CN117517877A - Distributed traveling wave online measurement fault positioning system - Google Patents
Distributed traveling wave online measurement fault positioning system Download PDFInfo
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Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/08—Locating faults in cables, transmission lines, or networks
- G01R31/081—Locating faults in cables, transmission lines, or networks according to type of conductors
- G01R31/085—Locating faults in cables, transmission lines, or networks according to type of conductors in power transmission or distribution lines, e.g. overhead
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/08—Locating faults in cables, transmission lines, or networks
- G01R31/081—Locating faults in cables, transmission lines, or networks according to type of conductors
- G01R31/086—Locating faults in cables, transmission lines, or networks according to type of conductors in power transmission or distribution networks, i.e. with interconnected conductors
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
- Y04S10/52—Outage or fault management, e.g. fault detection or location
Abstract
The invention relates to a distributed traveling wave online measurement fault positioning system which comprises a Beidou satellite accurate time service and positioning module, an FTU device, a distributed traveling wave online measurement fault positioning device, a block chain-based data management and verification system, a user interface and an interaction module, wherein the Beidou module provides accurate time and position information, the FTU device monitors power grid parameters in real time and responds to faults rapidly, the traveling wave positioning device detects power grid states and fault positions in real time, a high-speed data acquisition and artificial intelligence-based fault identification program is adopted, a block chain system guarantees the safety and consistency of data, the user interface displays power grid data and provides interaction functions, and the whole system is connected through data communication, an API and a software interface, so that real-time, accurate and safe fault positioning and data management are ensured, the stability and reliability of a power grid are improved, the maintenance cost is reduced, and the user experience is enhanced.
Description
Technical Field
The invention relates to a distributed traveling wave online measurement fault positioning system, in particular to a distributed traveling wave online measurement fault positioning system applied to the technical fields of power systems and power electronics.
Background
In recent years, with the rapid development of a power system, the requirements on the stability and the safety of the power system are higher and higher, and the ultra-high voltage transmission line has serious influence on the whole power system once the fault occurs due to the characteristics of long distance and large capacity, so that the rapid and accurate positioning of the fault of the ultra-high voltage transmission line is a key for the safe and stable operation of the power system.
The invention discloses a traveling wave fault positioning method of an extra-high voltage transmission line based on distributed monitoring in a Chinese patent CN114966309 specification, which analyzes phase current phase difference of fault phases so as to determine fault occurrence intervals and fault phases, and provides a fault positioning flow of the extra-high voltage transmission line based on the distributed monitoring, and specifically comprises the following steps: subtracting the normal state current amount from the fault current to obtain a current fault component; when the monitored current fault component is larger than the threshold value, a signal is sampled to the monitoring station at low frequency; judging a fault interval and a fault phase based on a current phase differential principle; sending instructions to four nearest monitoring points of the fault point to enable the monitoring points to send high-frequency traveling wave data to the monitoring station; performing traveling wave speed on-line measurement and fault positioning; and outputting a fault positioning result and a fault type. The influence of the length error of the line and the wave speed error of the traveling wave on fault location is reduced, and the fault location accuracy is effectively improved.
Although the above design reduces the influence of the line length error and the traveling wave speed error on fault location, effectively improves the fault location accuracy, certain limitations exist, such as the method may not be capable of measuring faults on line and locating specific fault places in real time, and in addition, due to lack of integration with a geographic information system, an maintainer may not be capable of directly checking the geographic position of the faults, which brings inconvenience to field overhaul.
Disclosure of Invention
Aiming at the prior art, the invention aims to solve the technical problems of how to measure faults online in real time, quickly respond to the faults and locate specific fault places, and integrate with a geographic information system so that an maintainer can directly check the geographic positions of the faults.
In order to solve the problems, the invention provides a distributed traveling wave online measurement fault positioning system which comprises a Beidou satellite accurate time service and positioning module, an FTU device, a distributed traveling wave online measurement fault positioning device, a block chain-based data management and verification system, a user interface and an interaction module.
The Beidou satellite accurate time service and positioning module is connected with the distributed traveling wave online measurement fault positioning device and the FTU device through data communication, the FTU device is connected with the distributed traveling wave online measurement fault positioning device through data communication, the distributed traveling wave online measurement fault positioning device is connected with the blockchain-based data management and verification system through data communication and API or software interface, the blockchain-based data management and verification system is connected with the user interface and the interaction module through data communication and API or software interface, the user interface and interaction module are connected with the Beidou satellite accurate time service and positioning module and the FTU device through API or software interface, and the user interface and interaction module are connected with the distributed traveling wave online measurement fault positioning device through control signals and data communication.
