Fault monitoring system and method for high-capacity power transmission line

Abstract

The invention discloses a fault monitoring system and method for a high-capacity power transmission line, and relates to the field of fault monitoring, and the system comprises a power transmission line information acquisition subsystem and a terminal service subsystem. The power transmission line information acquisition subsystem is installed on a tower of a power transmission line. The power transmission line information acquisition subsystem is in wireless communication with the terminal service subsystem; the power transmission line information acquisition subsystem is used for acquiring magnetic information during operation of a power transmission line; and the terminal service subsystem is used for carrying out fault monitoring on the high-capacity power transmission line based on the magnetic information. Influences of short circuit faults are reduced, repairing time is shortened, maintenance cost is reduced, and the risk that operators are exposed in a possible fault occurrence area is reduced as much as possible.

Description

Technical Field

[0001] The present application relates to the field of fault monitoring, and in particular to a fault monitoring system and method for a large-capacity power transmission line. Background Art

[0002] The distribution network is a key component of the power grid, which steps down the voltage of the high-voltage transmission system and delivers the electricity to end users. The distribution system covers a wide geographical area and can deliver electricity to all consumers in cities and remote villages. The feeder terminals of the 11kV overhead distribution are connected to the public transformer to further reduce the voltage according to user needs.

[0003] Generally, overhead transmission lines are exposed to harsh environments, especially overhead primary distribution lines. Faults on these primary distribution lines are caused by a variety of reasons, and short-circuit faults (i.e., SC faults) are the most common type of faults. Among them, microprocessor-based overcurrent relays installed in substations can be used for SC fault identification of primary distribution circuits. However, line personnel are required to manually check the distribution lines until the specific location of the SC fault is determined. Another method is to install remote terminal units (RTUs) based on intelligent electronic devices (IEDs) at predetermined distances on each three-phase line to locate such SC faults. These RTUs communicate with each other and with the central unit of the substation through communication media. However, these devices require the IED to be connected to the high-voltage line, which increases the complexity of the equipment design. At the same time, line personnel need to touch the line during installation and maintenance, resulting in low monitoring efficiency and high danger.

[0004] At present, there are technologies for locating fault locations in distribution networks, which can be mainly divided into three categories: impedance-based fault estimation methods, traveling wave technologies, and theory-based methods. Among them, the impedance-based fault estimation method is to obtain the voltage and current values ​​in normal and fault states, and use the distribution line model to calculate various line parameters to identify faults. This method requires the design of a filter system to obtain the phase voltage and current phasors. However, if the fault duration is short, the nominal response time of the filter will be affected, resulting in a large error in fault location. In the traveling wave technology, the shock wave caused by the fault propagates along the distribution line at the speed of light. Then the reflected wave composed of current and voltage waveforms is checked with a time domain reflectometer, and the fault location is determined by correlating the difference in arrival time at both ends of the line. However, the main limitation of this technology is that it requires a measuring instrument with a high sampling rate (in MHz). Based on the above description, the existing technologies for locating fault locations in distribution networks have reasonable fault location accuracy, but these technologies require the equipment to be connected to the overhead transmission line, which has the disadvantages of large impact of short-circuit faults and high maintenance costs, and requires operators to be exposed to areas where faults may occur, and the personal safety of operators cannot be guaranteed.

[0005] Based on the above description, in order to reduce the impact of short circuit faults, shorten repair time, reduce maintenance costs, and minimize the risk of workers being exposed to areas where faults may occur, developing a practical solution that can locate faults in distribution systems has become an urgent issue to be solved. Summary of the invention

[0006] The purpose of this application is to provide a fault monitoring system and method for a large-capacity transmission line, which can reduce the impact of short-circuit faults, shorten repair time, reduce maintenance costs, and minimize the risk of operators being exposed to areas where faults may occur.

[0007] To achieve the above objectives, this application provides the following solutions:

[0008] In a first aspect, the present application provides a fault monitoring system for a large-capacity power transmission line, including: a power transmission line information acquisition subsystem and a terminal service subsystem;

[0009] The transmission line information acquisition subsystem is installed on the transmission line tower; the transmission line information acquisition subsystem communicates wirelessly with the terminal service subsystem; the transmission line information acquisition subsystem is used to acquire magnetic information of the transmission line during operation; the terminal service subsystem is used to perform transmission line fault monitoring based on the magnetic information.

