886results about "Emergency protection data processing means" patented technology

The invention belongs to the field of power systems, and discloses a power distribution network fault autonomous diagnosis and self-healing control method and system based on deep reinforcement learning, and the method comprises the steps: carrying out the collection and preprocessing of the multi-source heterogeneous data of a power distribution network; key feature vectors are extracted from the multi-source heterogeneous data based on a graph convolutional network, and a state representation model is constructed; based on an asynchronous dominant actor-commentator algorithm, constructing a fault diagnosis agent capable of quickly diagnosing faults; a meta-reinforcement learning algorithm is adopted, a dynamic reconstruction strategy library is generated through pre-training, and a self-healing control agent capable of rapidly adapting to various different fault scenes to generate an optimal reconstruction strategy is constructed; constructing a self-healing control module based on virtual impedance matching, wherein the self-healing control module is used for intelligent reconstruction and self-healing control of the power distribution network; a risk-sensitive reward function and a game equilibrium strategy optimization method are introduced to improve performance and robustness; and finally carrying out system deployment and engineering verification.

The invention relates to the technical field of power system automation, in particular to a real-time monitoring and fault positioning system for a vehicle-mounted mobile substation. The system comprises a signal acquisition and processing unit which monitors and acquires line parameters and environmental parameters of a transformer substation and traveling wave signals generated when a fault occurs in real time; the fault type identification unit calculates the confidence coefficient of each fault type based on the traveling wave signal so as to judge the fault type generated by the traveling wave signal, and marks the arrival time of the traveling wave head; an algorithm fusion positioning unit preliminarily positions a fault point according to the fault type and the arrival time of a traveling wave head, and then constructs a fitness function through a particle swarm optimization algorithm in combination with line topology and environmental parameters to correct a preliminary positioning error; according to the system, high-precision fault positioning and rapid isolation recovery are realized, the accuracy of fault section division in the complex power distribution network is ensured by modeling switch state and branch change, and misjudgment caused by topological change or equipment overload is effectively avoided.

The invention relates to the technical field of power distribution protection cabinet fault diagnosis, and discloses an intelligent fault diagnosis and rapid isolation method for a power distribution protection cabinet, and the method comprises the steps: synchronously collecting electrical parameters, environment states and equipment motion signals in the cabinet as multi-source monitoring data when the power distribution protection cabinet operates; parameter fluctuation, state change and action time sequence features are extracted after preprocessing, cross-data association analysis is carried out through a multi-dimensional association model to generate an association feature set, a fault diagnosis information set is formed based on the identified abnormal types, fault positions and development trends, an isolation strategy is formulated according to severity levels and influence ranges, and a fault diagnosis result is obtained. And generating a rapid isolation instruction and dynamically adjusting along with fault evolution. According to the method, multi-source data fusion analysis is realized, faults can be accurately diagnosed and rapidly isolated, the operation safety and reliability of the power distribution protection cabinet are improved, and the method is suitable for fault processing of the power distribution protection cabinet in a power system.

The invention discloses an intelligent reclosing circuit breaker modular protection system, which relates to the technical field of circuit breaker intelligent management, and comprises an acquisition module, a judgment module, a reclosing control module and an optimization module. Voltage holes caused by fault tripping and non-fault disturbance are effectively distinguished, and false triggering of reclosing operation is avoided; meanwhile, the optimization module introduces a machine learning algorithm to carry out continuous filing and strategy updating on misjudgment events, and self-adaptive discrimination logic optimization is realized, so that reclosing judgment accuracy and power supply stability of the power grid system under a complex load condition are remarkably improved, and system impact and equipment damage are effectively prevented.