The Beidou satellite accurate time service and positioning module is used for providing accurate time and position information and comprises a satellite receiving antenna, a receiver and a data processing unit.
The FTU device is used for monitoring parameters such as current and voltage of the power grid in real time and rapidly responding when faults are detected, and comprises a fault detection module, a data acquisition module and a communication module.
The distributed traveling wave online measurement fault positioning device is used for detecting the running state and the fault position of the power grid in real time and comprises a sensor, a high-speed data acquisition card, a data processing unit and a fault identification program based on artificial intelligence.
The block chain-based data management and verification system is used for guaranteeing the safety and consistency of data and comprises a data node, an intelligent contract and a user interface.
The user interface and the interaction module are used for displaying power grid data and providing interaction functions, and comprise a data display interface, a fault query interface and a system management interface.
In the distributed traveling wave online measurement fault positioning system, the fault can be measured online in real time, meanwhile, the specific fault location can be responded and positioned quickly, and the distributed traveling wave online measurement fault positioning system can be integrated with a geographic information system, so that an maintainer can directly check the geographic position of the fault, and the efficiency and the accuracy of fault processing are improved.
As a further improvement of the application, the satellite receiving antenna is used for receiving signals of Beidou satellites, the receiver is used for analyzing satellite signals, extracting positioning and time service information, and the data processing unit is used for processing received signal data.
The sensor is used for detecting current and voltage signals of a line, the high-speed data acquisition card is used for acquiring signals output by the sensor at a high speed, the data processing unit is used for processing acquired data in real time and realizing a fault positioning algorithm, and the fault positioning algorithm is used for identifying the fault type of a power grid based on an artificial intelligent fault identification program.
As a still further improvement of the method, the fault detection module is used for monitoring key parameters such as current, voltage and the like in the power grid in real time and carrying out fault identification and classification.
The data acquisition module comprises a sensor, a high-speed data acquisition card and a data preprocessing function, and is used for carrying out high-precision and high-speed sampling on parameters such as current, voltage and the like in a power grid, and carrying out preprocessing operations such as filtering, amplifying or shrinking on acquired original data.
And the communication module is used for transmitting data in the FTU device, such as fault information, collected current and voltage data and the like, to the upper monitoring system or other equipment and receiving instructions of the upper monitoring system.
As a still further improvement of the present application, the artificial intelligence based fault recognition program includes a feature extraction module for extracting useful feature information from the raw data, a deep learning model for learning and recognizing different types of faults, and a fault database for storing historical fault data.
And the data node stores power grid operation data and fault data, and the intelligent contract realizes automatic verification and transaction confirmation of the data, and the user interface is used for users to inquire the data and submit new data.
As a further improvement of the application, the data display interface displays real-time operation data and historical data of the power grid, the fault inquiry interface displays historical fault records and fault positioning results, and the system management interface provides system configuration and management functions.
In addition to the further improvement of the application, the data processing unit comprises a signal processing algorithm, a traveling wave detection algorithm and a double-end positioning algorithm, wherein the signal processing algorithm, the traveling wave detection algorithm and the double-end positioning algorithm are used for accurately receiving and processing satellite signals in a complex environment, the traveling wave detection algorithm is used for accurately detecting traveling wave signals generated by faults, the double-end positioning algorithm is used for accurately calculating fault positions by utilizing data at two ends, the fault recognition program based on artificial intelligence comprises a feature engineering and a model selection technology, and the deep learning model suitable for fault recognition is used for determining feature parameters capable of accurately describing fault characteristics and selecting or designing.
As a further improvement to the present application, the blockchain-based data management and verification system includes data encryption and consensus mechanism techniques for ensuring the security of data during transmission and storage and for ensuring data consistency among all data nodes, and the user interface and interaction module also includes data visualization and interaction module techniques for presenting complex data to the user in an intuitive manner and for ensuring that the user can conveniently use the system functions.
The signal processing algorithm comprises a filtering algorithm, fourier transformation and wavelet transformation, the travelling wave detection algorithm comprises threshold detection and short-time Fourier transformation, the double-end positioning algorithm comprises a cross correlation method, a least square method and a neural network method, and the neural network method adopts forward propagation.
As a further improvement of the present application, comprising the steps of,
s1, starting and initializing;
s2, data acquisition and processing;
s3, synchronizing time and position;
s4, fault detection and positioning;
s5, data storage and verification;
s6, user interaction;
s7, fault response and repair;
s8, monitoring and managing the system;
s9, backing up and updating data;
s10, closing and maintaining the system.