[0010] Optionally, the transmission line information acquisition subsystem includes:

[0011] A sensor module is used to obtain magnetic signals during the operation of the transmission line and process the magnetic signals to obtain sensing signals;

[0012] A coprocessor module, connected to the sensor module, for acquiring and processing the sensor signal in real time, obtaining magnetic information, and for performing communication processing on the magnetic information;

[0013] A storage and transmission module, connected to the coprocessor module, communicates with the terminal service subsystem, and is used for storing the magnetic information in real time;

[0014] The backup power supply module is respectively connected to the coprocessor module and the storage and transmission module to provide electric energy.

[0015] Optionally, the sensor module includes:

[0016] Sensors for acquiring magnetic signals during the operation of transmission lines;

[0017] A magnetostatic filter connected to the sensor and used to eliminate noise of the magnetic signal and obtain magnetostatic information;

[0018] an amplifier, connected to the magnetostatic filter, for amplifying the magnetostatic information;

[0019] An analog-to-digital converter is connected to the amplifier and is used to convert the amplified static magneto information into the sensing signal.

[0020] Optionally, the sensor is a magnetoresistive sensor.

[0021] Optionally, the coprocessor module includes:

[0022] A first coprocessor, connected to the sensor module, for acquiring and processing the sensor signal in real time to obtain the magnetic information;

[0023] The second coprocessor is connected to the first coprocessor and the storage and transmission module, and is used for communication processing of the magnetic information.

[0024] Optionally, the terminal service subsystem includes:

[0025] A cloud server communicates with the power transmission line information acquisition subsystem, and is used to obtain a fault monitoring result of the power transmission line based on the magnetic information; the fault monitoring result includes a fault location and a fault type; the fault type includes a short circuit fault and a dead zone fault;

[0026] The intelligent terminal communicates with the cloud server and is used to retrieve, adjust and visually display the fault monitoring results.

[0027] Optionally, the smart terminal is one or more of a desktop computer, a laptop computer, a smart phone, a tablet computer, an Internet of Things device, and a portable wearable device.

[0028] Optionally, the storage and transmission module includes:

[0029] A SIM card, connected to the coprocessor module, for storing the magnetic information in real time;

[0030] The antenna is connected to the SIM card and communicates with the terminal service subsystem.

[0031] Optionally, the backup power supply module is powered by solar energy.

[0032] In a second aspect, the present application provides a method for monitoring a fault of a large-capacity power transmission line, comprising:

[0033] The magnetic signals of different nodes in the operation of the transmission line are obtained according to the set number of cycles, and the magnetic signals are filtered, amplified and analog-to-digital converted to obtain a sensor signal sequence; the tower equipped with the transmission line information acquisition subsystem is regarded as a node;

[0034] Co-processing the sensing information in the sensing signal sequence to obtain a magnetic information sequence;

[0035] generating a monitoring waveform based on the magnetic information sequence;

[0036] When the peak value in the monitoring waveform is greater than a threshold value, it is determined that a short circuit fault occurs in the transmission line;

[0037] Determine the fault location based on the maximum peak value in the monitoring waveform and the dead value adjacent to the maximum peak value;

[0038] When the peak value in the monitoring waveform is a dead waveform, it is determined that a dead zone fault occurs in the power transmission line, and a node corresponding to the starting point of the dead waveform is determined as the fault location.

[0039] According to the specific embodiments provided in this application, this application has the following technical effects:

[0040] The present application provides a fault monitoring system and method for a large-capacity power transmission line. By installing a transmission line information acquisition subsystem on a transmission line tower, the impact of a short circuit fault can be reduced. In addition, by setting a terminal service subsystem that wirelessly communicates with the transmission line information acquisition subsystem, fault monitoring is implemented based on the acquired magnetic information, which can shorten the repair time, reduce maintenance costs, and minimize the risk of operators being exposed to areas where faults may occur. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] 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 of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0042] Figure 1 A schematic diagram of an implementation flow of a fault monitoring system for a large-capacity power transmission line provided in one embodiment of the present application;

[0043] Figure 2 A schematic diagram of horizontal layout parameters of a power distribution line provided in an embodiment of the present application;

[0044] Figure 3 A schematic diagram of a magnetic field caused by a current-carrying conductor at a sensor point provided by an embodiment of the present application;

