316 results about "Topology identification" patented technology

The invention discloses an equipment management system and a server, and relates to the technical field of servers, and the equipment management system is characterized in that a topology identifier storage assembly for storing slot position signal source identifiers is moved to a server mainboard end, so that the occupation of mainboard connector pins by information transmission is reduced; and meanwhile, the management control component establishes and stores a corresponding relation between the address of the arbitration component and the screen printing area of the case. The adapter card does not need to be pre-bound and configured, can automatically identify the screen printing area of the case through the relationship by inserting any communication interface of the mainboard, and generates slot screen printing information in combination with the pre-stored signal source identifier. The problems that a large number of pins are occupied due to the fact that the adapter card hardware address signal identification configuration needs to be transmitted through a connector, and the adapter card needs to be bound with the fixed configuration and lacks flexibility in the prior art are solved. The technical effects of reducing pin occupation, realizing flexible plugging of the adapter card and automatic identification of screen printing, reducing hardware development cost and meeting the requirement of the server for reserving more bus interfaces for the connector are achieved.

The invention discloses a power distribution area line topology identification method and system based on an embedded system. The method comprises the following steps: acquiring and preprocessing electrical operation data and equipment state data in a power distribution area line; constructing a graph neural network model based on the preprocessed electrical operation data, and constructing a static graph structure in combination with the preprocessed equipment state data to train the graph neural network model; monitoring the real-time load change degree of the distribution line, and judging whether to trigger a dynamic update mechanism based on the load change degree, including dynamically updating the parameters of the static graph structure according to the load change degree to obtain an optimized model; and obtaining a topology recognition result according to the optimized graph neural network model, and regularly evaluating and optimizing the topology recognition result. The dynamic updating mechanism is triggered by monitoring the load change in real time, and the model can be adjusted in real time according to the actual operation condition of the power distribution area, so that the topology identification can accurately reflect the real-time state of the power distribution area.

The invention discloses a metering processing method for an electric energy meter topology application and an electric energy meter of a transformer area topology. The metering processing method comprises the following steps: S1, constructing a measurement data set based on an equipment identifier, a power factor and a sampling timestamp of the electric energy meter; s2, generating an initial graph model containing user nodes and electric energy transmission edges based on the data set; s3, inputting a dynamic coupling backflow enhancement graph diffusion network to execute topology identification; s4, constructing a fusion path diagram and initializing an edge weight; s5, calculating an edge weight regulation factor, and updating the edge weight; s6, asynchronous propagation is carried out to output a transformer area power supply topological graph; s7, constructing a metering path based on the topological graph and identifying an abnormal path segment; and S8, correcting the abnormal path, and generating an optimization topology and evaluation report. According to the method, the precise identification of the power supply topology of the transformer area and the self-adaptive correction of the abnormal metering path are realized.

The invention discloses a power distribution area topology identification method and system based on an intelligent fusion terminal and correlation coefficients, and the method comprises the steps: collecting the multi-source data of a power distribution area through an edge fusion terminal, and carrying out the data preprocessing and feature extraction at a terminal side; carrying out parallel calculation on a voltage fluctuation Pearson's correlation coefficient and a load change Kendall rank correlation coefficient, and constructing a correlation coefficient matrix in different time periods; calculating an adaptive weight based on the load fluctuation entropy, and fusing a dual-mode correlation coefficient; carrying out topology generation by using a graph neural network, and outputting an edge existence probability and a node hierarchy; performing physical constraint optimization on the initial topology by adopting a genetic algorithm; the system comprises an edge fusion terminal cluster, a cloud analysis platform, a topology verification module and a terminal management platform. According to the method, topology recognition precision and dynamic adaptability are remarkably improved, bimodal correlation coefficients and graph neural network space modeling are creatively fused, and a complex topological structure is precisely restored.

The invention relates to the technical field of power system power distribution network fault detection, in particular to an arc fault diagnosis and analysis method based on an artificial intelligence algorithm, and the method comprises the four steps: synchronous data collection and topological excitation, deployment of terminals at transformer area nodes, injection of characteristic current, and synchronous collection of response waveforms; signal preprocessing: separating a key frequency band through double-digital band-pass filtering, and calculating energy ratio and other enhanced fault features; performing multi-source feature fusion and intelligent diagnosis, constructing a vector containing statistical features, time domain distortion features and topology identification, and inputting a gradient boosting decision tree and deep neural network hybrid model to obtain fault confidence and type; and based on fault positioning and verification of topology, scheduling multi-node cooperative monitoring, and determining a fault point in combination with a topological relation. The method improves the data reliability and diagnosis precision, achieves the precise positioning of a fault, and guarantees the safe operation of a power distribution network.