In summary, the scheme has the following beneficial effects:
1. the fault positioning accuracy is improved, the fault position in the power grid can be accurately positioned by combining the Beidou satellite accurate time service and positioning module with the distributed traveling wave on-line measurement fault positioning device, and the fault positioning accuracy is improved.
2. The FTU device can monitor parameters such as current and voltage of the power grid in real time, responds rapidly when faults are detected, and can detect anomalies in the power grid in real time and locate faults rapidly by combining the design of the system, so that the fault response time is shortened, and the loss caused by the faults is reduced.
3. The data security and reliability, the data management and verification system based on the blockchain ensures the security and consistency of the data, and avoids the risks of data falsification and counterfeiting.
4. The maintenance efficiency is improved, and the maintenance team can rapidly acquire the detailed information and the geographic position of the fault through the user interface and the interaction module, so that the fault repairing efficiency is improved.
5. The system is enhanced in intellectualization, and the fault identification program design based on artificial intelligence enables the system to automatically identify faults of different types, so that the level of intellectualization of the system is further improved.
6. Time and position synchronization, accurate time service and positioning functions of the Beidou satellite are utilized, time and position synchronization among distributed equipment is guaranteed, and data accuracy is enhanced.
7. The maintenance cost is reduced, and the accurate fault detection and the quick response of the FTU reduce unnecessary maintenance work, thereby reducing the maintenance cost.
8. The stability of the power grid is improved, and the stability and the reliability of the power grid are improved by combining the real-time fault detection and the quick response of the FTU and other modules of the system.
9. The user-friendly interaction interface and the visual user interface enable a user to conveniently inquire the state and fault information of the power grid, and improve user experience.
10. The expandability of the system and the modularized design enable the system to have good expandability, and new functions and modules can be added according to requirements.
Drawings
FIG. 1 is a system block diagram of the present application;
FIG. 2 is a system workflow diagram of the present application;
FIG. 3 is a second system workflow diagram of the present application;
fig. 4 is a working flow chart of the Beidou satellite accurate time service and positioning module of the present application;
FIG. 5 is a workflow diagram of a distributed traveling wave online measurement fault locating device of the present application;
FIG. 6 is a block chain based data management and validation system workflow diagram of the present application;
FIG. 7 is a signal processing algorithm formulation of the present application;
FIG. 8 is a formula diagram of a traveling wave detection algorithm of the present application;
FIG. 9 is a graph of a double-ended positioning algorithm of the present application;
fig. 10 is a block diagram of the system architecture of the present application.
Detailed Description
Three embodiments of the present application are described in detail below with reference to the accompanying drawings.
First embodiment:
fig. 1-3 and 10 show.
A distributed traveling wave online measurement fault positioning system comprises a Beidou satellite accurate time service and positioning module, an FTU device, a distributed traveling wave online measurement fault positioning device, a block chain-based data management and verification system, a user interface and an interaction module.
The Beidou satellite accurate time service and positioning module is connected with the distributed traveling wave online measurement fault positioning device and the FTU device through data communication, the FTU device is connected with the distributed traveling wave online measurement fault positioning device through data communication, the distributed traveling wave online measurement fault positioning device is connected with the blockchain-based data management and verification system through data communication and API or software interface, the blockchain-based data management and verification system is connected with the user interface and the interaction module through data communication and API or software interface, the user interface and interaction module are connected with the Beidou satellite accurate time service and positioning module and the FTU device through API or software interface, and the user interface and interaction module are connected with the distributed traveling wave online measurement fault positioning device through control signals and data communication.
The Beidou satellite accurate time service and positioning module is used for providing accurate time and position information and comprises a satellite receiving antenna, a receiver and a data processing unit.
The FTU device is used for monitoring parameters such as current and voltage of the power grid in real time and rapidly responding when faults are detected, and comprises a fault detection module, a data acquisition module and a communication module.
The distributed traveling wave online measurement fault positioning device is used for detecting the running state and the fault position of the power grid in real time and comprises a sensor, a high-speed data acquisition card, a data processing unit and a fault identification program based on artificial intelligence.
The block chain-based data management and verification system is used for guaranteeing the safety and consistency of data and comprises a data node, an intelligent contract and a user interface.
The user interface and the interaction module are used for displaying power grid data and providing interaction functions, and comprise a data display interface, a fault query interface and a system management interface.
In the distributed traveling wave online measurement fault positioning system, the fault can be measured online in real time, meanwhile, the specific fault location can be responded and positioned quickly, and the distributed traveling wave online measurement fault positioning system can be integrated with a geographic information system, so that an maintainer can directly check the geographic position of the fault, and the efficiency and the accuracy of fault processing are improved.
