to the prediction results, the accuracy of feeder fault point locating is divided into accurate locating and inaccurate locating. Specifically, the calculated accuracy coefficient of feeder fault point locating is compared with the reference threshold of the accuracy coefficient pre-set according to historical data. If the accuracy coefficient of feeder fault point locating is greater than or equal to the pre-set reference threshold of the accuracy coefficient, it means that the accuracy of feeder fault point locating is high, and it is divided into accurate locating; if the accuracy coefficient of feeder fault point locating is less than the pre-set reference threshold of the accuracy coefficient, it means that the accuracy of feeder fault point locating is low, and it is divided into inaccurate locating.

3. A method for detecting feeder faults in a hydropower station according to claim 2, characterized in that: When the accuracy coefficient of the feeder fault point location is less than the preset reference threshold of the accuracy coefficient, it indicates that the positioning deviation is large and needs to be compensated by lowering or increasing the traveling wave propagation velocity v, which specifically includes: adjusting v by the accuracy coefficient, and the adjustment formula is: ;in: is the adjusted traveling wave propagation speed, is the initial setting of the traveling wave propagation speed, is the wave propagation velocity adjustment coefficient, AC is the calculated feeder fault location accuracy coefficient, is the reference threshold of the accuracy coefficient; When the accuracy coefficient of the feeder fault point location is less than the preset reference threshold of the accuracy coefficient, it indicates that the line impedance deviates from the theoretical value. The error is compensated by adjusting the line impedance Z, specifically including: dynamically adjusting Z through AC, and the adjustment formula is: ;in, is the adjusted line impedance, is the initial set line impedance, is the line impedance adjustment factor.

4. A method for detecting feeder faults in a hydropower station according to claim 3, characterized in that: The calculation formula of the corrected fault point location is: ; Where: D is the adjusted fault point location, L is the total length of the line, is the dynamically adjusted traveling wave propagation speed, and ΔT is the time difference between the traveling wave signal and the two ends of the feeder.

5. A hydropower station feeder fault detection system, used to implement a hydropower station feeder fault detection method according to any one of claims 1 to 4, characterized in that: It includes data acquisition module, signal transmission analysis module, signal authenticity verification module, positioning accuracy prediction module, positioning correction module and fault visualization and linkage module; Data acquisition module, where high-speed transient monitoring devices are arranged at both ends of the hydropower station feeder to collect the traveling wave signals generated when a fault occurs; Signal monitoring devices are arranged at multiple nodes of the feeder to record the amplitude changes of the traveling wave signal during the transmission process; The signal transmission analysis module calculates the traveling wave attenuation law of the feeder by establishing a theoretical propagation model, and compares the actual measured attenuation data with the theoretical model to determine the rationality of the signal transmission path; The signal authenticity verification module performs frequency analysis on the traveling wave signal with unreasonable signal transmission path, extracts its frequency spectrum characteristics, matches the extracted frequency spectrum with the preset fault traveling wave feature library, and verifies the authenticity of the signal source; The positioning accuracy prediction module predicts the accuracy of feeder fault point positioning based on the rationality of the signal transmission path and the authenticity of the signal source; based on the prediction results, the accuracy of feeder fault point positioning is divided into accurate positioning and inaccurate positioning; Positioning correction module: for inaccurate positioning, it continuously corrects the positioning deviation caused by clock synchronization error according to the prediction results to improve the accuracy of fault point positioning, including dynamically adjusting the traveling wave propagation speed and line impedance according to the prediction results; The fault visualization and linkage module combines the location information of the hydropower station feeder fault point with the geographic information system to generate a visual location map of the fault point; Cooperate with protection devices to achieve rapid fault isolation and line reconstruction, shorten fault recovery time, and reduce the scope of power outage.

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