[0045] Figure 4 A schematic diagram of the installation and monitoring of a fault monitoring system for a large-capacity power transmission line provided in one embodiment of the present application;

[0046] Figure 5 For Figure 4 Schematic diagram of monitoring results corresponding to sensor module A;

[0047] Figure 6 For Figure 4 Schematic diagram of monitoring results corresponding to sensor module B;

[0048] Figure 7 For Figure 4 Schematic diagram of monitoring results corresponding to sensor module C;

[0049] Figure 8 A schematic diagram of a potential scenario provided for an embodiment of the present application;

[0050] Fig. 9 A schematic flow chart of a method for monitoring a fault of a large-capacity power transmission line provided in another embodiment of the present application;

[0051] Fig.10 A schematic diagram of fault monitoring results of a large-capacity transmission line provided in one embodiment of the present application. DETAILED DESCRIPTION

[0052] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0053] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0054] In an exemplary embodiment, the present application provides a fault monitoring system for a large-capacity power transmission line, the system comprising: a power transmission line information acquisition subsystem and a terminal service subsystem.

[0055] The transmission line information acquisition subsystem is installed on the transmission line tower. The transmission line information acquisition subsystem communicates wirelessly with the terminal service subsystem. The transmission line information acquisition subsystem is used to obtain magnetic information when the transmission line is running. The terminal service subsystem is used to perform fault monitoring of large-capacity transmission lines based on magnetic information.

[0056] In an exemplary embodiment, the power transmission line information acquisition subsystem adopted in the present application includes: a sensor module, a coprocessor module, a storage and transmission module, and a backup power supply module.

[0057] The sensor module is used to obtain magnetic signals during the operation of the transmission line and process the magnetic signals to obtain sensing signals. Figure 1 As shown, the sensor module consists of a sensor (such as a magnetoresistive sensor), a static magnetofilter, an amplifier, and an analog-to-digital converter. When the overhead transmission line is in operation, the magnetoresistive sensor is used to obtain magnetic signals during the operation of the overhead transmission line. The acquired magnetic signal is filtered through a static magnetofilter to eliminate noise and obtain static magneto information (i.e., useful magnetic signals). The amplifier then gains the static magneto information to a set multiple (e.g., 1000 times). Finally, the amplified single signal is converted into a sensing signal (i.e., usable data) through an analog-to-digital converter.

[0058] The coprocessor module is connected to the sensor module and is mainly used to acquire and process the sensor signal in real time, obtain magnetic information, and perform communication processing on the magnetic information. Figure 1 As shown, the coprocessor module consists of two coprocessors, namely the first coprocessor P1 and the second coprocessor P2. The first coprocessor P1 is used for processing sensor signals to ensure timely acquisition and processing of sensor signals, thereby ensuring continuous fault detection without interruption due to communication delays. The second coprocessor P2 is used for communication processing to ensure timely and smooth information transmission.

[0059] The storage and transmission module is connected to the coprocessor module and communicates with the terminal service subsystem for real-time storage of magnetic information. In this embodiment, the storage and transmission module is a module composed of a SIM card and an antenna (such as a GSM antenna). Figure 1The SIM card is used to store useful data to be saved in the coprocessor module, and the GSM antenna is used to realize two-way communication between the terminal service subsystem and the coprocessor.

[0060] The backup power module is connected to the coprocessor module and the storage and transmission module respectively to provide power. In this embodiment, the backup power module adopts solar power supply. Figure 1 As shown in the figure, the backup power module consists of a solar panel, a battery charge and discharge circuit, a controller, a Lipo battery, and a voltage regulation unit (a voltage regulator and a boost circuit). When there is sufficient light energy, the solar panel converts the light energy into electrical energy, and the voltage regulator and boost circuit ensure stable power supply. The battery charge and discharge circuit and the controller control the charge and discharge of the Lipo battery. In the absence of any charging equipment, the backup battery can be enabled to run for up to 2 and a half days (especially convenient for operation on rainy days).

[0061] In an exemplary embodiment, Figure 1 As shown, the terminal service subsystem provided in the present application may include: a cloud server and a smart terminal.

[0062] The cloud server communicates with the transmission line information acquisition subsystem to obtain the fault monitoring results of the large-capacity transmission line based on magnetic information. The fault monitoring results include the fault location and fault type. The fault types include short circuit faults and dead zone faults.

