1181 results about "Distribution transformer" patented technology

The invention discloses a precise positioning method for a leakage fault source of a low-voltage distribution network, which belongs to the technical field of power system fault diagnosis and comprises the following steps: acquiring and calculating the voltage unbalance degree and the zero-sequence current value at a total outgoing line of a distribution transformer, generating a primary leakage trigger signal based on a voltage safety threshold and a current safety threshold, and determining the leakage fault source of the low-voltage distribution network. Injecting a characteristic signal with a preset frequency into the line, monitoring the response in the zero sequence loop, and calculating and generating a reference fault path impedance spectrum; and according to the switch topology of the line, sequential opening operation and closing operation are executed to calculate a real-time fault path impedance spectrum, whether impedance spectrum jump exists is judged, a fault branch indication signal is identified and generated, multi-source synchronous data is used for verification, and final fault positioning information is output. Impedance spectrum analysis is carried out by injecting characteristic signals, differential comparison is carried out by combining intelligent switch sequential operation, multi-source synchronous data is utilized to carry out multi-evidence chain verification, and high-precision and high-reliability positioning of an electric leakage fault source can be realized.

The invention discloses a distribution transformer monitoring system and method, and relates to the technical field of electric power intelligent monitoring, and the method comprises the steps: obtaining the three-dimensional temperature gradient field distribution and mechanical stress distribution of a distribution transformer based on a standardized multi-source data set, and outputting a comprehensive field matrix through a field coupling analysis method; performing spatial analysis on the comprehensive field matrix by adopting spatial hot spot analysis, identifying and marking temperature and mechanical stress abnormal areas, performing spatial aggregation and noise filtering through an OPTICS density clustering algorithm, and outputting abnormal feature vectors; inputting the abnormal feature vector into a pre-trained intelligent diagnosis model, outputting a comprehensive fault risk score and performing preliminary diagnosis; searching fault data in a historical case library based on the preliminary diagnosis result for comparison verification, and optimizing the preliminary diagnosis result through a machine learning algorithm to generate a final diagnosis result; according to the method, a field coupling analysis method is adopted to establish a heat-force bidirectional action model, and the spatial distribution characteristics of the temperature gradient and the stress tensor are accurately reflected.

The invention relates to the technical field of power system regulation and control, in particular to a mutual aid regulation and control method and system for multiple power distribution transformer areas considering capacity margin, and the multiple power distribution transformer areas comprise N low-load power distribution transformer areas and M high-load power distribution transformer areas which are connected through N + M interconnection devices; the load rate of the low-load power distribution area is less than or equal to a first load rate threshold, and the load rate of the high-load power distribution area is greater than a second load rate threshold; the regulation and control method comprises the following steps: constructing a comprehensive constraint condition based on an economic operation constraint condition and a mutual aid capacity margin constraint condition of a power distribution area; constructing a multi-objective function based on the power distribution area loss objective function and the economic benefit objective function; building a target optimization model through a comprehensive constraint condition and a multi-target function; and obtaining an optimal power distribution scheme based on the target optimization model, and performing hierarchical cooperative control execution. Through the regulation and control method and system, the problem of insufficient load sensitivity can be effectively solved.

The invention relates to the technical field of power distribution network risk early warning, in particular to a power distribution network abnormal risk early warning method based on a multi-mode space-time large model. According to the method, a mapping relation between multi-dimensional influence factors such as a source load space-time matching characteristic, voltage sensitivity, a net load peak value, a power distribution network topological structure and meteorological data and a new energy power distribution network abnormal risk is deeply mined based on a Lama large model; and respectively constructing independent optimization branches of power distribution network node voltage out-of-limit prediction and transformer area distribution transformer weight and overload prediction, and balancing a synchronous optimization target of prediction of different abnormal risk events through a multi-task weighted loss function. The method comprises the following steps: aligning text information and spatio-temporal information of historical marking abnormal risks of a new energy power distribution network by adopting a spatio-temporal instruction fine tuning model, dynamically adjusting model parameters, and generating an abnormal risk auxiliary prediction threshold in combination with a risk judgment threshold; therefore, occurrence moments and positions of abnormal risks such as node voltage out-of-limit of the new energy power distribution network and heavy and overload of the distribution transformer in the transformer area can be accurately predicted.