The Beidou satellite accurate time service and positioning module receives signals of the Beidou satellite through a satellite receiving antenna. The method comprises the steps that a receiver performs preliminary processing on signals, a data processing unit further processes the data to provide accurate time and position information, a fault detection module of an FTU device monitors parameters such as current, voltage and the like of a power grid in real time, when a fault is detected, a data acquisition module starts to acquire related data and sends the data to a distributed traveling wave online measurement fault positioning device through a communication module, a sensor of the distributed traveling wave online measurement fault positioning device monitors the running state of the power grid, a high-speed data acquisition card acquires the data at a high speed, the data processing unit further processes the data, an artificial intelligent fault recognition program is based on the data to analyze the data to determine whether faults and positions of the faults exist, a block chain-based data management and verification system is used for transmitting the related data to the system after the distributed traveling wave online measurement fault positioning device detects the faults and determines the positions of the faults, the data are stored on data nodes of the block chain, automatic verification and transaction confirmation are performed through intelligent contracts, the safety and consistency of the data are ensured, and a user interface and an interaction module can check the real-time running state, a historical fault record and a fault positioning result of the power grid through a data display interface. The fault query interface allows a user to query for specific fault information, while the system management interface provides system configuration and management functionality.
By combining the accurate time service and positioning functions of the Beidou satellite, the system can accurately position the fault position in the power grid, the FTU device and the distributed traveling wave online measurement fault positioning device can monitor the state of the power grid in real time and respond rapidly when faults are detected, the data management and verification system based on the blockchain ensures the safety and consistency of the data, the risks of data falsification and forging are avoided, the user interface and the interaction module provide visual interfaces, users can conveniently inquire and manage the power grid data, the system can automatically identify and position the faults based on an artificial intelligent fault identification program, the intelligent level of the system is improved, the system provides accurate fault positioning information, the maintenance team is helped to respond rapidly and repair the faults, the accurate fault positioning and real-time response reduce unnecessary maintenance work, and therefore the maintenance cost is reduced, and the real-time fault detection and rapid fault response are beneficial to improving the stability and reliability of the power grid.
Second embodiment:
fig. 4-10 show.
The satellite receiving antenna is used for receiving signals of the Beidou satellite, the receiver is used for analyzing satellite signals, extracting positioning and time service information, and the data processing unit is used for processing received signal data.
The sensor is used for detecting current and voltage signals of a line, the high-speed data acquisition card is used for acquiring signals output by the sensor at a high speed, the data processing unit is used for processing acquired data in real time and realizing a fault positioning algorithm, and the fault positioning algorithm is used for identifying the fault type of a power grid based on an artificial intelligent fault identification program.
The fault detection module is used for monitoring key parameters such as current, voltage and the like in the power grid in real time and carrying out fault identification and classification;
the data acquisition module comprises a sensor, a high-speed data acquisition card and a data preprocessing function, and is used for carrying out high-precision and high-speed sampling on parameters such as current, voltage and the like in a power grid, and carrying out preprocessing operations such as filtering, amplifying or shrinking on acquired original data;
and the communication module is used for transmitting data in the FTU device, such as fault information, collected current and voltage data and the like, to the upper monitoring system or other equipment and receiving instructions of the upper monitoring system.
The fault identification program based on artificial intelligence comprises a feature extraction module, a deep learning model and a fault database, wherein the feature extraction module is used for extracting useful feature information from original data, the deep learning model is used for learning and identifying different types of faults, and the fault database is used for storing historical fault data.
And the data node stores power grid operation data and fault data, and the intelligent contract realizes automatic verification and transaction confirmation of the data, and the user interface is used for users to inquire the data and submit new data.
The data display interface displays real-time operation data and historical data of the power grid, the fault inquiry interface displays historical fault records and fault positioning results, and the system management interface provides system configuration and management functions.
The data processing unit comprises a signal processing algorithm, a traveling wave detection algorithm and a double-end positioning algorithm, wherein the signal processing algorithm, the traveling wave detection algorithm and the double-end positioning algorithm are used for accurately receiving and processing satellite signals in a complex environment, the traveling wave detection algorithm is used for accurately detecting traveling wave signals generated by faults, the double-end positioning algorithm is used for accurately calculating fault positions by utilizing data of two ends, the fault recognition program based on artificial intelligence comprises a feature engineering and a model selection technology, the feature parameter capable of accurately describing fault characteristics is used for determining, and a deep learning model suitable for fault recognition is selected or designed.