[0063] The intelligent terminal communicates with the cloud server to retrieve, adjust and visualize the fault monitoring results.

[0064] In addition, the terminal service subsystem may also include only smart terminals. The setting of smart terminals facilitates operators to monitor and control. Among them, the smart terminal is one or more of a desktop computer, a laptop computer, a smart phone, a tablet computer, an Internet of Things device, and a portable wearable device.

[0065] In an exemplary embodiment, Figure 2 As shown in the figure, it is assumed that the transmission line information acquisition subsystem ( Figure 2 The A' in the figure is installed at the center of the distribution pole, 2 meters away from the current-carrying conductor. The conductors are placed in a horizontal (flat) configuration, and the distance between each conductor is the same. At this time, the magnetic field (MF) caused by a current-carrying conductor at A' is as follows: Figure 3 shown. Figure 3 In the figure, a represents the conductor, y represents the direction perpendicular to the ground and parallel to the pole, x represents the direction parallel to the ground and perpendicular to the transmission line, and r represents the direction perpendicular to the ground and parallel to the pole. a and θ both represent position vectors, B ax represents the X-axis component of MF generated by conductor a in the sensor, Bay represents the Y-axis component of MF generated by conductor a in the sensor, B a It represents the MF generated by conductor a in the sensor.

[0066] Based on the above description, if Figure 4 As shown in the figure, when the potential scenario is a short circuit in the overhead distribution circuit, the magnetic resistance sensor is used to collect the magnetic signal near the distribution pole, the noise is eliminated by the static magnetic filter, and the usable signal is amplified to 1000 times by the amplifier. Finally, the single signal is converted into usable data by the digital-to-analog converter.

[0067] The acquired sensor signals are processed in the coprocessor. The sensor inputs are collected for a set number of cycles and then compared with a predefined set of conditions. This process is repeated until a potential fault is detected. Figure 8 The potential scenario shown here is how this process works:

[0068] According to the Biot-Savart law, the MF formula generated by a single wire (infinitely long straight wire) in the sensor is given as:

[0069]

[0070] In the formula, μ 0 is the magnetic permeability of air, I is the current flowing in the conductor, and r is the distance between the measurement point and the current source. Figure 3 The MF produced by conductor a at the sensor point is shown to be decomposed into B ax and B ay component, and its direction is along the tangent line of the field line. a and θ are calculated using trigonometric identities. The MF distribution around the conductor is in the form of concentric circles. Overhead conductors are in the form of catenaries (sags) between the support points. In MF analysis, the effect of sag is often neglected if the conductor sag is small compared to the span. Therefore, the axial component of MF along the distribution line is invalid, especially near the pole structure.

[0071]

[0072] In the formula, B a ,B b and B c are the MF components generated by phase currents a, b, and c, respectively, and are unit vectors along the X, Y, and Z axes. a ,I b and I c They are phase currents a, b and c respectively. x ,i y and i z are the unit vectors of the x, y and z axes respectively. is the magnetic induction intensity vector. Assuming the current is in the Z direction, the magnetic sensor monitors the alternating magnetic field along the direction of its specified magnetic circuit. Since the magnetic sensor is linear and only measures MF along its sensitivity direction. Therefore, since a single three-phase line generates MF at the sensor point along the horizontal direction, we have:

[0073]

[0074] In the formula, B x It is the component of MF generated at the sensor point along the horizontal direction.

[0075] In primary distribution lines, MF is proportional to current. When there are no load imbalance events (such as daily and seasonal demand changes), the MF level will fluctuate around the overhead conductors. Under balanced conditions, the amplitude and frequency of the three-phase current (forward current only) are equal, and the phase shift is 120°. The current in each phase is related to the other phase by the phase difference determined by the sine and cosine terms. Assuming I b (Phase current) is the reference current, where the phase current is divided into in-phase current and out-of-phase current. Therefore, the angle α here is equal to 0°. The MF component is calculated by multiplying the geometric term by the appropriate current coefficient, and their relationship is as follows:

[0076]

[0077] In the formula, B x,in is the input mf component, r b is the distance between the measurement point and the b-phase current source, r c is the distance between the measurement point and the c-phase current source, and γ is the phase angle of c-phase.

