1313 results about "Feeder line" patented technology

The invention discloses a power distribution network feeder terminal FTU intelligent monitoring method based on artificial intelligence. The method comprises the following steps that multi-dimensional operation parameter data of a power distribution network feeder terminal FTU are collected in real time through multiple sensors; carrying out dynamic preprocessing on the multi-dimensional operation parameter data to generate a standardized feature matrix, and matching the dimension of the standardized feature matrix with a preset multi-modal deep learning model input layer; inputting the standardized feature matrix into a pre-trained multi-modal deep learning model to generate a real-time monitoring result; wherein the real-time monitoring result comprises fault probability distribution and an equipment health degree score. Compared with the prior art, the method has the following advantages and effects that the data processing precision can be improved, and fault prediction and equipment health assessment can be optimized through the multi-modal deep learning model, so that more intelligent management of the power distribution network is realized.

The invention discloses a distributed power supply access-oriented power distribution network fault distance measurement method and system, and relates to the technical field of power systems, and the method comprises the steps: collecting the electrical parameters and operation states of distributed power supply access nodes in a power distribution network in real time, building a dynamic manifold model based on an ecological niche theory, and carrying out the calculation of the dynamic manifold model; adaptively adjusting manifold learning neighborhood parameters according to power fluctuation data included in the electrical parameters, and updating node ecological niches to reconstruct a dynamic manifold model; based on the reconstructed dynamic manifold model, fault features are extracted from three scales of a current harmonic component, a feed line inter-harmonic propagation path and whole network voltage influence, and a three-dimensional feature vector is generated through fusion of a graph correlation algorithm; based on the expanded fault sample library and the power fluctuation data, constructing a fault transfer relation model to predict a ground fault and a short circuit risk area; a fault source is modeled by adopting a topological neural network, and a fault point distance measurement value is output through state prediction and strategy deduction.

The invention provides a feeder terminal fault detection method, system and device, a medium and a program product, and the method comprises the steps: obtaining multi-source heterogeneous data comprising feeder terminal operation data, a topological graph structure of a power distribution network and external sensing data, the multi-source heterogeneous data comprises at least one kind of structured or unstructured time sequence data, and the external sensing data comprises at least one kind of structured or unstructured time sequence data; the external sensing data comprises meteorological data, geographic space information and historical fault records; and preprocessing the multi-source heterogeneous data, inputting the preprocessed time-aligned multi-source heterogeneous data into the trained time-space diagram neural network model to extract features and perform joint modeling, and outputting a fault type classification result and a fault probability distribution result corresponding to each feeder terminal node in the power distribution network. According to the method, a multi-source heterogeneous data fusion and time-space diagram neural network modeling mechanism is introduced, so that the model has a dynamic response capability to complex environment changes, and the identification precision of a potential fault mode is effectively enhanced.

A method, system, and readable storage medium for fault line selection in distribution networks is provided. The method includes: obtaining the zero-sequence current of each feeder and the zero-sequence voltage of the busbar within a preset time window after a fault occurs; using these to process the feeder's short-time window zero-sequence instantaneous power curve cluster in the distribution network through KPCA (Kernel Principal Component Analysis) for dimensionality reduction, determining the principal component scores; and performing BIRCH (Balanced Iterative Reducing and Clustering using Hierarchies) clustering based on these scores to identify whether a feeder is faulted. This clustering process allows for precise and rapid identification of the faulted feeder, even when the current is small, improving detection accuracy. This solves the problem of quickly identifying the faulted feeder in a small current grounding distribution network during single-phase grounding faults.

The invention discloses a high-low voltage switch cabinet feeder fault positioning method and system based on transient traveling waves, and belongs to the technical field of power system fault detection and positioning, and the method comprises the steps: synchronously collecting electric and acoustic multi-mode signals, and generating a weighted transient synchronization feature matrix; performing time-frequency transformation and feedback optimization on the matrix, and outputting a multi-scale time-frequency feature set; analyzing the feature set by using an integrated learning network, and outputting a layered preliminary positioning result; convergence to an accurate fault section is carried out through iteration calibration; and finally, fusing multi-model calculation and outputting a comprehensive fault positioning report. According to the method, a technical path of combining multi-modal signal fusion and a physical model is adopted, convergence from fuzzy region division to an accurate position can be realized in stages, and the accuracy, the speed and the anti-interference capability of switch cabinet feeder line fault positioning are remarkably improved.

