214results about How to "Reduce outage time" patented technology

The invention relates to a real-time fault detection and automatic repair system for a power grid. The real-time fault detection and automatic repair system comprises a multi-level sensing module, a data processing module, an automatic repair module and a monitoring and logging module. The multi-level sensing module collects data such as voltage, current, frequency and temperature in operation of a power grid by deploying multiple types of sensors, and sends the data to the data processing module. And the data processing module analyzes the collected data through an embedded intelligent algorithm, identifies potential faults and generates fault diagnosis results. And the automatic repair module executes repair operations of isolating a fault area, reconstructing a power grid topological structure and recovering normal power supply according to a fault diagnosis result. The monitoring and log module records the operation state of the power grid and the fault diagnosis and repair process, and provides fault analysis and performance evaluation functions through a user interface. According to the system, real-time detection, accurate positioning and automatic repair of power grid faults and comprehensive monitoring of operation data are realized, and the safety and reliability of power grid operation are remarkably improved.

The invention discloses a low-voltage power distribution area topology identification method and system based on clustering analysis and a graph theory, and relates to the technical field of low-voltage power distribution area topology classification. The system can accurately identify the topological structure of each partition through the combination of a clustering analysis model and a graph theory algorithm, and automatically calculate a topological characteristic coefficient Tp; therefore, the complex topological structure of the power distribution area can be classified and analyzed more carefully and comprehensively. According to a traditional method, accurate classification is often difficult when a complex branch structure is faced, and a topology recognition module ensures the accuracy of a classification result through a calculation mode of a graph theory. Through the feedback management module, when the power performance risk coefficient Lpjx of the partition exceeds a safety threshold R, a fault early warning signal can be sent out in time, abnormal nodes are automatically identified, faults are isolated, meanwhile, load transfer is executed, the power demand is rapidly transferred to the normally operating partition, and the power failure range and time are reduced.

The invention discloses a real-model experiment distribution line fault positioning method and system. The method comprises the following steps: acquiring a topological structure diagram of a target power distribution network in a real-model experiment; based on the topological structure diagram of the target power distribution network, combining a preset diagram input feature selection logic, and obtaining target power distribution network node and edge features as input of a power distribution network fault model to be established; according to the input of the to-be-established power distribution network fault model and the output of a preset power distribution network fault model, training the power distribution network fault model based on the improved graph neural network, the output of the preset power distribution network fault model being the probability of the line fault in the power distribution network; and according to the trained power distribution network fault model based on the improved graph neural network, real-type experiment power distribution line fault positioning is completed. The system and the method have good expansibility and adaptability, can be suitable for power distribution networks of different scales and structures, and have wide application prospects.

The invention relates to the technical field of electric power system safety early warning, and discloses a fault risk sensing early warning method for a high-low voltage switchgear assembly, and the method carries out the data preprocessing and feature extraction through collecting the state monitoring data, environmental parameters and basic attribute information of a device in historical operation. And based on the feature data sets, constructing a fault risk prediction model to predict the fault risk probability of the equipment in a period of time in the future, obtaining the operation state data and environmental parameters of the equipment in real time, and inputting the prediction model to obtain the fault risk probability. Meanwhile, the equipment is monitored in real time, original monitoring data is cleaned, abnormal values are removed, real-time monitoring data is compared with prediction data, whether the difference exceeds a threshold value or not is judged according to a preset risk threshold value, and risk points are marked. And evaluating the equipment fault risk according to the risk point and the evaluation strategy, and sending a result to related personnel to take prevention measures.

The invention discloses a source-grid-load-storage integrated micro-grid intelligent scheduling system, and relates to the technical field of micro-grid management, the system comprises a comprehensive scheduling platform, the comprehensive scheduling platform is in communication connection with an energy data acquisition module, an energy prediction module, an intelligent scheduling module, an energy storage management module and a fault early warning module, and the modules are in electric signal connection. By integrating the sensor network and the data acquisition and processing technology, the running states of various energy devices and energy storage devices in the micro-grid are monitored in real time, the reliability and stability of the system are remarkably improved, potential device faults can be found and early warned in time, fault enlargement is avoided, and the reliability and stability of the system are improved. The power failure time and economic loss caused by faults are reduced, the charging and discharging strategy of the energy storage equipment can be flexibly adjusted according to the real-time load requirement and the renewable energy power generation condition, it is ensured that the microgrid can keep stable electric energy supply under various working conditions, and the power utilization requirement of a user is met.