The invention belongs to the technical field of fault analysis and monitoring, and particularly relates to an intelligent monitoring and fault isolation method and system for a branch box, and the method comprises the steps: carrying out the multi-physical field data fusion collection of the branch box, and obtaining a spatial-temporal feature matrix; performing dynamic feature extraction on the multi-physical field data of the branch box, and outputting a fused dynamic feature vector of the branch box; obtaining a branch box topological graph structure, and obtaining a branch box node fault probability matrix; building a physically constrained fault propagation model based on the branch box node fault probability matrix, obtaining a pre-isolation set, and outputting a dynamic blocking instruction; taking the pre-isolation set as an initial solution space constraint, outputting a fault type and obtaining an isolation instruction; and setting a branch box topology reconstruction constraint, and performing closed-loop control on each branch box node in combination with the isolation instruction to obtain a switching action sequence of each branch box node and a reconstructed power supply path. Precise monitoring, rapid isolation and intelligent reconstruction of the fault of the branch box can be realized, and the operation and maintenance efficiency of the power distribution network is remarkably improved.

The invention discloses a servo motor dynamic overload detection and protection method based on a heat accumulation model, which relates to the technical field of servo system fault protection application, and comprises the steps of constructing a heat accumulation equivalent model, dynamically detecting an overload state, executing a heat dissipation recovery strategy, implementing a multi-stage protection mechanism, self-adaptive environment compensation and a historical data learning function. Through discretization processing of overload curve data and a nonlinear acceleration calculation strategy, the problems of protection lag and false triggering caused by traditional single-parameter detection are avoided, it is ensured that the motor can respond in time in light load, heavy load and load fluctuation scenes, the burn-out risk of the motor is reduced, and through integration of an environment temperature sensor and a heat dissipation condition evaluation unit, the reliability of the motor is improved. The heat accumulation coefficient and the heat dissipation attenuation parameter are dynamically adjusted, the problem of model deviation caused by environment interference is solved, when heat dissipation deterioration and temperature feedback abnormity are detected, the heat dissipation recovery period is automatically prolonged, calculation logic is corrected, and the continuous operation reliability of the system is improved.

The invention relates to the technical field of power grid self-healing control, and discloses a power grid self-healing control intelligent optimization method and system, and the method comprises the steps: obtaining the topological structure information of a power grid, dividing n power grid toughness evaluation regions according to the topological structure information of the power grid, calculating a hierarchical toughness evaluation index, and forming a comprehensive toughness evaluation index according to the hierarchical toughness evaluation index; a self-healing control intelligent optimization model is constructed based on the comprehensive toughness evaluation indexes, a self-healing control optimal solution is obtained by solving the self-healing control intelligent optimization model, the self-healing control optimal solution is dynamically calibrated, and a self-healing control strategy is generated; according to the method, the topological structure, the historical fault data and the real-time operation state of the power grid are comprehensively considered, a layered evaluation and dynamic calibration combined mode is adopted, the intelligent level and adaptability of self-healing control of the intelligent micro-grid are improved, the toughness and recovery capacity of the micro-grid for coping with complex faults are enhanced, and safe, reliable and efficient operation of the power grid is guaranteed.

The invention relates to the technical field of protection device testing, in particular to a verification method of an intelligent comprehensive protection device, which comprises the following steps of: extracting starting time and response time in a tripping state transition sequence of the protection device, calculating execution delay and action segment length, and comparing and identifying an abnormal link based on a state number sequence; the method comprises the following steps: realizing analysis and standard reconstruction of a state logic structure, forming an ordered tripping path, introducing a long short-term memory neural network to carry out time alignment on a state change sequence and a current signal segment, identifying a potential mismatch or abnormal change trend in a state chain through linkage analysis of a state-current abrupt change position, and reconstructing a state path. According to the method, path continuity and dynamic adaptability are enhanced, a random forest is adopted to take device numbers, the number of jump segments and response residual errors as multiple inputs for training modeling, device scores are output through an integrated tree voting mechanism, and recognition sorting of abnormal frequency significant devices is achieved.