The blockchain-based data management and verification system comprises a data encryption and consensus mechanism technology for ensuring the safety of data in the transmission and storage processes and ensuring the data consistency among all data nodes, and the user interface and interaction module further comprises a data visualization and interaction module technology for displaying complex data to a user in an intuitive way and ensuring that the user can conveniently use the system functions.
The signal processing algorithm comprises a filtering algorithm, fourier transformation and wavelet transformation, the travelling wave detection algorithm comprises threshold detection and short-time Fourier transformation, the double-end positioning algorithm comprises a cross correlation method, a least square method and a neural network method, and the neural network method adopts forward propagation.
The satellite receiving antenna firstly receives signals of Beidou satellites, the receiver analyzes the satellite signals, positioning and time service information is extracted, the data processing unit processes the received signal data and comprises a signal processing algorithm (a filtering algorithm, fourier transformation and wavelet transformation), the sensor detects current and voltage signals of a line, the high-speed data acquisition card acquires signals output by the sensor at a high speed, the fault detection module monitors key parameters such as current and voltage in a power grid in real time and carries out fault identification and classification, the data acquisition module carries out high-precision and high-speed sampling on the parameters such as current and voltage in the power grid and carries out preprocessing on the acquired original data, the communication module transmits the data in the FTU device to an upper monitoring system or other equipment and receives instructions of the upper monitoring system, the fault identification program based on artificial intelligence comprises a feature extraction module, a deep learning model and a fault database, the feature extraction module extracts useful feature information from the original data, the deep learning model learns and identifies different types of faults, and the data node stores operation data and fault data of the power grid.
The system can accurately position the fault position in the power grid by combining a satellite positioning algorithm, a traveling wave detection algorithm and a double-end positioning algorithm, the fault detection module and the data acquisition module can monitor the state of the power grid in real time and respond rapidly when faults are detected, the data management and verification system based on the block chain ensures the safety and consistency of data, the risks of data falsification and falsification are avoided, the user interface and the interaction module provide visual interfaces, users can conveniently inquire and manage the power grid data, the system can automatically identify and position the faults based on an artificial intelligent fault identification program, the intelligent level of the system is improved, the system provides accurate fault positioning information, the maintenance team is helped to respond rapidly and repair the faults, the accurate fault positioning and real-time response reduce unnecessary maintenance work, thereby the maintenance cost is reduced, the real-time fault detection and rapid fault response are beneficial to improving the stability and reliability of the power grid, the data processing unit adopts an advanced signal processing algorithm, the accurate receiving and processing satellite signals are ensured under a complex environment, and the data visualization and interaction module technology enables complex data to be displayed to the users in a visual mode.
Third embodiment:
figures 1-10 show.
Comprises the steps of,
s1, starting and initializing, starting all modules and performing self-checking, enabling the Beidou satellite accurate time service and positioning module to start receiving satellite signals and performing preliminary positioning and time service, and simultaneously initializing an FTU device and starting to monitor parameters such as current and voltage of a power grid.
S2, data acquisition and processing are carried out, a sensor of the distributed traveling wave on-line measurement fault positioning device and the FTU device start to monitor current and voltage signals of a line, and acquired signal data are acquired at a high speed through a high-speed data acquisition card.
S3, time and position synchronization, namely, time synchronization is carried out on the distributed traveling wave online measurement fault positioning device and the FTU device by utilizing time and position information provided by the Beidou satellite accurate time service and positioning module, so that the accuracy of data is ensured.
S4, fault detection and positioning, wherein the data processing unit processes the acquired data in real time, if abnormality is detected, fault positioning is carried out by using a traveling wave detection algorithm and a double-end positioning algorithm, and the FTU device rapidly responds and provides fault information when detecting the fault.
S5, data storage and verification, fault information and positioning results are sent to a data management and verification system based on the blockchain, and the data are stored on data nodes of the blockchain and are automatically verified and confirmed through intelligent contracts.
S6, user interaction, wherein the user queries the real-time running state, the historical fault record and the fault positioning result of the power grid through a user interface and an interaction module, and the user interface acquires data from a block chain-based data management and verification system and displays the data to the user.
S7, fault response and repair, wherein once the fault is located, a relevant maintenance team can receive notification, and the maintenance team can check detailed information and geographic positions of the fault through a user interface, so that the fault is responded and repaired rapidly.
S8, system monitoring and management, wherein a system administrator can perform system configuration and management through a system management interface of a user interface, and the system configuration and management comprises calibration of a sensor, setting of data acquisition frequency, adjustment of a fault threshold value and the like.