The invention relates to the technical field of power maintenance, and discloses a power distribution network-oriented single-phase earth fault AI comprehensive research and judgment system, which integrates a power distribution network monitoring module, a fault diagnosis equipment module and an AI comprehensive research and judgment module. The system can accurately judge the type, position and severity of the single-phase earth fault by monitoring and collecting all-dimensional data of the power distribution network in real time and combining intelligent analysis of the AI comprehensive research and judgment module, and the accuracy of fault positioning and isolation is remarkably improved. The AI comprehensive research and judgment module adopts a Markov decision process for modeling, and a deep reinforcement learning algorithm is used for training a research and judgment model, so that rapid fault positioning, isolation and power supply recovery are realized, the fault processing efficiency and the power supply recovery speed are effectively improved, and the power failure time and the influence on users are reduced.

The invention relates to the technical field of power failure troubleshooting, and discloses a single-phase earth fault rapid positioning method based on multi-source data fusion, and the method comprises the steps: collecting historical fault data, power system operation data and environment data through employing a plurality of monitoring devices, such as a power system monitoring device, a fault recorder and a distributed sensor; and forming a basic data set. By performing fault feature analysis on the data set, a dual machine learning model is constructed, including a fault prediction model and a positioning model. A training data set is used to train a model, model parameters are optimized, then the trained model is used to predict real-time data, potential fault risks are identified, and a targeted troubleshooting plan and a rapid positioning strategy are formulated. According to the invention, through data fusion and a machine learning algorithm, the accuracy of fault positioning is improved, the positioning time is shortened, and the power failure time and the influence on users are reduced.

The invention provides an intelligent power grid safety early warning system and a monitoring method in the technical field of intelligent power grids, which are used for solving the problem of safety early warning and monitoring function defects of the existing imperfect intelligent power grids, and comprise an information acquisition unit, a data management unit, an abnormity analysis unit and a safety early warning unit, the method comprises the steps of collecting power grid real-time data and line equipment data; constructing an adjacent matrix and a target matrix, calculating and analyzing to obtain a node weight and a target correlation degree, and analyzing by using a discrete model to obtain a dispersion index; a data evaluation value is obtained, and a data abnormal value is obtained through analysis; and generating intelligent power grid safety early warning information and a disaster recovery strategy according to the data abnormal value and the line equipment data. By constructing an intelligent power grid monitoring and early warning system, power grid equipment with potential safety problems is predicted in real time, the operation and maintenance efficiency is improved, the method can be suitable for power grid systems of different scales, the influence of faults on power grid operation is reduced, and large-area power failure events are effectively prevented.

The invention discloses a power distribution network fault management system and method with a rapid positioning function, and relates to the technical field of power distribution network management, and the system comprises a data collection module, a data analysis and processing module, a fault positioning module and a display and decision module. According to the power distribution network fault management system and method capable of achieving rapid positioning, the power distribution network fault management system is arranged, positioning errors caused by inaccurate data are reduced by means of high precision of a sensor and data preprocessing measures, multiple times of fault positioning are completed, the fault generation area is determined preferentially, and the fault management efficiency is improved. And then the node is combined to realize the specific judgment of the fault generation position, so that the exact positioning operation of the fault can be quickly completed, the interference of external factors is eliminated, the positioning accuracy is effectively improved, and meanwhile, the omnibearing management of each region of the power distribution network is facilitated.

The invention discloses an automatic feeder fault processing method based on a 5G network, and the method improves the fault processing capability of a power distribution network through the high speed, low delay and high safety of the 5G communication network, can quickly position a fault region through the information exchange between power distribution terminals in combination with the fault signals of the power distribution terminals and adjacent terminals, and improves the fault processing efficiency. Therefore, quick isolation of a fault section is achieved, when a fault occurs, the power failure range is controlled within the minimum range, the power failure time is shortened, fault positioning and control decision making are completely and autonomously completed by the power distribution terminal, the whole processing process does not depend on a power distribution main station, and the main station only needs to receive a fault processing result afterwards; according to the method, the network topology structure can be automatically updated when part of power distribution terminals have communication faults, the operation states of all nodes and circuit breakers in a power distribution line can be monitored in real time, remote measurement can be conducted on voltage, current, power factors and the like, and operation parameter curves of all the nodes can be displayed in real time.