[0078] MF is sensitive to changes caused by load imbalance on distribution lines. Hence, MF levels are higher than estimated in balanced lines. When unbalanced conditions prevail, symmetrical components (zero-sequence and negative-sequence currents) are added to the balanced line currents, increasing MF levels. When an unbalance factor of 20% is added to the 11kV overhead line, the MF level increases threefold. And, the magnitude part of the unbalance factor dominates the effect on MF. Hence, the MF output is modified to include the unbalance factor U a , U b and U c These unbalance factors will cause the corresponding current (I a ,I b and I c ) amplitude differences. In addition, the uncertainty in distance mentioned earlier also increases these unbalanced factors. Compared with the balanced current case, the phase angles (α, β and γ) are different, such as Figure 8 Therefore, the MF component is expressed as follows:

[0079]

[0080] In the formula, B x,out is the mf component of the output.

[0081] When a short-circuit fault occurs in an overhead distribution line, the unbalanced current rises rapidly to a very high point and varies depending on the distance between the source and the fault location. The MF level also increases to very high values, which can be clearly distinguished from the unbalanced load case. The total MF caused by the SC fault (denoted as B total ) is represented by the following equation:

[0082]

[0083] Here, the phase angles of the phase currents are not exactly 120° apart. Therefore, the actual angles (α, β, and γ) are used to calculate the sine and cosine terms. The SC current will contribute to the unbalance factor U a The MF level of the three-phase overhead distribution line under short-circuit conditions is described by equations (7) to (9).

[0084] In radial distribution networks, feeder protection is implemented by instantaneous and inverse time overcurrent relays. Among them, the power supply company uses automatic reclosing of overhead feeder circuit breakers. The purpose of automatic reclosing is to detect faults, solve the faults, and restore power supply services to users. Before starting to lock, the automatic reclosing follows a predefined sequence of switching operations to respond to permanent SC faults. Permanent SC faults occur at the 11kV power supply on the distribution line. At this time, the MF waveform is equal to the current waveform.

[0085] Based on the peak analysis of the MF waveform, the present application locates SC faults on the main feeder and other branch main feeders based on the system provided above. MF is sensed near the main feeder and branch feeder of the 11kV radial distribution network. The output MF waveform has two different states: normal and fault. The unbalanced load effect is taken into account in the normal state, which causes different line currents on the feeder, resulting in corresponding fluctuations in the sensed MF.

[0086] The most common SC fault on primary distribution lines is a single-phase to ground fault. The effects caused by the fault resistance and ground resistance are negligible and do not affect the accuracy. Because the ratio of the fault current to the normal current is the same as the ratio of the fault MF to the normal MF, the measured MF is proportional to the magnitude of the SC fault.

[0087] Based on the obtained fault information, the data is further compared with the previous and upcoming values, and then the fault range is determined and the data is captured to achieve fault location. The fault location principle is:

[0088] Wait for all nodes (towers where the transmission line information acquisition subsystem will be installed) to send data and start comparing with each other. Because the impedance of the fault point is the smallest, the magnetic field value of the node closest to the short circuit is the largest. Other nodes also have high values. Nodes located after the potential short-circuit node usually enter a dead value state because the current has been grounded at the previous node. Figure 4-Figure 7 As shown in Figure 1, a short circuit occurs between the 2nd and 3rd pole nodes. At this time, the 2nd pole node will give the maximum magnetic field value, and then enter the dead value state. In contrast, the magnetic field value of the 1st pole node is smaller, and the 3rd pole node directly enters the dead value state without magnetic field jump. The magnetic field jump usually lasts for several cycles before the circuit breaker operates and the line is cut off. The specific process of this fault location is as follows Fig. 9 As shown, the fault data is sent to a cloud server, and the above fault location method is run on the cloud server.

[0089] In actual application, the node sends pulses to the cloud server at specific time intervals, continuously checks whether the data request sent by the cloud server is received, and can be controlled by the cloud server through a set of commands. Communication does not affect short-circuit detection because short-circuit detection is performed independently.

[0090] Based on this description, the coprocessor handles communication and sensor related information separately to ensure continuous fault detection without interruption due to communication delays. The coprocessor used has one core for processing all data related to the MF sensor, while the other core runs independently to communicate between servers. There are two ways of communication, either requesting data from the cloud server or pushing data when it is needed.