The invention relates to the related technical field of distribution transformer insulation aging, in particular to a frequency domain diagnosis method, system and device for distribution transformer insulation aging and a medium, and the method comprises the steps: carrying out the frequency response test of a to-be-tested transformer, and obtaining a first frequency response curve; performing a frequency response simulation test on a transformer equivalent circuit model pre-constructed based on the to-be-tested transformer to obtain a second frequency response curve; constructing a target function based on the deviation of the first frequency response curve and the second frequency response curve; taking element parameters in the equivalent circuit model of the transformer as position vectors, taking the objective function as a fitness function, and adopting a multi-objective particle swarm algorithm to solve the element parameters to obtain optimal values of the element parameters; respectively comparing the optimal values of the element parameters with corresponding normal values to obtain insulation aging degrees; according to the method, the insulation aging degree can be obtained by comparing the element parameters obtained through optimization with the normal unaged element parameters.

The invention discloses a distribution transformer state evaluation method, system and device and a storage medium, and the method comprises the steps: obtaining current and voltage long sequence data through high-frequency sampling, and forming a high-quality data set through expert labeling; signal preprocessing is realized by adopting dual-channel adaptive wavelet packet denoising and cross-correlation sinchinger interpolation phase correction; constructing an asymmetric convolution pyramid to extract current high-frequency and voltage low-frequency multi-scale features, and performing cross-modal fusion by using compressed multi-head attention and a channel-space double-gating mechanism; dynamic random depth regularization is introduced, and a time domain loss function in a fault sensitive period is focused, so that high-accuracy and low-delay real-time state evaluation is realized; the capacity of capturing and recognizing early weak fault features of the distribution transformer in a complex operation environment is remarkably enhanced, and therefore more sensitive and more accurate state early warning is achieved.

The invention relates to the technical field of power grid deicing, in particular to an alternating current short circuit ice melting control method and an ice melting distribution transformer. The invention discloses a distribution transformer with voltage reduction and ice melting dual functions, an ice melting control system and a control method thereof. The transformer is provided with two groups of low-voltage output ends which are respectively used for power distribution, power supply and ice melting operation; the ice melting control system comprises a local intelligent control box and a far-end communication control box, and adopts a deep reinforcement learning model to calculate an optimal ice melting power gear and ice melting time; according to the control method, environment parameters and equipment parameters are obtained, cooperative control of the boundary switch, the ice melting switch, the protection switch and the short circuit switch is combined, and accurate adjustment of the ice melting process is achieved. The system realizes a one-key ice melting function, has the characteristics of simple operation, high ice melting efficiency, remote control and the like, remarkably improves the intelligent level, safety and reliability of power grid ice melting operation, and provides an innovative solution for anti-ice management of a power system.

The invention relates to a distributed photovoltaic transformer area metering data abnormity tracing method, belongs to the field of intelligent power distribution networks, and solves the problem of low metering abnormity user positioning efficiency caused by topological information loss of a low-voltage photovoltaic transformer area. Comprising the following steps: acquiring electrical data of a distribution transformer and each user when a distributed photovoltaic transformer area has no photovoltaic output at night, and constructing a transformer area trunk line approximate topology; constructing an inter-node final adjacency matrix between nodes on the basis of the acquired voltage data of each user in the afternoon photovoltaic high output time period of the transformer area; clustering based on the final adjacency matrix among the nodes to divide the users into a plurality of user clusters; constructing a cluster power curve for each user cluster, and calculating the fluctuation consistency between the voltage of each user in the cluster and the cluster power curve of the cluster to which the user belongs based on the approximate topology of the main line of the transformer area so as to identify a suspected abnormal cluster; and performing node-level identification on the suspected abnormal cluster to obtain an abnormal metering user. Automatic traceability and accurate positioning of abnormal measurement data are realized.