The invention discloses an unmanned aerial vehicle carrying type ice stripping robot device for a distribution line. The unmanned aerial vehicle carrying type ice stripping robot device comprises an unmanned aerial vehicle system, a clamping guide mechanism, a docking mechanism, a camera mechanism and a wheel type ice stripping mechanism, the clamping guide mechanism comprises a top cover, a V-shaped wheel and a clamping wheel assembly, and the distribution line is clamped below the V-shaped wheel and is clamped by the clamping wheel assembly to advance; the unmanned aerial vehicle system is mounted above the top cover through the docking mechanism; the camera mechanisms are mounted on the front and rear sides of the top cover; the wheel type ice stripping mechanism comprises a connecting top plate, a planetary gear, a main gear and a cutter, the front end of the connecting top plate is installed on the top cover, the planetary gear is installed at the tail end of the connecting top plate, the main gear is arranged on the outer side of the tail end of the connecting top plate and meshed with the planetary gear, and the cutter is fixed to the main gear. The power distribution cable deicing device is compact in structure, high in automation degree, high in stability, simple and convenient in deicing operation, high in efficiency, safe and reliable, and power distribution cable deicing operation can be realized without power failure.

The invention discloses a power distribution network fault self-healing device and a self-healing method. The device comprises node equipment and an operation management platform, the operation management platform is used for analyzing operation parameters of the node equipment, positioning a fault area and sending a control instruction for power-off isolation and power supply recovery; the node equipment comprises power supply equipment, sensing equipment, a node control switch and electric energy quality treatment equipment; the sensing equipment is used for monitoring and collecting operation parameters of the node equipment; the node control switch is disconnected and isolates a fault area when detecting that an operation parameter exceeds a threshold value or the integrated fault detection model identifies an abnormal mode or receives a control instruction of the operation management platform, and is connected and recovers power supply of a non-fault area when receiving a power supply recovery control instruction of the operation management platform so as to realize fault self-recovery; the electric energy quality control equipment is used for reducing voltage fluctuation in the process of recovering power supply of a non-fault area and avoiding misoperation of a node control switch. The device is simple in structure and self-healing process, and quick response to faults is realized.

The invention discloses a distribution network self-healing management method and system, and relates to the technical field of self-healing control of a distribution network, and the method comprises the steps: generating a fault log; automatically generating a fault log line attribute based on the line attribute managed by the line ledger; an operator initiates a self-healing action analysis application; auditing the self-healing action analysis list; automatically calculating a summary index based on the self-healing action analysis information; and generating a self-healing application evaluation criterion based on the self-healing action analysis summary index and the self-healing action analysis information. According to the method, by automatically generating the fault log and matching the line attributes, manual input errors are reduced, the response speed of fault processing is improved, the self-healing line investment, change and back operation application process is standardized, the operation normalization and accuracy are ensured, the management complexity and operation errors are reduced, and the management efficiency is improved. The automatic recording and analysis of the self-healing action are realized, the time required by manual analysis is reduced, and the fault processing efficiency is improved.

The invention relates to the technical field of power distribution systems, in particular to a power distribution system operation fault monitoring and predicting system which comprises a data acquisition module used for acquiring operation data of a power distribution system in real time; the data processing module is used for preprocessing, storing and transmitting the data acquired by the data acquisition module; the fault detection and prediction module is used for monitoring the operation state of the power distribution system in real time, detecting abnormal conditions and predicting potential faults; the user interface is used for man-machine interaction and displaying real-time data, historical data, alarm information and maintenance suggestions; the maintenance management module is used for making a management maintenance plan, recording maintenance information and evaluating a maintenance effect; early detection and prediction of faults are realized, and reliability and operation efficiency of a power distribution system are improved.

The invention discloses an emergency processing assessment method and system based on power grid disaster damage, and relates to the technical field of resource allocation. A power grid information set, an environment information set and an emergency resource information set are collected in advance, and a partition risk assessment model is constructed and trained based on the power grid information set and the environment information set; the method comprises the steps of collecting real-time power grid load data of a power grid, calculating estimated resource demand proportion distribution of the power grid in combination with a partition risk assessment model and the power grid load data, constructing a comprehensive loss index based on the estimated resource demand proportion distribution and the power grid load data, and constructing a resource allocation optimization model based on the comprehensive loss index and an emergency resource information set. Solving the resource allocation optimization model by using an optimization model solving tool to obtain an emergency resource allocation scheme; and the power-off time and economic loss of the power grid are greatly reduced.