The invention relates to a transformer area topology identification method and device based on a carrier communication network, and a concentrator. The method comprises the following steps: determining electric energy meter nodes in the same phase line and the same court and electric energy meter nodes in a cluster unit of the lowest level in a plurality of cluster units; performing hierarchical identification on the plurality of cluster units by adopting a carrier communication network to obtain hierarchies of the plurality of cluster units; according to the electric quantity data sent by the monitoring device corresponding to each branch box cluster unit in the plurality of cluster units and the electric quantity data sent by the monitoring devices corresponding to the superior power distribution room unit and the subordinate plurality of meter box units of each branch box cluster unit, determining an outgoing line and incoming line corresponding relation of the branch box cluster units in the plurality of cluster units, and forming a transformer area topological graph. By adopting the method, the transformer area topology identification can be carried out based on the carrier communication network, so that the situation that signal receiving devices are additionally arranged on branch boxes and electric meter boxes in a power distribution network is avoided, and the cost of transformer area topology identification is further reduced.

The invention discloses a distribution network dynamic topology identification and self-healing control method and device, and the method comprises the steps: collecting operation data of a distribution network, carrying out the time synchronization processing, data quality evaluation and data restoration, and obtaining a high-quality network state data set; based on the data set, performing dynamic topology identification by adopting a path improved by a relaxation method and a forest enhancement algorithm to obtain a dynamic network topology model; constructing a backpack network model by adopting a cyclic data generation method, and evaluating distributed photovoltaic output and load conditions; network abnormity is monitored in real time, and a machine learning algorithm is adopted to assist in judging fault types, positions and influence ranges; power supply reliability and economy are comprehensively considered, and a multi-objective optimization algorithm is adopted to generate a switch operation sequence; switching operation is executed, a temporary micro-grid is formed or a power supply path is adjusted, and the execution effect is monitored and evaluated in real time. According to the method, the dynamic topology of the high-proportion distributed photovoltaic power distribution network can be accurately identified, and fault positioning and efficient self-healing control are realized.

The invention discloses a graph contrast learning identification method for the low-voltage transformer area topology of a power distribution network. The method comprises the following steps: data acquisition and standardization; constructing a feature extraction module; constructing a time sequence encoder, a voltage correlation module, a time alignment module and a power mode module; semi-supervision and measurement combined training: carrying out graph contrast learning based on attributes, and carrying out supervision training on transformer attribution and meter box attribution by adopting cross entropy loss; and topology identification and reasoning output: inputting time sequence data of a user and a transformer under the condition of zero sample of a new transformer area, and outputting a user-transformer attribution probability and a meter box attribution probability through a feature extraction and classifier. According to the method, physical interpretable features such as voltage correlation and time alignment are introduced and are combined with time sequence coding and metric learning, so that the accuracy and stability of topology identification of the low-voltage transformer area are remarkably improved under the condition of small samples.

The invention relates to the technical field of power distribution network bidirectional power flow coordination control, and discloses a power distribution network bidirectional power flow coordination control method based on V2G aggregation, and the method comprises the following steps: S1, constructing a logic energy storage unit composed of a plurality of V2G charging piles and vehicles supporting reverse discharge; s2, aggregating the logic energy storage units into virtual power plant nodes which can be dispatched by a power grid through an information communication technology (ICT); and S3, bidirectional power flow sensing and real-time state estimation: utilizing an intelligent electric meter, a sensor and a topology identification algorithm. According to the method, a logic energy storage unit composed of a plurality of V2G charging piles and vehicles supporting reverse discharging is constructed, the logic energy storage unit is aggregated into a virtual power plant node capable of being dispatched by a power grid through an information communication technology (ICT), and specific charging and discharging actions are decomposed and executed, so that dispersed V2G resources can be effectively integrated, and the V2G resources can be effectively integrated. And collaborative optimization with operation states such as voltage and power flow of the power distribution network is carried out.