The invention relates to a self-adaptive data acquisition method and system for an intelligent distribution transformer monitoring unit, and the method comprises the steps: monitoring a plurality of operation parameters in a power distribution network in real time through the intelligent distribution transformer monitoring unit; classifying various monitored operation parameters into conventional monitoring data and abnormal monitoring data according to the operation state of the power distribution network, analyzing the current state of the power distribution network based on the real-time monitoring data, and judging whether the power distribution network is in a normal, load or abnormal state; constructing a distribution transformer monitoring prediction model for identifying the operation state of the power distribution network, predicting potential faults or abnormal conditions, and determining the frequency and type of data acquisition according to the prediction result; under the normal operation state of the power distribution network, various operation parameters in the power distribution network are acquired by adopting low-frequency data; when the load change of the power distribution network is large or a fault is about to occur, the data acquisition frequency is improved; when a fault or abnormity occurs, the highest-frequency data acquisition mode is started immediately, and detailed power distribution network data are collected in real time.

The invention discloses a column type distribution transformer winding abnormity detection system and detection method. The detection system comprises a frequency response detection instrument, a signal coupling assembly, an impedance matching module and a data processing module. The frequency response detection instrument is used for outputting a frequency sweep excitation signal and collecting a winding response signal; the signal coupling assembly is used for isolating power frequency voltage and filtering low-frequency interference; the impedance matching module is used for adjusting output impedance and input impedance to realize matching with electrical characteristics of different windings; and the data processing module is used for constructing an equivalent detection loop model, completing frequency response simulation calculation and carrying out frequency domain analysis and anomaly identification on an actually measured response curve. According to the invention, electrified state diagnosis of distribution transformer winding structure abnormity (such as deformation and loosening) can be realized.

The invention discloses a method for predicting the service life of a transformer in a high-proportion new energy access zone based on multi-physics field modeling, and the method comprises the steps: building an electromagnetic field-temperature field coupling simulation model based on a COMSOL simulation platform, and setting the electrical parameters, oil physical parameters and material physical attributes of the transformer; secondly, simulating a photovoltaic access working condition by utilizing a multi-power supply superposition mode, obtaining key data such as three-phase voltage, three-phase current, iron core magnetic flux density, oil temperature and winding temperature, calculating a life label based on a working state, and performing quantitative evaluation on the state of the transformer by adopting a health state scoring method; and finally, constructing a Perii-midFormer life prediction model to realize prediction of the residual life of the transformer. Compared with a traditional life evaluation method, the method fully considers the multi-physical field dynamic coupling effect caused by photovoltaic access, improves the adaptability and reliability of life prediction, and provides an important reference for the operation and maintenance of a transformer in a power distribution network.

The invention provides a power distribution area interconnection planning method and related equipment, and the method comprises the steps: obtaining the historical data of distributed new energy output and load power of a target area, and calculating the maximum net load rate of each low-voltage power distribution area to determine a heavy overload area; the method comprises the following steps of: interconnecting a heavy overload transformer area and a transformer area connected with new energy with other normal transformer areas, screening out interconnectable combinations of the transformer areas, and taking all original connecting lines of a medium-voltage distribution network as SOP to-be-selected lines; based on the interconnectable combination of the transformer area and SOP candidate lines, by constructing a target function and constraint conditions with the optimal economical efficiency as a target, obtaining a mixed integer linear programming model converted from a distribution transformer area interconnection stochastic programming model under multiple scenes and solving the mixed integer linear programming model, and obtaining a transformer area interconnection programming scheme and a medium-voltage distribution network SOP access condition; power mutual aid and capacity sharing between low-voltage distribution areas are achieved, local consumption of distributed new energy is promoted, and the heavy overload phenomenon of the areas is relieved.