The embodiment of the invention discloses a medium-voltage line fault positioning method, device and system. The medium-voltage line fault positioning method comprises the following steps: acquiring a node state of a line monitoring node sent by each node monitoring device; wherein the node monitoring device is arranged in a distribution network line, and the node monitoring device is used for acquiring voltage and current of a line monitoring node, and determining impedance magnitude and impedance angle of the line monitoring node according to the voltage and current of the line monitoring node; determining the node state of the line monitoring node according to the impedance size and the impedance angle of the line monitoring node; and marking the node state of each line monitoring node in the wiring topological graph, and determining a line fault section according to a marking result. The method has the advantages of being accurate in fault positioning, small in calculation amount and capable of adapting to various forms of complex power grids.

The invention provides a fault positioning method and device for a box-type substation, and the method comprises the steps: obtaining a topological structure of the box-type substation, and recognizing all switch nodes and terminal equipment nodes; according to the current flow direction and the electric energy transmission path, establishing a directed graph model of the box-type substation; a sensor array is deployed on the switch node and the terminal equipment, electrical parameters of a deployment area are monitored in real time, fault detection and signal analysis are carried out according to a set threshold value, and a fault signal is determined; according to the current flow direction in the topological structure and a fault signal in the sensor data, analyzing the current flow direction at the fault moment, determining a monitoring area where the fault signal is located, and preliminarily positioning a fault area; and according to the change rate of the voltage and the current of the preliminarily positioned fault area, the distance from the fault point to the nearest sensor is calculated by combining cable parameters and transmission delay, the fault position is accurately positioned, and rapid and accurate positioning of the fault is realized.

The invention discloses an electric power line fault detection and positioning method applying an unmanned aerial vehicle, and the method comprises the following steps: collecting an overall distribution diagram of an electric power line, and planning an unmanned aerial vehicle inspection route according to the overall distribution diagram of the electric power line; acquiring an electric power line image through the unmanned aerial vehicle according to the unmanned aerial vehicle inspection route, and analyzing the electric power line image to obtain a fault detection result; and carrying out fault point positioning based on the fault detection result and the power line image to obtain a power line fault position. According to the invention, the efficiency and accuracy of fault detection can be greatly improved, the power failure time is reduced, and the stability of power supply is guaranteed.

The invention discloses an auxiliary decision-making system and method for load transfer of a power distribution network, and aims to improve the operation efficiency and reliability of the power distribution network. The method comprises the following steps: S10, acquiring node voltage and branch current data in a power distribution network in real time, and calculating a voltage fluctuation index to evaluate the operation state of the power distribution network. And S20, identifying an overload line by using a direct-current power flow calculation method, obtaining a load unbalance factor through calculation, and identifying a key area in which load transfer needs to be carried out. And S30, comprehensively evaluating the transfer capacity of each feeder line through a weighted average method in combination with the voltage fluctuation index and the load imbalance factor, and calculating the transfer capacity coefficient of each feeder line as a basis for optimizing load distribution. And S40, adjusting the switching state by adopting an intelligent optimization algorithm to realize optimal load transfer path planning, and maximizing the transfer capacity coefficient, thereby improving the power supply reliability and economy. The operation efficiency and the power supply quality of the power distribution network can be effectively improved.

The invention discloses a parallel power supply path searching method and system based on a graph database, and the method comprises the steps: building a power grid power supply association graph model based on structural model connection files and equipment coordinate information of all transformer substations, power transmission lines, feeder lines, loads and distributed power supplies in a region; updating the power grid power supply association graph model according to the latest minute-level section data based on the power grid power supply association graph model; calculating an optimized power supply path by using mixed integer linear programming based on the updated power grid power supply association graph model; based on the optimized power supply path, if a power grid fault is detected, using a Dijkstra algorithm to quickly find an alternative path bypassing a fault area; based on the alternative path bypassing the fault area, deep analysis is carried out through a station power supply source searching algorithm, and a power supply path is refined; a graph parallel computing technology is utilized to distribute computing tasks to a plurality of nodes for parallel execution, and a path search result is obtained; and determining a power supply path from the source side to the target station according to the path search result and the power supply state, marking the power supply path on the geographic coordinates by using a graph database visualization component, and simultaneously performing minute-level dynamic updating to obtain visual and complete path information. Under the conditions that a large number of distributed power supplies are accessed and the topological structure of the power grid is complex and changeable, rapid and accurate power supply path information can be provided, and valuable support is provided for regulation and control and optimization decision making of a power system.