The invention relates to the technical field of power distribution networks, in particular to a low-voltage transformer area topology recognition method and system adopting a graph diffusion model, equipment and a medium, and the method mainly comprises the steps that a topology recognition model is established, target time sequence characteristics are input into the topology recognition model, and the target time sequence characteristics are input into the low-voltage transformer area topology recognition model. And implicitly identifying node pairs with synchronous fluctuation through a topology identification model, outputting node features fusing neighbor information, predicting a connection probability between nodes based on the node features, and outputting a new transformer area topology structure. Different from a traditional method which depends on a specific transformer area rule or needs a large amount of manual adjustment, the graph neural network trained by the scheme aims at learning a general electrical characteristic-topological structure mapping rule and denoising logic. The model is not limited to a specific structure of training data, can be effectively generalized and applied to new courts with large topological structure differences, and solves the problems that a traditional method is poor in adaptability and weak in expansibility.

The invention discloses a transformer area topology identification method and system capable of being deployed in a concentrator, equipment and a medium, and the method comprises the steps: solving an initial virtual impedance matrix based on historical electrical quantity data of a transformer area, and taking the minimum deviation between an optimization result and the initial matrix as an optimization target; and taking symmetry constraint, boundary constraint and collinear constraint as constraint conditions, and performing iterative solution to obtain an optimized virtual impedance matrix, so that the optimized virtual impedance matrix is closest to an original matrix on the basis of conforming to the actual topology, noise interference can be eliminated, the topology identification precision is improved, the method can dynamically adapt to a transformer area change scene, and the method is suitable for being applied to a transformer area. The method has high robustness, the unstructured virtual impedance matrix can be fitted into a unique solution conforming to physical topology, fuzziness of a traditional method is avoided, the whole recognition process only depends on historical electrical quantity data of the transformer area, no initial topology information is needed, and the high-precision transformer area topology can be constructed from zero.

The invention discloses a structure three-dimensional displacement monitoring method and device based on a monocular camera and a concentric annulus, and relates to the field of computer vision and structure health monitoring, a concentric annulus target is fixed at a to-be-monitored structure monitoring point, and the monocular camera carries out positioning and lens parameter adjustment; shooting a checkerboard image and calibrating the checkerboard image by adopting a camera calibration algorithm to obtain a distortion parameter and an internal reference matrix; collecting a video sequence containing a structure displacement process of the target; image distortion correction is carried out based on the distortion parameters and the internal reference matrix, a target is identified through a target detection algorithm, and target parameters are calculated through least square circle fitting; realizing multi-target tracking by a target point topology identification algorithm based on Y-X threshold sorting; calculating scale factors according to target parameters and actual physical sizes, and calculating in-plane orthogonal direction displacement and out-of-plane displacement to form three-dimensional displacement information of the structure; according to the invention, the monocular camera is adopted to realize the accurate measurement of the three-dimensional displacement of the structure and reduce the complexity and calibration difficulty of the system.

The invention discloses a bidirectional reversible conversion method and system between a peptide molecule SMILES and a sequence expression. The core innovation lies in that a new sequence description syntax is defined to retain information of a polypeptide special bond and specific modification of amino acid; a main chain atom index and adjacency traversal topology identification algorithm is adopted, and end group and topology integrated detection and coding are carried out; a residue recognition algorithm for main chain cutting and template library matching is compatible with any standard or non-standard amino acid residues, an extensible end group library / monomer template library and an automatic increment mechanism, and automatic recognition and sequence annotation of S-S disulfide bonds; the invention relates to a high-fidelity assembly algorithm of HELM anchor points and topology aware cyclic peptide processing. The method solves the problems of incapability of supporting a complex polypeptide topological structure, poor reversibility, insufficient expansibility of a monomer library and the like in the prior art, can be widely applied to scenes of quantitative structure-activity relationship model construction, large-scale polypeptide data cleaning and the like, and has remarkable practicability and innovativeness.

The invention discloses a topology identification method based on intelligent measurement data of a low-voltage transformer area. According to the technical scheme, the topology identification method comprises the steps that 1, a master station issues a timing command to an intelligent measurement terminal and an electric meter; step 2, the master station issues a transformer area electric meter file to the intelligent measurement terminal, configures an acquisition task and issues the acquisition task to the intelligent measurement terminal; step 3, establishing an electric quantity sum linear regression model based on a Lasso algorithm by using daily frozen electric quantity data, and converting the identification problem of the transformer area user-transformer relation into regression coefficient solving; step 4, on the basis of user change relation identification, performing dimension reduction on historical voltage data by using a t-SNE algorithm to improve the identification efficiency of the model; and step 5, clustering the voltage data after dimension reduction by using agglomerated hierarchical clustering, identifying a user phase and a meter box to which the user belongs, and completing identification of a topological structure. According to the method, the power grid topology information of the transformer area can be automatically identified, the efficiency and the accuracy of topology identification are improved, and the method has far-reaching significance for construction of an intelligent power grid.