The invention relates to the technical field of power grid bearing capacity evaluation, in particular to a method and system for evaluating the bearing capacity of a power distribution network. The method comprises the following steps: obtaining a noise reduction power distribution network operation data set; performing three-phase imbalance index calculation based on the noise reduction power distribution network operation data set to obtain three-phase imbalance characteristic data; performing wavelet transform decomposition on the noise-reduced operation data set of the power distribution network to obtain photovoltaic output fluctuation characteristic data; associating the photovoltaic output fluctuation characteristic data with the three-phase imbalance characteristic data to obtain a photovoltaic-imbalance mapping relation model; performing electric-thermal coupling modeling on the distribution transformer winding based on the photovoltaic-unbalanced mapping relation model to obtain a thermodynamic response model of the distribution transformer; and performing finite element thermal field simulation on the thermodynamic response model of the distribution transformer to obtain winding temperature distribution data. By accurately quantifying the influence of the intermittent output of the photovoltaic inverter on the three-phase imbalance of the distribution transformer, the defect that the traditional method is difficult to accurately evaluate is overcome.

The invention is suitable for the technical field of intelligent power grids, and relates to a G3-PLC communication characteristic-based power distribution network area physical topology identification method, which comprises the following steps of: S10, constructing a power distribution network area physical topological graph model; s20, determining an edge weight in the physical topological graph model of the distribution network area; s30, improving and constraining a minimum spanning tree (MST) based on a Prim algorithm of G3-PLC communication characteristics, and improving a Prim algorithm flow; and S40, identifying the physical topological structure of the power distribution network area. The method is simple in process and convenient to operate, on the basis of not adding extra hardware equipment and any manual operation, the weighted graph is constructed through G3-PLC communication data, the minimum spanning tree (MST) is generated through the Prim algorithm, the physical topological structure of the power distribution network area is recognized, and the recognition accuracy is high.

The invention discloses a 10kV distribution transformer on-load voltage regulation control method and system, and relates to the technical field of transformer on-load voltage regulation, and the method comprises the steps: collecting the three-phase voltage and current of a low-voltage side of a distribution transformer and a tap switch gear signal, and loading a preset voltage regulation control mode and an oscillation region parameter; based on the acquired three-phase voltage and current of the low-voltage side of the distribution transformer and the tap switch gear signal, calculating a feeder comprehensive impedance parameter and a load reactive power parameter, and outputting a transformer operation state index; according to the transformer operation state index, the voltage regulation control mode and the oscillation area rule, current voltage out-of-limit and reactive power deviation are judged, and a voltage regulation strategy triggering instruction is generated according to the judgment result; and calculating upper and lower limit values of feed line correction voltage based on the voltage regulation strategy trigger instruction, and controlling the tap switch to execute voltage regulation action. According to the method, a combined calculation scheme of feeder comprehensive impedance and load reactive power is fused, and dynamic optimization of the triggering condition of the voltage regulation strategy is achieved.

The embodiment of the invention discloses a low-voltage reactive power compensation equipment state evaluation method, and the method comprises the steps: collecting basic data of low-voltage reactive power compensation equipment, the basic data comprises a voltage, a power factor, an active load, a distribution transformer low-voltage side reactive load, a distribution transformer low-voltage side active power, a reactive power, a common compensation capacitor rated capacity, a separate compensation capacitor rated capacity and a voltage abnormal duration; determining an evaluation index according to the basic data; and determining the operation state of the low-voltage reactive power compensation equipment according to the evaluation index. According to the method, the basic data is collected, the evaluation index is determined according to the basic data, the operation state of the low-voltage reactive power compensation equipment is further judged, the health condition and performance of the equipment can be comprehensively and objectively evaluated, the accuracy of state evaluation of the low-voltage reactive power compensation equipment can be improved, and the working efficiency is improved. And real-time monitoring and early warning of the operation state of the equipment can be realized.