The invention discloses a distribution line single-phase earth fault section prediction method and system based on transient signals. And carrying out multi-scale analysis on the transient current signal or the transient voltage signal by using wavelet transform, extracting a wavelet coefficient reflecting fault features and energy thereof as feature values, inputting the feature values into a pre-trained neural network model, carrying out distributed training, and predicting to obtain a fault section. According to the method, the fault positioning accuracy is remarkably improved, false alarm and missing alarm are reduced, the fault positioning time is greatly shortened, the fault response speed of the power system is improved, and the power failure time and economic loss are reduced.

The invention discloses a power grid operation state monitoring system based on multi-dimensional information, and the system comprises a data collection module which is used for collecting power grid operation data in real time, and the data comprise electrical parameters, load parameters and power grid equipment geographic position parameters; the data processing module is used for preprocessing the power grid operation data; the state analysis module is used for calculating the number of adjacent nodes related to a fault node and an electrical parameter deviation value according to the decision tree, a preset power grid physical simulation model, historical power grid operation data and processed power grid operation data, and identifying the fault node related to the adjacent nodes; the state display module is used for displaying power grid operation data and fault nodes, the fault nodes relate to adjacent nodes, and the fault nodes relate to the number of the adjacent nodes and the electrical parameter deviation value. According to the invention, through the provided information of the fault node and the influence range thereof, power grid dispatching personnel can be assisted to carry out optimized dispatching, resources are reasonably distributed, and the overall operation efficiency is improved.

The invention discloses an on-line withstand voltage test device for transformer oil, relates to the technical field of electrical test instruments, and is used for testing the dielectric constant of the transformer oil. The device can be directly installed between the oil pumping pipe and the oil filling pipe of the transformer oil arc extinguishing on-load tap-changer without being carried back and forth, the automatic oil pumping device is designed, oil is directly pumped out of the transformer without being in contact with the outside, obtained detection data are accurate, and insulating oil is not wasted. The device consists of a transformer oil withstand voltage tester and an automatic oil pumping device, wherein a test unit is arranged in the automatic oil pumping device. The automatic oil pumping device is directly communicated with an oil pumping pipe and an oil injection pipe of the transformer oil arc extinguishing on-load tap-changer, so that totally-closed sampling and reinjection processes are realized. Exposure of an oil sample is avoided, the purity of an oil product is kept in the whole process, and then the accuracy of data is improved.

The invention discloses a power grid fault identification system based on big data. The system comprises a data acquisition module used for acquiring real-time operation data in power grid operation; the data storage module stores real-time operation data; the data processing module preprocesses the real-time operation data; the fault identification module is used for inputting the real-time operation data into a fault identification model and identifying a fault type; the fault analysis module compares the voltage phasor difference and the current phasor difference of different PMU nodes, calculates the fault position and evaluates the fault involved range when the fault occurs; the fault processing scheme generation module is used for generating a fault processing scheme; the alarm and processing module is used for sending fault information to operation and maintenance personnel; and the visualization module is used for displaying the fault type, the fault factor and the fault related range when the fault occurs, and providing an interactive operation interface for operation and maintenance personnel. The fault processing speed is increased by analyzing the fault information, the possibility of human errors is reduced, and the processing efficiency is improved.

The invention relates to the technical field of power transmission line detection, in particular to a power transmission line hardware fitting damage intelligent detection method based on an unmanned aerial vehicle. Comprising the steps that a main unmanned aerial vehicle takes off, an auxiliary unmanned aerial vehicle is assisted to take off, a to-be-detected hardware fitting is accurately determined through cooperation of the main unmanned aerial vehicle and the auxiliary unmanned aerial vehicle, and the main unmanned aerial vehicle and the auxiliary unmanned aerial vehicle conduct X-ray picture collection and detection on the hardware fitting; the unmanned aerial vehicle airborne detection platform is constructed, double unmanned aerial vehicles work cooperatively, clear X-ray images can be obtained quickly, the detection efficiency is far higher than that of traditional manual detection, and the power failure time is greatly shortened; according to the improved network structure, SPPF-DLKA and C2fG-Ghost modules and a CA attention mechanism are applied, the feature adaptation and extraction capability is enhanced, strong light interference is inhibited, and the damage type, degree and position of the hardware fitting are accurately judged; potential problems can be found in time, line faults are avoided, maintenance cost is reduced, and safety and reliability of power transmission lines are improved.