The invention provides a one-master multi-slave type high-speed serial communication and synchronous control method and system and a medium, and the method comprises the steps: firstly, resetting slave stations based on an initialization instruction, and sequentially transmitting equipment type query instructions based on a physical connection sequence, thereby completing the topology recognition of the slave stations; then, aggregated data frames are periodically constructed, a frame header is written into a master station status word, a frame body is formed by splicing slave station data packets according to a station number sequence, and a frame tail is a check code; and finally, the slave station analyzes the aggregated data frame based on the station number, executes the task, and feeds back a task execution result according to a physical inverted sequence. In addition, when a new slave station is accessed, the master station switches a status word and triggers the whole system to be reinitialized, and the new slave station is dynamically incorporated into the topology; according to the invention, the expansibility, the real-time performance and the reliability of multi-node synchronous control in an industrial scene are comprehensively improved.

The invention discloses a low-voltage distribution area topology identification method, system and device and a storage medium, and the method comprises the following steps: deploying a synchronous measurement unit in a low-voltage distribution area, and obtaining the outgoing line current phasor and voltage phasor data with a synchronous time scale of a whole network; constructing an incoming line and outgoing line current phasor set, and performing adaptive descending sorting according to amplitudes; determining that the nodes corresponding to the incoming line current phasors and the found nodes corresponding to the one or more outgoing line current phasors are in a father-son relationship, and iterating the process until all sets are empty, thereby completing the identification of the topological relationship of the power distribution side; and according to the equipment number contained in the obtained voltage phasor data, determining a meter box connected with the user electricity meters, and then clustering the user electricity meters connected to the same meter box according to the voltage phase angle to obtain the connection phase sequence of each user electricity meter. The problem of key information missing is solved from a data source, and accurate and efficient identification of topology is realized by fusing physical constraints.

The invention relates to a low-voltage distribution network topology identification method based on voltage-current correlation feature mining, and the method comprises the steps: carrying out the time synchronization processing of user-side multi-source electric parameter data after obtaining the user-side multi-source electric parameter data, and forming a unified electric parameter data set; after further preprocessing the integrated electric parameter data, extracting a voltage feature sequence based on the preprocessed point parameter data; the method comprises the following steps: establishing a user group, calculating voltage curve similarity among users, establishing a feature matrix and performing clustering analysis to preliminarily identify the user group, then establishing a mixed integer programming model by combining a Kirchhoff's current law, optimizing a phase-line-user relationship, and finally outputting a topological structure result. The problems that the low-voltage power distribution network topological structure is insufficient in recognition precision, poor in data consistency and low in dynamic adaptive capacity are solved, so that efficient and reliable network topology recognition is achieved, and monitoring and fault management of the power distribution network are effectively supported.

The invention is suitable for the technical field of smart power grids, and relates to a low-voltage transformer area undisturbed topology identification method and system, a medium and a terminal, and the method comprises the steps: S10, cleaning and screening original communication and measurement data; s20, the RSSI between the devices is converted into the distance between the nodes, and an undirected weighted graph is formed; s30, determining an affiliation relationship between the meter box and the electric meter by using a clustering algorithm; s40, performing constraint matching on the transformer, the line and the meter box node according to the power utilization information, and optimizing the topological structure by using the law of conservation of energy and the Kirchhoff's current law; and S50, evaluating the accuracy of the identification result by using the adjusted Lam index and the normalized mutual information. The method is simple in process and convenient to operate, a complete topological structure is constructed step by step on the premise of not adding extra hardware, uninterruptible power and not injecting characteristic signals by relying on electric power data of an existing intelligent electric meter, a communication signal and an electricity utilization information acquisition system, and high-precision and automatic identification of the topological structure of the transformer area is achieved.

The invention relates to the technical field of building block toy programming, and discloses an extensible modular building block toy intelligent programming control system and method. A building block topology identification module of the system collects the physical connection state of modular building blocks through a multi-modal sensor, and extracts module identity features, a connection relation matrix and combined configuration parameters; the programming logic conversion engine establishes a mapping rule of the module identity characteristics and the connection relation matrix, and analyzes a correction rule of the combination configuration parameters on the two; the instruction sequence generator constructs an instruction conversion model based on the mapping rule and the correction rule, and generates a target control instruction queue; and the actuating mechanism driver analyzes the instruction queue and outputs a driving control signal matched with the current building block combination. The system can accurately identify the building block combination state, flexibly convert the programming logic, dynamically generate the adaptive instruction and accurately execute the driving action, the expansibility and adaptability of the system are improved, and the use experience of a user is improved.