The invention relates to the technical field of leakage protection, and provides a self-adaptive mining low-voltage leakage protection method based on working conditions, which comprises the following steps: detecting leakage resistance in real time, and determining the operation condition of a power grid; according to the power grid operation condition, matching a target detection algorithm in preset detection algorithms; wherein the preset detection algorithm comprises an integrated zero-sequence current break variable method, a zero-sequence current and zero-sequence voltage phase method and a zero-sequence current size phase comparison method; according to a target detection algorithm, establishing a unified criterion to coordinate the action logic of the main switch and each branch switch, and determining the electric leakage degree of the electric leakage resistor; and according to the electric leakage degree, performing switch locking on the electric leakage branches in sequence.

The invention relates to the technical field of battery management, and discloses a battery management system with an active monitoring function, which comprises a processor, a battery state monitoring module, an active equalization control module, a performance evaluation module and a fault early warning module. The battery state monitoring module collects various parameters of a battery at different stages, and generates an abnormal signal by using a dynamic threshold algorithm. The active equalization control module adjusts an equalization strategy based on a fuzzy logic algorithm, and a fuzzy rule base can be updated. And the performance evaluation module tracks and evaluates an equalization process, analyzes equalization efficiency and quality, and optimizes an equalization strategy accordingly. The fault early warning module displays abnormal signals in a grading mode and carries out early warning, and the processor is further connected with the aging feature extraction module and the thermal runaway prediction module to achieve battery life prediction and thermal runaway early warning. According to the invention, comprehensive monitoring, efficient equalization control, accurate performance evaluation and reliable fault early warning of the battery are realized, the safety of the battery is improved, and the service life of the battery is prolonged.

The invention discloses a digital calibration system and method for dynamic response parameters of a surge protection circuit, relates to the technical field of power electronic protection and test calibration, and is used for solving the problem that an existing surge protection circuit calibration method cannot reflect device degradation and dynamic response mismatch. Surge event voltage and current waveforms are collected through a synchronous trigger mechanism, non-stationary signal features are extracted through combined time-frequency analysis, and a voltage-current phase trajectory diagram is constructed to generate a response feature matrix; performing phase-space reconstruction on the matrix, calculating Kolmogorov entropy quantification system stability, and establishing a material degradation transfer function in combination with an energy absorption sequence to generate a grain boundary degradation index; key parameters are screened through L1 regularization regression, and a quantitative relation between a grain boundary degradation index and a protection threshold value is established to realize adaptive threshold value calculation; and executing strategy switching from calibration to predictive maintenance according to the degradation trend and threshold fluctuation change, and outputting a maintenance signal to complete dynamic accurate calibration and reliable operation of the surge protection circuit.

The invention belongs to the technical field of low-voltage switch cabinet operation control, and particularly discloses an intelligent low-voltage switch cabinet system based on a building intelligent function, which comprises an operation sensing module, a spatial topology module, a fusion diagnosis module, a fault positioning module and a dynamic protection module, current and insulation resistance are synchronously detected at a circuit wiring terminal of the low-voltage switch cabinet, temperature and humidity distribution data of the surrounding environment are collected, and then coupling characteristics between the current and temperature rise are fused. And carrying out visual display of coupling and time sequence correlation in the built three-dimensional heat-electricity correlation topological graph in the switch cabinet by utilizing the time sequence correlation between the insulation resistance and the humidity change, so as to realize comprehensive identification of potential faults. According to the method, the sensitivity and the accuracy of fault identification are effectively improved, early fault symptoms such as poor contact and insulation degradation can be found earlier, the early warning capability of the system is enhanced, and the safety and the stability of operation of the switch cabinet are guaranteed.