[0091] In another exemplary embodiment of the present application, a real experiment is conducted on a dedicated 11kV overhead feeder in the I-10 area of ​​Islamabad using the system provided by the present application as an example to illustrate the advantages of the solution provided by the present application. The sensor modules are placed at different spans of 300m (the span between two consecutive towers is 100m), and then the sensed data is transmitted to the data center (i.e., the storage and transmission module) to locate the fault span. In order to observe real-time data on site, a Pico oscilloscope is used to observe real-time sensor data on a laptop or PC.

[0092] In the experiment, a single-phase grounding SC fault, which is common on 11kV overhead lines, can be observed. The waveform of the SC fault is analyzed in PicoScope 6 software, where the waveform is sampled at a rate of 25kS / sec. The maximum number of bits is set to 12Bt. The magnetic sensor is installed at an appropriate distance of nearly 2m below the conductor. The final experimental results are shown in Figure 1. Fig.10 shown.

[0093] In this experiment, the peak amplitude is calculated based on the obtained experimental results by measuring the magnetic field strength. The process of calculating the peak amplitude includes:

[0094] A. By passing the time k 0 The amplitude of the previous moment (k 0-1 ) and the next moment (k 0+1 ) values ​​to identify the peak.

[0095] B. Calculate and store the amplitudes of positive and negative peaks.

[0096] C. Analyze the peak spacing, i.e. the amplitude.

[0097] Further, based on the above results, abnormal features are detected, including:

[0098] A. Calculate the maximum peak value from the aforementioned peak array and compare it with the predefined conditions to check whether an anomaly has occurred.

[0099] a. If the maximum peak is within the average range of the peak, it is in normal condition.

[0100] b. If the detected peak value is significantly greater than the average value or is a dead waveform, it is in a fault state.

[0101] B. Compare with the short circuit or dead zone status of other nodes.

[0102] Further, the fault detection algorithm is designed to detect two states, short circuit or dead waveform.

[0103] (1) Detect short circuit:

[0104] A). Within the time interval t, for the magnetic field strength measured by the sensor, if the measurement change of the magnetic field sensor between adjacent cycles exceeds the set threshold, the window array is marked.

[0105] B). Compare with predefined conditions.

[0106] C). Repeat steps A) and B) for the next time interval.

[0107] In actual application, locating faults requires at least two or more nodes, and the number of nodes is proportional to the degree of narrowing the search area for short-circuit fault events. When locating between two nodes, the short-circuit state will be detected and distinguished, and the cloud server will locate the fault area.

[0108] In summary, the present application has the following advantages over the prior art:

[0109] 1. This application uses a magnetoresistive sensor (i.e., a magnetic sensor) to achieve non-contact monitoring of the magnetic field of overhead transmission lines, and uses changes in magnetic field strength to detect short-circuit faults, which can greatly reduce the complexity of equipment installation and maintenance and avoid the risk of contacting high-voltage lines in traditional methods. In addition, due to the non-contact characteristics of the sensor, it can effectively reduce the risk of personnel being exposed to high-voltage power grids and improve safety.

[0110] 2. This application calculates and compares the peak value of the magnetic field at the current moment with the amplitude before and after it, identifies abnormal characteristics, such as fault conditions such as short circuit or dead waveform, and can quickly identify fault conditions, especially when a short circuit fault occurs. It can quickly detect abnormal peaks and respond in time. Compared with traditional impedance-based fault estimation methods, this application has improved response speed and accuracy. Compared with traveling wave technology, a measuring instrument with a high sampling rate (in MHz) is required, and this application has reduced production costs.

[0111] 3. This application can determine whether the power grid is in a fault state, and send data to the cloud server or receive remote control commands through the storage and transmission module (i.e., GSM module). This allows the system to not only monitor the fault state in real time, but also achieve remote management, thereby greatly improving the timeliness of fault location and the convenience of remote management, reducing the frequency and time of manual inspections, reducing labor costs, and shortening the response time of fault handling, thereby improving the stability and reliability of the distribution network.

[0112] 4. This application compares and locates data through multiple nodes, which can accurately determine the location of the fault, reduce the fault area, improve positioning accuracy, and avoid errors caused by only a single sensor data in traditional methods. It is especially important for fault location in large-scale distribution networks, and improves fault repair efficiency and accuracy.