The invention discloses a topological structure rapid identification method for real-time operation of a power distribution network, and the method comprises the steps: obtaining multi-source measurement data of a plurality of data sources in the power distribution network, and carrying out the preprocessing of the multi-source measurement data, and obtaining effective measurement data; generating a candidate topology set based on the on-off state of the power distribution network switch equipment; performing state estimation on each candidate topology in the candidate topology set to obtain a state estimation value; calculating a topology error between the state estimation value of each candidate topology and the corresponding measurement value in the effective measurement data; and screening out an effective topology from the candidate topology set based on the topology error, and taking the effective topology as the operation topology of the power distribution network at the current moment. According to the scheme of the invention, the accuracy and efficiency of topology identification of the power distribution network are effectively improved.

The invention discloses a line loss analysis method and system based on transformer area topology identification and terminal equipment. The line loss analysis method comprises the steps of obtaining first power data and load data of a plurality of ammeters and second power data of a plurality of transformers in a transformer area; determining a target transformer to which each electricity meter belongs based on the first power data and the second power data, if each electricity meter belongs to the same target transformer, determining a phase group to which each electricity meter belongs based on the first current data and the second voltage data, and determining a branch box group to which each electricity meter belongs based on the first voltage data between the electricity meters, determining an initial topology result based on the target transformer, the phase group and the branch box group; and checking the initial topology result based on the load data to determine a target topology result, and performing line loss analysis based on the target topology result to obtain a transformer area line loss result. According to the invention, the accuracy of topology identification and line loss analysis can be improved.

The invention discloses a radial power distribution network topology identification method, system and device and a medium. The method comprises the following steps: acquiring node voltage amplitude measurement data; calculating a sample covariance matrix based on the voltage amplitude measurement data to obtain the covariance of the voltage amplitude between the nodes; estimating a precision matrix of the covariance matrix through a graph lasso model; calculating a partial correlation matrix based on the precision matrix, wherein the partial correlation matrix is used for representing a direct correlation coefficient between nodes in the radial power distribution network; and deriving an adjacent matrix through a maximum spanning tree based on the partial correlation matrix to obtain a radial power distribution network topological structure. According to the method, sparse learning and partial correlation analysis are combined to deal with the problem of limited data volume; the key condition dependency relationship between the nodes can be quickly and accurately identified only through voltage amplitude measurement data without a large number of samples and phase angle information, and the identification precision is high.

The invention discloses a power distribution network topology identification and fault location method based on multi-dimensional zero-sequence current characteristics, and the method comprises the steps: fusing the transient high-frequency information, steady-state phase and amplitude characteristics of zero-sequence current, and combining the standardized configuration of a zero-sequence current transformer of a ring main unit; and rapid and accurate identification of the single-phase earth fault and accurate inference of the topological structure of the power distribution network when the fault occurs are realized. The invention belongs to the technical field of power distribution networks of power systems, and particularly provides a method for solving the problems of insufficient precision, slow response speed and weak anti-interference capability in single-phase earth fault positioning of a power distribution network.

The invention relates to a distribution network maintenance topology identification system based on multi-source data fusion, and the system achieves the effective integration and precise processing of multi-source power distribution network data through the cooperative work of a multi-source data collection module, a data preprocessing module and a measurement generation module, and remarkably improves the temporal-spatial resolution of the state quantity of a distribution network. According to the method, a confidence evaluation system is constructed, and an algorithm confidence evaluation system is used for carrying out confidence scoring on an output identification structure, so that the uncertainty of an identification result can be quantified, and the availability and reliability of the system in an actual complex environment are greatly improved; through seamless connection and data interaction between a database and a marketing system and a scheduling system, the applicability and effectiveness of the system in an actual maintenance scene are ensured, accurate and reliable topology identification support can be provided for power distribution network maintenance, and the maintenance efficiency and the power supply reliability are improved; the method has the advantages of being high in self-adaption, accurate and reliable.