The invention relates to a magnetic control fast switch and dynamic voltage restorer combined power supply switching system and method. The system comprises a magnetic control switch unit, a voltage monitoring unit, a voltage compensation unit and an arc extinguishing unit. The magnetic switch unit is made of a novel magnetic control material and forms a vertical motion opening and closing mechanism through excitation and demagnetization of a built-in coil and assistance of a spring, and the vertical motion opening and closing mechanism is used for changing an internal magnetic domain and rapidly opening and closing. The voltage detection unit adopts a double-second-order generalized integral phase-locked loop voltage monitoring structure and is used for detecting instantaneous phase and frequency information of power grid voltage; the voltage compensation unit adopts a dynamic voltage restorer and is used for performing voltage compensation according to a difference value between a current power supply and an objective table power supply in a power supply switching gap so as to effectively maintain the stability of load voltage when voltage sag occurs in a power grid; and the arc extinguishing unit adopts a T-shaped double-outlet vacuum arc extinguishing chamber and is used for realizing zero arc in the whole power supply switching process. According to the invention, rapid switching of the power supply can be realized, and continuous voltage is ensured in the switching process.

The invention discloses an intelligent opening and closing method and system for a reclosing circuit breaker based on an electromagnet, and relates to the field of intelligent control, and the method comprises the steps: monitoring a line current in real time, comparing the line current with a preset threshold value, and carrying out the opening after the overcurrent abnormality is detected. Entering a first time delay stage after opening, comprehensively evaluating the states of the circuit breaker and the circuit, and constructing a dynamic weight index system to calculate an evaluation score; if the score exceeds a threshold value, closing is carried out after time delay is finished, otherwise, an alarm is triggered. And entering a second delay stage after switching on, continuously monitoring the electric parameters and establishing an anomaly judgment mechanism, forming a closed-loop protection process of monitoring, switching off, evaluating, switching on and re-monitoring, and realizing intelligent linkage of overcurrent protection and state self-adaption. The method has the advantages that through real-time line electric parameter monitoring, multi-dimensional state evaluation and an intelligent decision-making mechanism, precise opening and closing of the circuit breaker are achieved, the power supply reliability is improved, the power failure time is shortened, and the misoperation risk is reduced.

The invention discloses an intelligent power distribution network fault positioning system and method, and the system comprises a sensing module which monitors the current, voltage, load and temperature of a power grid in real time through the deployment of a line sensor, an intelligent electric meter and distributed feeder automation equipment; the communication module is used for constructing a high-speed communication network covering the whole power distribution network, so that fault information can be quickly transmitted to a control center from terminal equipment; the data analysis module is used for processing and analyzing the collected mass data through big data analysis, machine learning and an artificial intelligence algorithm, identifying fault features and establishing a fault diagnosis model; the fault isolation and positioning module is used for accurately positioning a fault point based on the change of the electrical signal when the fault occurs; and the geographic information system integration module combines the fault positioning information with a geographic information system and visually displays the fault position in the form of a map. According to the invention, the fault processing efficiency is obviously improved, the power failure time and range are reduced, and the toughness of the power grid is enhanced.

The invention discloses an active power distribution network secondary system planning method, and relates to the technical field of power system planning, and the planning method comprises the following steps: regional characteristic deep analysis, differential fault processing configuration scheme making, medium and low voltage terminal function extension and optimization path exploration, and differential power distribution terminal partition deployment strategy. And formulating a primary and secondary system overall planning technical principle, and scientifically formulating a power distribution network secondary system planning design technical principle oriented to the differentiated primary network frame. According to the invention, through careful analysis of the influence of new energy access, a targeted protection logic and a cooperative control strategy are designed, a fault area can be accurately identified and rapidly isolated under loads of different positions and types, the power failure time of users in a non-fault area is reduced, and through implementation of a differentiated partition deployment strategy, the power failure rate of the users in the non-fault area is improved. And each power supply area can obtain power distribution terminal configuration most suitable for self requirements, so that the fault processing capability is further enhanced.

The invention discloses a substation double-bus switch cabinet replacement method and device and a medium. Relates to the technical field of substation power supply, upgrade and reconstruction are implemented in an original switch cabinet position area, single-power-supply operation is avoided, the power failure time is reduced to the maximum extent by gradually transferring loads and stopping a transformer, and continuity and reliability of power supply are guaranteed. Through temporary connection of the contact power cable, dual-power supply of a user is kept, long-time single-bus power supply is avoided, the influence of power supply interruption is minimized, and stable operation of the system is kept. Investment cost can be effectively reduced, many difficult problems of difficult examination and approval, large construction difficulty, high single-power-supply operation safety risk and the like of the renovation land are solved, and operation safety of operation equipment in the renovation period is ensured.