[0113] 5. Each node of the present application can be equipped with an independent processor for short-circuit detection, and send data requests to the cloud server through independent communication, so that short-circuit detection and data communication will not interfere with each other, ensuring the stability and efficiency of the system, thereby avoiding the impact of fault detection due to communication delays or interruptions, and ensuring the efficient and reliable operation of the monitoring system when a fault occurs.

[0114] 6. This application uses solar power supply and is equipped with a controller for solar charging to ensure continuous operation in an environment without external power supply, which not only improves the energy self-sufficiency of the system, but also avoids dependence on traditional power sources. It is especially suitable for remote areas far away from urban power grids. In addition, the solar power supply system has the advantages of green environmental protection and sustainable development.

[0115] Based on the same inventive concept, the embodiment of the present application also provides a method for monitoring a large-capacity transmission line fault applied to the large-capacity transmission line fault monitoring system mentioned above. The implementation scheme for solving the problem provided by the method is similar to the implementation scheme recorded in the above system, so the specific limitations in the embodiments of one or more large-capacity transmission line fault monitoring methods provided below can refer to the limitations of the large-capacity transmission line fault monitoring method above, and will not be repeated here.

[0116] In an exemplary embodiment, a fault monitoring method for a large-capacity power transmission line is provided, comprising:

[0117] Step 1: Obtain magnetic signals of different nodes in the operation of the transmission line according to the set number of cycles, and obtain a sensor signal sequence after filtering, amplifying and analog-to-digital conversion of the magnetic signals. The tower equipped with the transmission line information acquisition subsystem is regarded as a node.

[0118] Step 2: Coordinately process the sensing information in the sensing signal sequence to obtain a magnetic information sequence.

[0119] Step 3: Generate a monitoring waveform based on the magnetic information sequence.

[0120] Step 4: When the peak value in the monitoring waveform is greater than the threshold, it is determined that a short circuit fault occurs in the transmission line.

[0121] Step 5: Determine the fault location based on the maximum peak value in the monitoring waveform and the dead value adjacent to the maximum peak value.

[0122] Step 6: When the peak value in the monitored waveform is a dead waveform, it is determined that a dead zone fault occurs in the transmission line, and the node corresponding to the starting point of the dead waveform is determined as the fault location.

[0123] Based on the above description, compared with the prior art, the present application has the following advantages:

[0124] (1) High efficiency:

[0125] This application uses a non-contact magnetic field sensor for fault monitoring, avoiding the cumbersome steps of contacting high-voltage lines in traditional methods, thereby improving monitoring efficiency and reducing the time for equipment troubleshooting. Real-time monitoring and automatic identification enable the system to respond quickly, greatly shortening the response time for fault location.

[0126] (2) High precision:

[0127] This application can accurately locate the fault area in a short time by accurately calculating the peak value and amplitude of the magnetic field and comparing and locating the data between nodes. Compared with the traditional estimation technology based on current and voltage waveforms, this method has higher positioning accuracy and smaller error.

[0128] (4) Safety:

[0129] Since a non-contact magnetic field sensor is used, the present application greatly reduces the risk of operators directly contacting high-voltage lines and improves the safety of the system.

[0130] (5) Low cost:

[0131] This application uses low-power solar power supply, which reduces the dependence on external power supply, saves electricity costs, and due to the non-contact installation characteristics of the sensor, it also reduces the cost of equipment installation and maintenance. In addition, the intelligent fault detection and positioning system can reduce manual inspections and improve cost-effectiveness.

[0132] (6) Scalability and adaptability:

[0133] This application can expand more nodes as needed to improve the accuracy of fault location. Since this design does not rely on contact with high-voltage lines, it can be widely used in distribution networks of different sizes, including power grids in cities and remote areas.

[0134] (7) Remote management and automation:

[0135] By carrying out remote data transmission and control, this application can realize automated management, reduce manual intervention, and improve management efficiency, especially in remote areas, without the need for a large number of manual inspections.

[0136] In an exemplary embodiment, a computer device is provided, which may be a server or a terminal. The computer device includes a processor, a memory, an input / output interface (I / O for short) and a communication interface. The processor, the memory and the input / output interface are connected via a system bus, and the communication interface is connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store fault monitoring data of a large-capacity power transmission line. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a method for fault monitoring of a large-capacity power transmission line is implemented.

[0137] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0138] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0139] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0140] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0141] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiments can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0142] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.