The invention provides a remote intelligent control distribution box, which belongs to the technical field of distribution boxes and comprises a control chip, a wireless communication device, a current monitoring device, a voltage monitoring device, a temperature monitoring device, a leakage protection device, a circuit breaker state monitoring device, a grounding state monitoring device, a humidity monitoring device and a power management device. A control module is arranged in the control chip and is used for acquiring output data of the current monitoring device, constructing a linear temperature rise prediction model, identifying potential fault types by using a decision tree algorithm, operating a lightweight power distribution network sensing model to process dimension-reduced time sequence data and realizing low-calculation-amount feature extraction by adopting a sparse attention mechanism; and when the system health state risk score exceeds a threshold value, a protection strategy is adjusted, and fault precursor characteristics are recorded. The technical problem that early warning of the abnormal state of the power distribution system is difficult to realize in a low-computing-resource environment is solved.

The invention discloses a power distribution network fault self-healing power restoration method and device, and belongs to the technical field of power distribution networks. Obtaining fault data corresponding to a plurality of fault types, performing fault simulation in the mathematical model of the power distribution network, and determining a self-healing power restoration operation rule; acquiring operation data of the power distribution network in real time, determining a current fault type of the power distribution network, and determining equipment action constant values and equipment action sequences corresponding to the plurality of protection equipment in the self-healing power restoration operation rule; when the operation data of the power distribution network reaches the equipment action constant value, performing isolation processing on each protection equipment according to the equipment action sequence, and collecting the isolated operation data of the power distribution network, thereby determining a fault area and a non-fault area of the power distribution network; and removing the fault area, and forwarding the non-fault area. Therefore, by implementing the method, the problem of low self-healing power restoration efficiency of the power distribution network in the prior art can be solved.

The invention discloses an electrical equipment overload protection method and system based on multistage load monitoring, and relates to the technical field of electrical equipment overload protection, and the method comprises the steps: setting an equipment-level monitoring node, a line-level monitoring node and a system-level monitoring node, and obtaining a three-level load data set; constructing a load characteristic matrix; setting an initial overload threshold conforming to the industrial standard of the switch equipment; a correction coefficient is configured, and the initial overload threshold value is synchronously corrected; drawing up a grading threshold comparison table; meanwhile, a load dynamic constraint mechanism and an equipment health intervention mechanism are set, and electrical equipment overload protection parameter setting is carried out. The technical problems that in the prior art, the overload protection threshold value of the electrical equipment is fixed, dynamic adjustment is lacked, and the adaptability to the health state and load change of the equipment is insufficient, so that protection pertinence and effectiveness are low are solved, accurate overload protection of the electrical equipment is achieved, and the safety of the electrical equipment is improved. And the technical effects of pertinence and effectiveness of overload protection are improved.

The invention belongs to the field of overvoltage protection, and relates to an overvoltage stabilizing and protecting device which comprises a data acquisition operation module, a control logic module, a display module, an overvoltage protecting assembly and a high-voltage vacuum circuit breaker or an electric isolation handcart structure. The real-time monitoring and protection of the working state of the overvoltage protection assembly are realized; through the arrangement of the high-voltage circuit breaker or the electric isolation handcart, when the overvoltage protection assembly is detected to be abnormal, the connection between the overvoltage protection assembly and the high-voltage bus can be rapidly cut off, so that the system safety is ensured; the device integrates a transient fault recording function and can capture wave map data before and after a power frequency overvoltage fault of the system; the overvoltage protection assembly in the device adopts a geometric center air cooling heat dissipation mode, the fan is quick in starting response, the operating temperature of the overvoltage protection assembly is greatly reduced, the operating time of the overvoltage protection assembly can be effectively prolonged, and the device adopts an integrated modular structural design, so that the operation safety, the maintenance and the management are greatly facilitated.

The invention discloses a microcomputer synchronous automatic closing analysis system, which relates to the technical field of power system automation and comprises a data acquisition module, a data processing and storage module, a machine learning analysis module, a closing control module and a maintenance decision module. Electrical quantity data and equipment state data are monitored in real time through the data acquisition module, and the machine learning analysis module is utilized to perform modeling analysis on key parts and the overall operation state of the system, so that health assessment and fault prediction of the key parts are realized; when a fault possibly influencing closing safety or a health score of a key component is predicted to be lower than a set threshold value, the closing control module can adjust a closing control strategy to ensure the safety and reliability of closing operation, and the intelligent closing control mechanism remarkably improves the operation safety and reliability of the microcomputer synchronous automatic closing system.