The utility model discloses a low-voltage outgoing line flexible connection device of a distribution transformer, which belongs to the technical field of transformer wiring and comprises two connectors, a plurality of connecting holes and a plurality of connecting terminals. The connector comprises two connectors, a plurality of flexible copper strips, the flexible copper strips are located between the two connectors, the ends of the flexible copper strips are connected with the connectors in an inserted mode, and the relative positions between the ends of the flexible copper strips and the centers of the connectors change along with changes of stress. The deformation quantity is compensated through sliding of the limiting frame, under the action of the elastic piece, the soft copper strip can be always kept in a tightened state, and meanwhile, due to the arrangement of the elastic frame, the soft copper strip can be prevented from being scattered, and the situation that the soft copper strip makes contact with other external components when deformed, and danger is generated can be avoided.

The present invention discloses a short-circuit resistant distribution transformer, comprising an oil tank, a body, an iron core, and a coil, wherein the body is arranged inside the oil tank, the iron core is arranged on the body, and the coil comprises a high-voltage coil and a low-voltage coil, wherein the low-voltage coil is arranged inside the high-voltage coil, and the low-voltage coil is arranged outside the iron core. Main technical scheme and effect: The coil is compressed by insulating blocks at both ends, which effectively avoids the situation that a short circuit is easily generated when the coil is loose, and can increase the distance between the coil and the upper pressing plate and the lower pressing plate, thereby improving the insulation effect between the coil and the upper pressing plate and the lower pressing plate.

The invention discloses a distribution transformer equipment state evaluation method and system based on machine learning. The method comprises the following steps: acquiring operation data and environment data of a distribution transformer; based on the operation data and the environment data, utilizing an improved DBSCAN algorithm to perform clustering analysis, and adopting an interval value method to perform normalization processing to obtain a data set; calculating based on the data set in combination with a pre-constructed state evaluation model to obtain an operation state of the distribution transformer; wherein the state evaluation model is obtained by taking the operation state of the distribution transformer as output, and training by utilizing the input data and combining with a CatBoost algorithm; according to the invention, the improved DBSCAN algorithm is utilized to optimize the data set, so that the realization effect of the state evaluation model can be effectively improved; according to the method, the state evaluation model is established by using the machine learning algorithm, so that errors and uncertainty caused by human subjective judgment are reduced, the intelligent level of equipment state evaluation is improved, loss caused by equipment failure and shutdown is effectively avoided, and accurate evaluation of the transformer equipment state is realized.

The invention discloses a transformer area topological structure estimation method, system, equipment and medium based on multi-dimensional power utilization characteristics, and belongs to the technical field of power distribution transformer area topologies, and the method comprises the steps: collecting multi-source data, carrying out dynamic weight distribution and abnormal value correction, carrying out the characteristic extraction according to the collected multi-source data, and generating a high-dimensional characteristic vector; clustering user nodes, dividing cluster labels, performing topological modeling according to a cluster division result, generating a topological graph, and performing anomaly verification through multi-dimensional anomaly scoring and abnormal power utilization detection; and performing incremental model parameter correction and multi-objective optimization according to anomaly verification feedback, and generating dynamic topological graph rendering and multi-dimensional decision suggestions by integrating topological modeling, anomaly verification and optimization results. According to the method, accurate estimation of a topological structure is realized through dynamic clustering and hidden node recognition, real-time diagnosis of abnormal nodes and self-correction of a model are realized by means of a multi-dimensional abnormal scoring and self-adaptive optimization mechanism, and the accuracy and operation and maintenance efficiency of transformer area management are improved.

The invention relates to the technical field of source network load storage cooperative control, in particular to an area source network load storage cooperative optimization control system based on an intelligent fusion terminal, and the system comprises an acquisition module which acquires energy characteristic parameters and cooperative response characteristic parameters of a target area in a historical period; analyzing an energy characteristic characterization value based on the energy characteristic parameter through an analysis module, and calculating a collaborative response characteristic characterization value based on the collaborative response characteristic parameter; determining a corresponding control strategy based on the energy feature representation value through a control module; through a verification module, whether the stability of the transformer area source network load storage meets the standard is judged based on the collaborative response characteristic representation value; and through a feedback module, based on a difference value between the energy feature representation value and a predetermined energy feature representation threshold, determining an adjustment amplitude of the cooperative response feature representation threshold, and performing collection and verification again. According to the invention, through the verification module and the feedback module, the response rate of cooperative control of each link of source network load storage is improved.