The invention relates to the technical field of voltage control, in particular to a synchronous main shift gear automatic compensation voltage control system, which comprises an area load information acquisition module, a voltage instantaneous value and a current instantaneous value are periodically read through a voltage transformer and a current transformer which are deployed on a key feeder line or a user side in a specified area, and the voltage instantaneous value and the current instantaneous value are acquired; and calculating to obtain an active power value and a reactive power value, adding a synchronous timestamp and a node position code to each collected value, transmitting and collecting the coded voltage value, active power value, reactive power value and timestamp information, organizing and storing according to a regional and time sequence, and establishing a regional load real-time measurement data set. According to the method, real-time capturing and structured processing of the system call number, the parameter and the return value are carried out on the L4T kernel event triggered by the target process PID, a serialized system call track is obtained, and an execution process recording path mainly driven by process behaviors is formed.

The invention discloses a micro-grid dispatching optimization method and system based on multi-modal information, and relates to the technical field of micro-grid dispatching optimization systems. The method comprises the following steps: performing space-time alignment on power data, energy storage charge state data and power grid operation data to generate a space-time associated multi-modal state matrix; solving the multi-target dynamic optimization model according to the multi-modal state matrix to obtain a hierarchical control instruction and an energy storage charging and discharging plan; decomposing the hierarchical control instruction to obtain and execute a substation-level global optimization task, a feeder-level power mutual aid task and a court-level in-situ balance task of a prediction time domain; correcting the energy storage charging and discharging plan in a short period, or updating the load priority list in a long period to obtain an execution result; and updating the data acquisition rule according to the execution result, and restarting data acquisition according to the updated data acquisition rule. According to the invention, the operation performance of the micro-grid can be improved.

The invention relates to a source-containing power distribution network multi-target collaborative voltage optimization control method based on an FACMAC algorithm, and belongs to the technical field of photovoltaic inversion control. According to the technical scheme, a power distribution network physical system is composed of a plurality of feeder lines, a transformer, a line and a plurality of grid-connected photovoltaic inverters, and each inverter can measure operation information such as local voltage and current in real time; the data acquisition and communication system is used for acquiring node operation data and realizing low-delay communication; the multi-agent reinforcement learning control system is composed of a plurality of distributed agents and factorization centralized Critic modules, and whole-network voltage optimization decision can be carried out in training and execution stages. And the execution unit adjusts the reactive power output of the inverter in real time according to the control instruction. According to the method, the whole-network cooperative regulation and control capability is improved, the training efficiency bottleneck in a high-dimensional scene is relieved, the expression capability on a complex nonlinear coupling relationship is enhanced, and efficient, stable and extensible power distribution network voltage optimization control is realized.

The invention provides a circuit breaker action coil current characteristic diagnosis and analysis system and method. Belongs to the technical field of power system automation and substation state monitoring. The method comprises the following steps: carrying out synchronous wave recording on current of a plurality of circuit breaker actuating coils on a direct current feeder screen side to generate multi-channel synchronous wave recording data; meanwhile, SOE message information is collected, a circuit breaker with specific action is automatically matched and positioned by utilizing a timestamp and action identification information in an SOE message, and action circuit breaker positioning data is generated; the current waveform data of the circuit breaker actuating coil are collected in real time, and a high-precision algorithm is used for feature extraction and analysis, so that abnormal fluctuation in current change can be accurately captured, such as overlarge starting current and unstable holding current, the risk of misoperation or rejection of operation of the circuit breaker caused by abnormal current characteristics is reduced, and the service life of the circuit breaker is prolonged. Electric power system accidents caused by equipment faults are avoided, and the operation reliability of the circuit breaker is improved.

The invention relates to the technical field of electric energy conversion control, and discloses a multi-source load auxiliary power supply power balance control system, which comprises a sampling module, a control module and a modulation module, the sampling module obtains parallel converter branch current and direct current bus voltage; the control module determines a weight by utilizing physical associated association of a bus voltage change gradient and branch current change polarity, corrects a dynamic slope factor determined by a current change rate according to the weight, and performs upper limit clamping on the dynamic slope factor according to a bus voltage margin; according to the invention, the rigid restriction of droop control logic is eliminated, the power deviation generated by asymmetry of feeder impedance is automatically offset while the bus voltage stabilization precision is maintained, and the convergence speed and the certainty of the system during violent load switching are improved.

A method may include receiving, by a wireless device, a system information block (SIB) comprising a first non-terrestrial network (NTN) configuration comprising a first value for a validity timer of a cell, a second NTN configuration comprising a second value for the validity timer of the cell, and a third NTN configuration corresponding to at least one NTN neighbor cell. The method may also include starting, based on the receiving the SIB and for the cell, the validity timer with the first value. The method may further include performing a link switch without changing a physical cell identifier (PCI) of the cell. The link switch can include stopping the validity timer with the first value indicated in the SIB and starting the validity timer with the second value indicated in the SIB.