The invention discloses a relay protection method and device based on time sequence data prediction, and the method comprises the steps: collecting the operation sequence data of a main network power transformation relay protection device in real time through a wireless sensing node, and transmitting the operation sequence data to a data processing layer through a Zigbee wireless network protocol; historical data features are extracted based on a sliding window method, abnormal data are recognized and removed through a quartile method, and missing data are filled up through a linear interpolation algorithm; constructing a CNN-GRU prediction model fused with the attention mechanism, dynamically weighting key features by the attention mechanism, inputting the preprocessed data into the model for training, and generating an operation state evaluation value based on a prediction result, and when the evaluation value exceeds a preset threshold, triggering a multi-level early warning mechanism. And the prediction precision is verified by using a decision coefficient R2, the R2 is required to be greater than or equal to 0.95, and model parameters are dynamically updated to adapt to the working condition change of the power grid.

The invention relates to the technical field of box transformer substation control, and particularly discloses an intelligent charging box transformer substation overload protection threshold value dynamic calculation method and related equipment, and the method comprises the steps: continuously obtaining the load information, the in-box temperature information and the environment temperature information of an intelligent charging box transformer substation; identifying and acquiring a parameter set of the dynamic thermodynamic model to determine the dynamic thermodynamic model; the identified dynamic thermodynamic model is utilized to predict the temperature in the box at the next moment based on the load information and the environment temperature information; based on the predicted temperature in the box and a preset safe temperature threshold value, a temperature margin is obtained through calculation; adjusting an overload protection threshold according to the temperature margin; according to the method, the self-adaptive adjustment of the overload protection threshold is realized, so that the overload protection strategy can dynamically change according to the actual operation state of the box-type transformer substation, the safe operation of the box-type transformer substation under the working conditions of slow heat dissipation and load fluctuation is ensured, the overload capacity of the box-type transformer substation is fully utilized, and the continuity of the charging service is improved.

The invention discloses a reclosing coordination control method and system based on electrical parameter measurement, particularly relates to the technical field of intelligent power grid fault processing and security defense, and is used for solving the problem that the reliability of fault judgment is reduced due to the fact that high-proportion distributed photovoltaic is connected to a power distribution network. A harmonic detection signal is injected during a reclosing waiting period, a response signal is measured, harmonic subspace energy distribution is extracted, an energy distribution matrix is constructed to calculate a nuclear norm change rate and form similarity, a system harmonic impedance stable state is judged through double verification, and finally a reclosing decision is executed according to a fault judgment parameter. The method can accurately identify the convergence characteristic of the dynamic process of the system, effectively distinguish the instantaneous fault from the permanent fault, and significantly improve the reclosing success rate and the power supply reliability of the distributed photovoltaic power distribution network.

The invention discloses a relay protection setting value checking optimization method based on an AI technology, and belongs to the technical field of relay protection setting value.The method comprises the steps that historical operation records are collected from an electric power system, a setting value analysis model is established according to the historical operation records, and the setting value analysis model is used for analyzing setting value input data to obtain a relay protection setting value; determining an acquisition item and a data acquisition mode according to the constant value analysis model, and performing data acquisition and processing according to the acquisition item and the data acquisition mode to obtain constant value input data; optimizing and adjusting a data acquisition mode based on the constant value input data; analyzing the constant value input data through a constant value analysis model to obtain a relay protection constant value; optimizing and adjusting the constant value analysis model according to the analysis record of the relay protection constant value; identifying an application protection setting value in real time; and comparing the relay protection constant value with the application protection constant value to obtain a constant value checking result, and optimizing and adjusting the application protection constant value according to the constant value checking result.