The invention relates to the field of power systems, in particular to a method and system for solving the problem of low voltage of a transformer area. The method comprises the following steps: S1, monitoring voltage data of a transformer area line in real time, and generating a low-voltage trigger signal when detecting that a current voltage value is lower than a preset voltage threshold value; s2, calculating an initial distribution proportion of active power and reactive power needing to be adjusted of the energy storage system according to the impedance characteristic parameters; s3, generating a dynamic adjustment strategy of the energy storage system; s4, collecting the deviation between the actual output power and the target value in real time through a feedback loop, and adjusting the pulse width modulation parameter of the inverter according to the deviation so as to correct the output; and S5, voltage data of the transformer area line are obtained again, if the voltage value is recovered to the preset threshold range, an adjustment completion signal is generated, and otherwise, the steps S2 to S4 are repeated based on the updated impedance characteristic parameters. The problems that in the prior art, precision is not high, active power and reactive power cooperative control cannot be achieved, and a feedback correction mechanism is lacked are solved.

The invention provides an automatic gear shifting device and method for a transformer tap switch. The gear shifting device comprises a rack and a lifting mechanism arranged in the middle of the rack, a rotating mechanism is arranged at the lifting end of the lifting mechanism, and a mechanical arm used for clamping the tap switch is arranged at the rotating end of the rotating mechanism; the side edge of the rack is also provided with a visual acquisition and analysis module which is used for acquiring gear image information of the tap switch, analyzing gear shifting execution information and transmitting the gear shifting execution information to the rotating mechanism; the rotating mechanism rotates the tap switch to a corresponding gear based on the gear shifting execution information; the operation risk of personnel can be reduced, the gear shifting efficiency is improved, and the power failure duration of the distribution transformer is effectively shortened.

The invention discloses an automatic voltage regulating device for a power distribution area and a control method of the automatic voltage regulating device, and belongs to the technical field of power distribution network voltage treatment. The device comprises a three-phase power supply, a power supply side input circuit, a load side output circuit, a current transformer, a single-P air switch, a power supply conversion module, a three-phase independent voltage regulation module, a main path control system, an automatic bypass control system, a gear driving module, a man-machine interaction module, a display module, a monitoring module, a mode switching module, a parameter storage module and an alarm module. The system comprises a manual adjustment execution module, a counting module, a voltage detection module, a current detection module, a 4G communication module and an over-temperature protection module. A main circuit control system depends on input and output voltage data fed back by a voltage detection module, compensation voltage U can be independently calculated for differential voltage fluctuation of L1, L2 and L3 phases, intelligent adjusting switches of all phases are driven to act accurately, and finally three-phase output voltage U2 is stabilized within an allowable range.

The invention relates to a distribution network topology analysis method and system, and the method comprises the steps: carrying out the metadata analysis of a distribution line SVG file, and constructing an undirected graph, a subgraph and a connected subgraph; traversing the sub-graph by using a breadth-first search algorithm with a specified root node as a starting point, and marking a hierarchy for each node according to the distance from the root node to the current node; carrying out edge pruning based on the marked hierarchy, and converting the undirected graph into a directed graph according to a hierarchical relationship; on this basis, distribution transformer-switch relation analysis is carried out to form a basic information table of a switch to which a distribution transformer belongs, and connection line analysis is carried out to obtain a simple line connection path. According to the method, it is ensured that the sub-graphs conform to the radial structure of the power distribution network through hierarchical pruning, connection of the same hierarchy is removed, formation of an annular structure is prevented, detailed line connection paths and simple line connection paths are formed, and contact points between lines can be checked quickly and conveniently.