S9, data backup and updating are carried out on a regular basis by a data management and verification system based on a block chain, so that the safety of data is ensured, the system also can regularly receive time and position updating from a Beidou satellite, and the accuracy of the system is ensured.
S10, closing and maintaining the system, safely closing the system when the system is required to be maintained or upgraded, restarting the system and performing self-checking after the maintenance is finished, and then recovering the normal operation.
The accurate time service and positioning module work flow of the Beidou satellite is as follows, signal receiving, the signal of the Beidou satellite is captured by a satellite receiving antenna, the satellite receiving antenna is installed at a proper position to maximize signal receiving quality, antenna parameters are adjusted to ensure stable receiving of the signal, the signal is analyzed, a receiver analyzes the satellite signal, positioning and time service information is extracted, the satellite signal is decoded by the receiver, original positioning and time service data are obtained, primary filtering and correction are carried out on the original data, data processing is carried out, a data processing unit processes the received signal data, accurate time and position information is provided, the data is further optimized and corrected by a signal processing algorithm, the processed data is converted into actual time and position information, a synchronization mechanism is adopted to ensure time synchronization among devices distributed at different positions, the time synchronization among the devices distributed at different positions is realized by the accurate time service information, the synchronization state is monitored, and stable operation of the system is ensured.
The FTU device work flow is as follows, initialization and self-checking, when the system is started or the FTU module is restarted, the FTU firstly carries out self-initialization, loads configuration parameters, carries out hardware self-checking, comprises state checking of key components such as current, voltage sensors, communication modules and the like, if any abnormality or fault is found, the FTU can generate warning or fault report and send the warning or fault report to an upper monitoring system through the communication modules, data acquisition is carried out, the FTU continuously acquires current and voltage data from a power grid line connected with the FTU, the data is sampled at a high speed and converted into digital signals so as to facilitate subsequent processing and analysis, a data processing unit inside the FTU carries out real-time analysis on the acquired data, detects whether abnormality or fault exists, and judges the state of the line by using preset threshold values and algorithms such as instantaneous overcurrent, overvoltage, undervoltage and the like, fault detection and response once the FTU detects a fault on the line, it immediately initiates a fault response procedure, depending on the type and severity of the fault, the FTU may perform various operations such as isolating the fault section, sending fault reports to the upper monitoring system or working in conjunction with other devices (e.g., circuit breakers) to isolate the fault, communication and data transmission, the FTU has a communication module that can communicate with the upper monitoring system, other FTUs or other power devices, periodically send real-time data, status reports and fault reports to the upper system, the FTU may also receive commands or configuration updates from the upper system, user interaction and configuration, the FTU is typically equipped with a local operator interface such as a touch screen or key, allowing a field operator to view status, fault records or make configuration, configuration of the FTU may be made remotely through the upper system, the fault recording and storage can also be carried out on site through a local operation interface, and a storage device is arranged in the FTU and used for recording fault events, operation logs and other important information, and the records can be used for subsequent fault analysis, system optimization or maintenance.
The distributed traveling wave online fault measuring and positioning device comprises the following working flows of signal detection, detection of current and voltage signals of a sensor detection circuit, installation of the sensor to monitor the current and voltage signals, protection of the sensor from external environment by utilizing protective measures, data acquisition, high-speed acquisition of signals output by the sensor by a high-speed data acquisition card, configuration of sampling rate and resolution of the high-speed data acquisition card, storage and transmission of acquired original data, traveling wave detection, realization of a traveling wave detection algorithm by a data processing unit, accurate detection of traveling wave signals generated by faults, analysis of data by the traveling wave detection algorithm, identification of traveling wave events, recording of relevant information of the traveling wave events, such as starting time and amplitude, fault positioning, realization of a double-end positioning algorithm, accurate calculation of fault positions by data at two ends, calculation of fault positions by the double-end positioning algorithm, and verification of accuracy of calculation results.
The fault recognition program based on artificial intelligence has the working flow of collecting data, collecting power grid operation data under normal and various fault states, collecting operation data under normal and fault states from the power grid, preprocessing and marking the collected data, extracting features, extracting useful feature information from original data by a feature extraction module, extracting key information from the data by a feature extraction method, storing and managing the extracted feature data, training a model, training a deep learning model by using the collected data, selecting or designing a proper deep learning model, training the model by using the marked data, and learning and identifying different types of faults by using the deep learning model.