The invention relates to the technical field of electric leakage protection, and particularly discloses a full-working-condition self-adaptive electric leakage protection device, which comprises a data acquisition module used for acquiring electrical data of electrical equipment in real time, including load current, active power and operating voltage value, and calculating the real-time electric data of the electrical equipment by combining the real-time electrical data of the electrical equipment; the real-time load state influence coefficient of the electrical equipment can be obtained through calculation in a diversified data fusion mode, the data can reflect the real-time operation condition of the electrical equipment, namely, which operation state the electrical equipment is in a no-load state, a light-load state and a heavy-load state, and on this basis, the real-time load state influence coefficient of the electrical equipment can be obtained through calculation. According to the invention, the leakage current monitoring threshold is adjusted in real time based on the real-time operation condition of the electrical equipment, so that the situation of malfunction or leakage protection caused by significant difference of parameters such as current characteristics, harmonic content and insulation stress of a power grid under different loads can be avoided, and the accuracy of a leakage monitoring result is improved.

The invention discloses a distribution network constant value setting method and system for large-scale distributed photovoltaic grid connection, and relates to the technical field of power system relay protection, and the method comprises the steps: carrying out the protection region division of a power distribution network according to the network topology parameters of the power distribution network, and obtaining a plurality of protection regions; fault characteristic parameters in the protection areas are calculated respectively, and the distributed power supplies in the protection areas are classified and modeled based on the fault characteristic parameters to obtain an equivalent model; and calculating a protection setting value parameter based on the equivalent model, and generating a protection setting value setting result. According to the method, the dynamic response characteristics of the distributed power supply group can be accurately reflected, the problem of large errors of the protection range and sensitivity calculation in a traditional method is effectively solved, and reliable technical support is provided for protection configuration of a large-scale distributed photovoltaic grid-connected power distribution network.

The invention discloses a modular high-voltage SVG circulating current suppression method. The method comprises the steps of obtaining and preprocessing module circulating current, voltage and state data; constructing an enhanced phase space fused with multiple physical quantities, extracting circulating current phase features and generating dynamic trend prediction data; calculating optimal feed-forward and feedback virtual impedance parameters based on phase characteristics and trend prediction; and generating a module control voltage correction value and a PWM control signal by applying a multi-time scale hybrid control strategy. Through hybrid control of phase space reconstruction of topology perception, multi-dimensional entropy analysis and stability guarantee, efficient suppression of the circulating current is realized, and the stability and robustness of the SVG system are improved.

The invention discloses an insulation fault edge self-healing method and device for a power conversion system, and belongs to the technical field of fault diagnosis and automatic maintenance of power electronic equipment, and the method comprises the steps: obtaining multi-modal sensing data, synchronously collected by a multi-modal sensor array, of the power conversion system; a preset lightweight CNN-Transform hybrid model is used to process the multi-modal sensing data, and a feature vector of each modal is obtained; fusing each modal feature vector by adopting a dynamic weight attention mechanism to obtain a fused fault feature vector; classifying the fused fault feature vectors based on a fault classifier, and determining a fault level; and according to the determined fault level, sending a corresponding control instruction to an execution mechanism, and triggering a hierarchical self-healing action. According to the invention, fault identification and self-healing decision can be rapidly completed, and the accuracy of fault detection is effectively improved.

The invention discloses a graph topology-based power distribution network protection parameter automatic checking method and system, and belongs to the technical field of power transmission and distribution. The method comprises the steps of obtaining a transformer substation outgoing line protection constant value, a terminal protection constant value, line zero-sequence current data, a topological relation below the transformer substation, line parameters and operation state data of lines, switches and distribution transformers; sVG analysis and power distribution network topological graph construction are carried out; subgraph extraction and hierarchy analysis; line parameter and protection constant value verification, including line parameter verification and protection constant value verification; the line parameter verification comprises branch line segment verification and switch position verification; the protection constant value verification comprises overcurrent I section verification, overcurrent II section verification and zero sequence protection verification. According to the method, automatic checking of the power distribution network protection parameters is realized, the checking efficiency and accuracy are greatly improved, and the method is suitable for a protection constant value checking scene of a complex power distribution network.