[0143] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0144] Specific examples are used herein to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method and core ideas of the present application. At the same time, for those of ordinary skill in the art, according to the ideas of the present application, there will be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be understood as limiting the present application.

Claims

1. A fault monitoring system for a large-capacity power transmission line, characterized in that: The fault monitoring system for large-capacity power transmission lines comprises: a power transmission line information acquisition subsystem and a terminal service subsystem; The transmission line information acquisition subsystem is installed on the transmission line tower; the transmission line information acquisition subsystem communicates wirelessly with the terminal service subsystem; the transmission line information acquisition subsystem is used to acquire magnetic information of the transmission line during operation; the terminal service subsystem is used to perform transmission line fault monitoring based on the magnetic information.

2. The fault monitoring system for a large-capacity power transmission line according to claim 1, characterized in that: The transmission line information acquisition subsystem comprises: A sensor module is used to obtain magnetic signals during the operation of the transmission line and process the magnetic signals to obtain sensing signals; A coprocessor module, connected to the sensor module, for acquiring and processing the sensor signal in real time, obtaining magnetic information, and for performing communication processing on the magnetic information; A storage and transmission module, connected to the coprocessor module, communicates with the terminal service subsystem, and is used for storing the magnetic information in real time; The backup power supply module is respectively connected to the coprocessor module and the storage and transmission module to provide electric energy.

3. The fault monitoring system for a large-capacity power transmission line according to claim 2, characterized in that: The sensor module comprises: Sensors for acquiring magnetic signals during the operation of transmission lines; A magnetostatic filter connected to the sensor and used to eliminate noise of the magnetic signal and obtain magnetostatic information; an amplifier, connected to the magnetostatic filter, for amplifying the magnetostatic information; An analog-to-digital converter is connected to the amplifier and is used to convert the amplified static magneto information into the sensing signal.

4. The fault monitoring system for a large-capacity power transmission line according to claim 3, characterized in that: The sensor is a magnetoresistive sensor.

5. The fault monitoring system for a large-capacity power transmission line according to claim 2, characterized in that: The coprocessor module comprises: A first coprocessor, connected to the sensor module, for acquiring and processing the sensor signal in real time to obtain the magnetic information; The second coprocessor is connected to the first coprocessor and the storage and transmission module, and is used for communication processing of the magnetic information.

6. The fault monitoring system for a large-capacity power transmission line according to claim 1, characterized in that: The terminal service subsystem includes: A cloud server communicates with the power transmission line information acquisition subsystem, and is used to obtain a fault monitoring result of the power transmission line based on the magnetic information; the fault monitoring result includes a fault location and a fault type; the fault type includes a short circuit fault and a dead zone fault; The intelligent terminal communicates with the cloud server and is used to retrieve, adjust and visually display the fault monitoring results.

7. The fault monitoring system for a large-capacity power transmission line according to claim 6, characterized in that: The smart terminal is one or more of a desktop computer, a laptop computer, a smart phone, a tablet computer, an Internet of Things device, and a portable wearable device.

8. The fault monitoring system for a large-capacity power transmission line according to claim 2, characterized in that: The storage and transmission module includes: A SIM card, connected to the coprocessor module, for storing the magnetic information in real time; The antenna is connected to the SIM card and communicates with the terminal service subsystem.

9. The fault monitoring system for a large-capacity power transmission line according to claim 2, characterized in that: The backup power supply module adopts solar energy power supply mode.

10. A method for fault monitoring of a large-capacity power transmission line, characterized in that: The fault monitoring method of the large-capacity power transmission line comprises: The magnetic signals of different nodes in the operation of the transmission line are obtained according to the set number of cycles, and the magnetic signals are filtered, amplified and analog-to-digital converted to obtain a sensor signal sequence; the tower equipped with the transmission line information acquisition subsystem is regarded as a node; Co-processing the sensing information in the sensing signal sequence to obtain a magnetic information sequence; generating a monitoring waveform based on the magnetic information sequence; When the peak value in the monitoring waveform is greater than a threshold value, it is determined that a short circuit fault occurs in the transmission line; Determine the fault location based on the maximum peak value in the monitoring waveform and the dead value adjacent to the maximum peak value; When the peak value in the monitoring waveform is a dead waveform, it is determined that a dead zone fault occurs in the power transmission line, and a node corresponding to the starting point of the dead waveform is determined as the fault location.

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