The data management and verification system based on the block chain comprises the following working processes of data access, power grid operation data and fault data are accessed into the block chain system, the format and structure of the data are defined, uploading and access interface of the data are realized, data verification is realized, automatic verification and transaction confirmation of the data are realized through intelligent contracts, the integrity and accuracy of the data are automatically verified through the intelligent contracts, verification results of the data are recorded and managed, the data management is performed, the safety of the data in the transmission and storage processes is ensured, the data consistency among all data nodes is ensured, and the data is encrypted and stored in a distributed mode by using the block chain technology, so that the inquiring and searching functions of the data are realized.
The system comprises a user interface, an interaction module workflow, interface display, a data display interface, a fault query interface, a system management interface, a user interaction and an interaction module, wherein the data display interface displays real-time operation data and historical data of a power grid, the fault query interface displays historical fault records and fault positioning results, the system management interface provides system configuration and management functions, the user interaction ensures that the user can conveniently use the system functions, and friendly user experience is provided through the interaction module.
The scope of protection of the above-described embodiments employed in the present application is not limited to the above-described embodiments, and various changes made by those skilled in the art without departing from the spirit of the present application are still within the scope of protection of the present invention.
Claims (10)
1. The utility model provides a distributed travelling wave online measurement fault location system which characterized in that: the system comprises a Beidou satellite accurate time service and positioning module, an FTU device, a distributed traveling wave online measurement fault positioning device, a block chain-based data management and verification system, a user interface and an interaction module;
the Beidou satellite accurate time service and positioning module is connected with the distributed traveling wave online measurement fault positioning device and the FTU device through data communication, the FTU device is connected with the distributed traveling wave online measurement fault positioning device through data communication, the distributed traveling wave online measurement fault positioning device is connected with the blockchain-based data management and verification system through data communication and API or software interface, the blockchain-based data management and verification system is connected with the user interface and the interaction module through data communication and API or software interface, the user interface and interaction module are connected with the Beidou satellite accurate time service and positioning module and the FTU device through API or software interface, and the user interface and interaction module are connected with the distributed traveling wave online measurement fault positioning device through control signals and data communication;
the Beidou satellite accurate time service and positioning module is used for providing accurate time and position information and comprises a satellite receiving antenna, a receiver and a data processing unit;
the FTU device is used for monitoring parameters such as current, voltage and the like of a power grid in real time and rapidly responding when a fault is detected, and comprises a fault detection module, a data acquisition module and a communication module;
the distributed traveling wave online measurement fault positioning device is used for detecting the running state and the fault position of the power grid in real time and comprises a sensor, a high-speed data acquisition card, a data processing unit and a fault identification program based on artificial intelligence;
the block chain-based data management and verification system is used for guaranteeing the safety and consistency of data and comprises a data node, an intelligent contract and a user interface;
the user interface and the interaction module are used for displaying power grid data and providing interaction functions, and the user interface and the interaction module comprise a data display interface, a fault query interface and a system management interface.
2. The distributed traveling wave online measurement fault location system of claim 1, wherein: the satellite receiving antenna is used for receiving signals of the Beidou satellite, the receiver is used for analyzing satellite signals, extracting positioning and time service information, and the data processing unit is used for processing received signal data;
the sensor is used for detecting current and voltage signals of a line, the high-speed data acquisition card is used for acquiring signals output by the sensor at a high speed, the data processing unit is used for processing acquired data in real time and realizing a fault positioning algorithm, and the fault identification program based on artificial intelligence is used for identifying the fault type of a power grid.
3. The distributed traveling wave online measurement fault location system of claim 1, wherein: the fault detection module is used for monitoring key parameters such as current, voltage and the like in the power grid in real time and carrying out fault identification and classification;
the data acquisition module comprises a sensor, a high-speed data acquisition card and a data preprocessing function, and is used for carrying out high-precision and high-speed sampling on parameters such as current, voltage and the like in a power grid, and carrying out preprocessing operations such as filtering, amplifying or shrinking on acquired original data;
the communication module is used for transmitting data in the FTU device, such as fault information, collected current and voltage data and the like, to the upper monitoring system or other equipment and receiving instructions of the upper monitoring system.
4. The distributed traveling wave online measurement fault location system of claim 1, wherein: the fault identification program based on artificial intelligence comprises a feature extraction module, a deep learning model and a fault database, wherein the feature extraction module is used for extracting useful feature information from original data, the deep learning model is used for learning and identifying different types of faults, and the fault database is used for storing historical fault data;
the data node stores power grid operation data and fault data, the intelligent contract realizes automatic verification and transaction confirmation of the data, and the user interface is used for users to inquire the data and submit new data.
5. The distributed traveling wave online measurement fault location system of claim 1, wherein: the data display interface displays real-time operation data and historical data of the power grid, the fault inquiry interface displays historical fault records and fault positioning results, and the system management interface provides system configuration and management functions.