The invention discloses a fine recovery decision-making method and system for a distribution transformer, and the method comprises the steps: carrying out the data collection and preprocessing of a transformer, and generating a transformer feature vector; determining the current state of the transformer according to the transformer feature vector and estimating a recovery value to form a recovery decision; executing the disassembling step according to the recovery decision, monitoring the oil product characteristics of the transformer and the state of internal components of the transformer in real time, and dynamically adjusting the disassembling granularity and mode; separating recoverable components from the disassembled object, evaluating the disassembled object according to a value evaluation model, and further adjusting the disassembly granularity according to an evaluation result; and the deviation between the actual recovery value and the estimated recovery value is recorded, the estimation mode is optimized, and a post-recovery analysis report is generated. According to the method, the recycling value is accurately estimated, the disassembling is monitored and adjusted in real time, and the granularity is optimized according to evaluation, so that the disassembling efficiency is greatly improved, and the optimal strategy generation of the disassembling efficiency and the recycling value is realized.

The invention relates to the technical field of transformer internal defect diagnosis, in particular to a distribution transformer internal defect diagnosis method and device based on virtual differential current. Comprising the following steps: synchronously acquiring data; calculating an actually measured differential current; establishing a differential current model; according to a differential current model, calculating a deviation value between the actually measured differential current of each phase and a model prediction value, and taking the deviation value as the virtual differential current; carrying out filtering processing on the virtual differential current; and judging defects. According to the method, a differential current model associated with winding impedance and excitation branch parameters is constructed based on operation data when the transformer has no defects, so that the model is bound with physical topological characteristics of the transformer, and virtual differential current (deviation between a measured value and a model predicted value) can reflect actual state change of the winding in the transformer; and the physical relevance and reliability of defect diagnosis are enhanced.

The invention discloses a data anomaly detection method and device for a low-voltage power distribution network, a medium and equipment, and belongs to the field of anomaly detection. Inputting the data into a preset LSTMAE-GRU knowledge distillation model to carry out anomaly detection, and outputting an anomaly detection result of each time step; the model is obtained by taking normal measurement time sequence data covering load characteristics of multiple courts as a training sample, extracting high-dimensional time sequence characteristics based on an initial LSTMAE teacher model, aligning teacher model characteristic distribution through latent variable projection by an initial GRU student model, and combining distillation loss training formed by KL divergence and mean square error. The problem that the abnormal data of the low-voltage power distribution network cannot be accurately and efficiently detected in the prior art is effectively solved.

The invention relates to a low-voltage transformer area meter box burning loss fault detection method and system, and the method comprises the following steps: obtaining the time sequence data of a low-voltage meter box, detecting an abnormal behavior through a trained PidanGAE-U model, recognizing the state of the low-voltage transformer area meter box, and generating a preliminary risk assessment result; obtaining multi-dimensional historical and real-time data, carrying out classification division and preliminary evaluation on the identified faults, and constructing a risk factor evaluation system; and based on a risk factor evaluation system, carrying out risk factor correction on a preliminary risk evaluation result, introducing a comprehensive weight evaluation algorithm to carry out quantitative calculation on the influence degree of each corrected factor, and finally generating a risk level of the burning loss fault. Potential faults can be identified and positioned in advance, and the stability of a power system and the power utilization safety of a user are ensured.

The invention discloses a controllable current-limiting reactance protection device, a control method, electronic equipment and a medium. Relates to the field of transformers, and solves the problem of low speed of current-limiting protection of an energy storage type distribution transformer. The working state of a power grid circuit is monitored in real time, on and off of a switch tube are rapidly controlled, and the impedance of an access circuit is adjusted, so that the rise rate and the first peak value of fault current can be greatly reduced, an energy storage system and a distribution transformer are prevented from being damaged, and due to the fact that the switching speed of the switch tube is far higher than that of a mechanical switch, the reliability is high. Moreover, fault signals do not need to be analyzed and processed, connection and disconnection of a switching tube are directly controlled, the fault processing speed is also improved, effective current-limiting protection is provided for the energy storage type distribution transformer within a short time when the fault occurs, the current-limiting protection is not affected by operation delay, and the service life of the energy storage type distribution transformer is prolonged. The reliability and the stability of the energy storage type distribution transformer in a micro-grid environment are remarkably improved, and a powerful guarantee is provided for safe and stable operation of a power system.