This invention relates to an automatic identification method and system for the topology of medium- and low-voltage distribution networks, belonging to the technical field of medium- and low-voltage distribution networks. First, it acquires the three-phase power signals and power frequency distortion communication signals of the medium- and low-voltage distribution network equipment; then, it acquires the equipment information of the medium- and low-voltage distribution network; next, it acquires the equipment connection relationship identification rules set by the master station; based on the three-phase power signals and power frequency distortion communication signals, it identifies the connection relationships of each device using the identification rules; finally, it obtains the topology of the medium- and low-voltage distribution network based on the connection relationships and equipment information. This invention utilizes equipment connection relationship identification rules to identify the connection relationships of equipment, thereby completing information transmission and achieving the purpose of distribution network topology identification. Because it identifies the topology of the medium- and low-voltage distribution network based on the connection relationships of each line, it eliminates the disadvantage of information not being interconnected, achieves the goal of full network topology identification, and effectively improves the accuracy of topology identification.

The invention discloses a block identification-based low-voltage transformer area topology modeling method and device and a storage medium, and the method comprises the steps: carrying out the correlation analysis of a target voltage time sequence of a branch box and a user based on the target voltage time sequence of the branch box and the user, obtaining the affiliation of the user and the branch box, and completing the preliminary blocking; constructing a data matrix used for branch box-electric meter box topology identification, and based on the target power time sequence of the branch box and the electric meter box, calculating to obtain a relation matrix representing a topological relation between branch box nodes and electric meter box nodes; a data matrix used for electricity meter box-user topology identification is constructed, and a relation matrix representing the topological relation between electricity meter box nodes and user nodes is obtained through calculation based on the power time sequences of electricity meter boxes and users in all branches. According to the method, the power sequences serve as main data, the data matrix is constructed, the linear relation of the power sequences of the adjacent hierarchical nodes is solved integrally, node-by-node similarity comparison is not needed, and the recognition convenience and the calculation efficiency are improved.

The invention discloses a digital power grid power line anti-theft alarm system, which relates to the technical field of electric power safety protection and comprises a coupling feature extraction module, an interference mode analysis module, a cross-modal feature fusion module, a time sequence calibration regulation and control module and a closed-loop dynamic suppression module, the method comprises the following steps: constructing a time-frequency phase-locked observation baseline of a continuous sampling signal, inverting coupling spectrum characteristics of a monitoring link and a communication link by using multi-channel phase reconstruction processing, generating a phase and amplitude residual fingerprint map, and calibrating a sudden change threshold domain as a dynamic reference of topology identification. Through technologies of phase reconstruction, causal replay, multi-modal fusion, time calibration and the like, electromagnetic coupling disturbance is accurately identified and suppressed, effective distinguishing between disturbance and intrusion signals is realized, a closed-loop steady-state control mechanism is constructed, and the accuracy, intelligence and robustness of power grid protection are improved.

The present invention is applicable to the field of smart grid technology and relates to a method for identifying the physical topology of distribution network substations based on G3-PLC communication characteristics, including: S10, constructing a physical topology model of the distribution network substation; S20, determining edge weights in the physical topology model of the distribution network substation; S30, improving the Prim algorithm based on the G3-PLC communication characteristics and constraining the minimum spanning tree (MST) to improve the Prim algorithm process; and S40, identifying the physical topology structure of the distribution network substation. This method has a simple process and is easy to operate. Without adding additional hardware equipment or any manual operation, it constructs a weighted graph using G3-PLC communication data, generates a minimum spanning tree (MST) using the Prim algorithm, and identifies the physical topology structure of the distribution network substation with high identification accuracy.

The invention discloses a distribution network terminal topology identification and distance measurement method and system, and the method comprises the steps: generating a binary tree according to the data of a tower, a switch, a line and the like, determining a reference terminal and an effective terminal according to the wave head moment data after the line breaks down, carrying out the topology identification through employing a binary tree algorithm, positioning a fault section, and carrying out the distance measurement. The method can adapt to topological changes caused by switch position changes, and is small in calculation amount and easy to implement.

The invention relates to the technical field of new energy automobile charging, and discloses a charging pile gun address dynamic allocation method and system based on power topology identification. A host control module, a terminal equipment module, a charging gun access module, a power transmission detection module, a network communication interaction module, an address intelligent distribution module, a fault diagnosis isolation module and a data persistent storage module are established; the host control module is connected with the charging gun access module, the power transmission detection module and other subsequent function modules through power lines, each module is correspondingly connected with a terminal and a charging gun, a system physical power topology and a multi-terminal network communication topology are constructed based on a hardware connection relationship, and the host and the terminal finish power-on initialization respectively. And the host starts an address allocation preparation process, and the terminal starts network initialization and address request preparation, so that a plug-and-play function is realized, the deployment efficiency and operation and maintenance reliability of the charging pile are improved, and finally the problems of low efficiency, easy error and complex after-sales maintenance of traditional manual address configuration are solved.