6. The distributed traveling wave online measurement fault location system of claim 1, wherein: the data processing unit comprises a signal processing algorithm, a traveling wave detection algorithm and a double-end positioning algorithm, wherein the signal processing algorithm, the traveling wave detection algorithm and the double-end positioning algorithm are used for accurately receiving and processing satellite signals in a complex environment, the traveling wave detection algorithm is used for accurately detecting traveling wave signals generated by faults, and the double-end positioning algorithm is used for accurately calculating fault positions by utilizing data of two ends.
7. The distributed traveling wave online measurement fault location system of claim 1, wherein: the artificial intelligence based fault recognition program comprises a feature engineering and model selection technology, wherein the feature engineering and model selection technology is used for determining feature parameters capable of accurately describing fault characteristics and selecting or designing a deep learning model suitable for fault recognition.
8. The distributed traveling wave online measurement fault location system of claim 1, wherein: the blockchain-based data management and verification system comprises a data encryption and consensus mechanism technology, which is used for ensuring the security of data in the transmission and storage processes and ensuring the data consistency among all data nodes.
9. The distributed traveling wave online measurement fault location system of claim 1, wherein: the user interface and the interaction module also comprise a data visualization and interaction module technology which is used for displaying complex data to a user in an intuitive way and ensuring that the user can conveniently use the system functions;
the signal processing algorithm comprises a filtering algorithm, fourier transformation and wavelet transformation, the travelling wave detection algorithm comprises threshold detection and short-time Fourier transformation, the double-end positioning algorithm comprises a cross correlation method, a least square method and a neural network method, and the neural network method adopts forward propagation.
10. A distributed traveling wave online measurement fault location system according to any one of claims 1-9, wherein: comprises the steps of,
s1, starting and initializing;
s2, data acquisition and processing;
s3, synchronizing time and position;
s4, fault detection and positioning;
s5, data storage and verification;
s6, user interaction;
s7, fault response and repair;
s8, monitoring and managing the system;
s9, backing up and updating data;
s10, closing and maintaining the system.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110187235A (en) * | 2019-06-10 | 2019-08-30 | 成都中工科技有限公司 | Distributed power line fault positioning system and method based on traveling wave speed dynamic measurement |
| CN110907748A (en) * | 2019-10-21 | 2020-03-24 | 贵州电网有限责任公司 | Distribution lines travelling wave fault acquisition and analysis device and fault positioning system |
| CN111257700A (en) * | 2020-03-31 | 2020-06-09 | 国网江苏省电力有限公司无锡供电分公司 | Power distribution network single-phase earth fault positioning device and method based on edge calculation |
| CN111913077A (en) * | 2020-08-19 | 2020-11-10 | 剑科云智(深圳)科技有限公司 | Intelligent fault positioning system of power distribution network |
| CN116908610A (en) * | 2023-07-11 | 2023-10-20 | 国网浙江省电力有限公司湖州供电公司 | Line fault positioning method based on Beidou short message |
| CN117150414A (en) * | 2023-10-17 | 2023-12-01 | 广东迅扬科技股份有限公司 | Fault diagnosis method |
-
2024
- 2024-01-05 CN CN202410017568.8A patent/CN117517877A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110187235A (en) * | 2019-06-10 | 2019-08-30 | 成都中工科技有限公司 | Distributed power line fault positioning system and method based on traveling wave speed dynamic measurement |
| CN110907748A (en) * | 2019-10-21 | 2020-03-24 | 贵州电网有限责任公司 | Distribution lines travelling wave fault acquisition and analysis device and fault positioning system |
| CN111257700A (en) * | 2020-03-31 | 2020-06-09 | 国网江苏省电力有限公司无锡供电分公司 | Power distribution network single-phase earth fault positioning device and method based on edge calculation |
| CN111913077A (en) * | 2020-08-19 | 2020-11-10 | 剑科云智(深圳)科技有限公司 | Intelligent fault positioning system of power distribution network |
| CN116908610A (en) * | 2023-07-11 | 2023-10-20 | 国网浙江省电力有限公司湖州供电公司 | Line fault positioning method based on Beidou short message |
| CN117150414A (en) * | 2023-10-17 | 2023-12-01 | 广东迅扬科技股份有限公司 | Fault diagnosis method |
Non-Patent Citations (1)
| Title |
|---|
| 程骏: "基于北斗卫星的故障行波定位系统的设计研究", 《中国优秀硕士学位论文全文数据库（电子期刊）》, no. 3, 15 March 2016 (2016-03-15), pages 1 * |
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