The invention provides a control method and system for an energy storage PCS with an AC / DC circuit breaker and a storage medium, and the method comprises the steps: firstly, synchronously collecting the electrical parameters of a DC side and an AC side, and carrying out the preprocessing of the collected data, so as to form a standardized electrical matrix; then, all parameters in the electrical matrix are cyclically compared with corresponding early warning thresholds, first-level thresholds, second-level thresholds and fusing thresholds in a multi-level threshold mapping table; if the pre-warning threshold value is exceeded, a log is recorded, if the pre-warning threshold value is exceeded, self-healing operation is executed, if the pre-warning threshold value is exceeded, turn-off operation is executed, and if the pre-warning threshold value is reached, physical fusing is triggered; meanwhile, all operation logs are recorded, and the threshold mapping table is dynamically optimized by analyzing log data; according to the method, the fault response speed and the protection precision are improved through multi-level threshold serial comparison and a cooperative protection mechanism, the stability and the reliability under different working conditions are enhanced through the adaptive learning capability, and meanwhile, the whole life cycle cost is reduced.

The invention relates to the technical field of power system protection, in particular to an underground power distribution network single-phase grounding protection system and method based on a signal injection method. The system comprises a signal acquisition module, a measurement and control protection module and an online monitoring module. According to the invention, by injecting the independent direct current signal and combining a zero-sequence fundamental wave time sequence identification algorithm and a traveling wave distance measurement method, rapid detection, high-precision positioning and selective protection of the single-phase earth fault of the underground low-voltage power distribution network are realized, and the method is suitable for complex environments such as coal mines and metal mines; through insulation value on-line monitoring and electric leakage protection, the ground insulation value level of a line is reflected to the voltage change of an additional direct current signal and a reactor neutral point. A zero-sequence fundamental wave time sequence identification model is adopted for electric leakage fault judgment so as to judge the fault type. By outputting a relay signal, on-off control is performed on a protected branch, so that a fault line can be quickly cut off when a fault occurs, and equipment and a bus are protected from being damaged by the fault.

The invention provides a power distribution network differential protection data compression method, device and equipment and a medium, and the method comprises the steps: obtaining the sampling data of a power distribution network, carrying out the feature classification of the sampling data at an edge node of the power distribution network according to the protection demands, and obtaining a fundamental current vector, high-frequency transient energy and an accurate timestamp; acquiring a real-time network bandwidth and a fault risk assessment result of the power distribution network, and selecting a compression mode according to the real-time network bandwidth and the fault risk assessment result; according to a compression mode, sequentially carrying out characteristic grading compression on the fundamental wave current vector, the high-frequency transient energy and the precise timestamp to obtain a characteristic data packet of the power distribution network; and transmitting the characteristic data packet to the master station side module through a hybrid communication network. The sampling data is divided into the fundamental component, the high-frequency transient component and the precise timestamp, the compression priority is distributed according to the differential protection requirement, the performance bottleneck caused by the fixed compression rate is broken through, and the redundant data volume during differential data compression is effectively reduced.

The invention discloses a power relay protection monitoring method and device based on intelligent matching and a medium, relates to the field of power relay protection, and solves the problem that a relay protection device is not adaptively arranged in combination with factors such as actual operation conditions during relay protection of a current power system. Matching and acquiring power failure data and power use data of the power line according to the line number; s2, setting relay protection measures of the power line according to the power fault data; s3, real-time operation data of different power lines are collected in real time, and the operation conditions of the power lines are analyzed and judged according to the real-time operation data; step S4, acquiring real-time determined duration of the fault section corresponding to the power line; and S5, analyzing the protection efficiency of the relay protection measure corresponding to the power line according to the determined duration. According to the invention, effective relay protection of the power system is realized based on the intelligently configured relay protection measure.