The invention relates to the technical field of power system fault protection, in particular to a power distribution network distance protection method, system and device considering distributed power supply negative sequence currents, and aims at a medium-voltage power distribution network where a plurality of distributed power supplies are connected in a feeder line T-connection mode. Considering the influence of negative-sequence current output under negative-sequence current control of a distributed power supply in each feeder line on measured impedance, the feeder line with a two-phase short-circuit fault in the power distribution network is identified and positioned through cooperation of additional impedance compensation and distributed power supply negative-sequence reconstruction control, and then a protection device is controlled to cut off the fault feeder line. And implementing distance protection of two-phase short circuit of the power distribution network. The method realizes fault identification and positioning only by depending on locally acquired electrical quantity parameters, does not need to depend on a communication system, considers and ensures autonomy and reliability of distance protection, has the advantages of simple principle, low cost and high reliability, and can adapt to power distribution networks with different fault positions and different distributed power supply access numbers and capacities.

The invention provides a wide-angle scanning dual-circularly-polarized phased-array antenna unit, which belongs to the field of dual-circularly-polarized antennas and comprises a first dielectric layer, a second dielectric layer and a third dielectric layer which are sequentially stacked, the antenna radiator is arranged on the side, away from the second dielectric layer, of the first dielectric layer, the antenna radiator comprises four radiation patches, each radiation patch comprises a metal patch and a loading branch knot, and each metal patch is provided with a slotted structure; the first metal ground layer is clamped between the first dielectric layer and the second dielectric layer, and a cross coupling gap and a first coupling gap and a second coupling gap which are perpendicular to each other are formed in the first metal ground layer; the U-shaped feeder line is clamped between the second dielectric layer and the third dielectric layer, and two ends of the U-shaped feeder line are respectively connected with a coaxial feed column penetrating through the third dielectric layer; the second metal ground layer is arranged on the side, away from the second dielectric layer, of the third dielectric layer; an array is also provided; the problem that a traditional circularly polarized antenna is narrow in impedance bandwidth and limited in polarization is solved.

The invention relates to a distribution line fault section positioning method and device, equipment, a medium and a product. The method comprises the following steps: acquiring voltage and current data acquired by each feeder terminal unit of a fault distribution line in a preset time period; performing differential processing on the voltage and current data to obtain a fault component of voltage and current, and performing optimal phase-mode transformation processing on the fault component to obtain a line-mode component of the fault component; calculating a forward traveling wave and a backward traveling wave of the linear mode component; and determining a fault area of the fault distribution line and a fault section in the fault area according to the front traveling wave and the reverse traveling wave corresponding to each feeder terminal unit. According to the invention, the fault positioning precision can be improved.

The invention relates to the technical field of power distribution network self-healing, and discloses a power distribution network fault self-healing method, system and device based on an intelligent distributed feeder line and a medium. According to the method, distributed feeder terminals installed at nodes of a power distribution network are used for information interaction, a fault type and a fault section are determined based on an information interaction result, a self-healing strategy is executed, and multi-node cooperative positioning and accurate isolation are achieved; if the communication is interrupted, the predicted load value of the current node is calculated based on the historical load data, and the power-off threshold value is dynamically adjusted based on the predicted load value, so that the fault isolation requirement under the complex working condition is effectively met, and the self-healing reliability of the power distribution network in different operation environments is remarkably improved.

The invention relates to the technical field of power systems, and discloses a power distribution network fault positioning method, device and equipment and a medium, and the method comprises the steps: synchronously collecting fault traveling wave data through a transformer area intelligent terminal and a feeder terminal disposed in a power distribution network; dynamically calculating traveling wave transmission parameters based on the topological information and the real-time operation parameters of the power distribution network; performing feature extraction and fusion processing on fault traveling wave data acquired by the transformer area intelligent terminal and the feeder terminal to generate a joint feature matrix; based on the joint feature matrix and the traveling wave transmission parameters, cooperative verification is carried out through the single-end positioning information and the double-end positioning information, and a fault section is determined; and performing fault type identification on the fault section by using the intelligent classification model, and performing consistency verification according to an obtained fault type identification result and the fault section to generate a fault diagnosis result. According to the invention, accurate positioning of the power distribution network fault can be realized, and the problems of positioning blind areas, high cost and easy misjudgment in the prior art are solved.

The invention relates to the technical field of power distribution automation operation and maintenance, in particular to a power distribution automation operation and maintenance method based on electric power big data. The method comprises the following steps: collecting and processing power distribution operation data, calling a fault feature rule set to analyze the power distribution operation data, and identifying and detecting a power distribution fault event; based on the electrical topological structure, the protection action information and the power distribution node on-off state of the current power distribution network, a fault feeder line and a fault section are identified, a switching value logic relation and a topological accessibility model are used for power distribution positioning of a fault event area, and a fault diagnosis result data set is output; and generating a fault isolation operation and maintenance strategy and an overhaul task priority list by using an operation and maintenance scheduling model based on the fault diagnosis result data set and the load transfer capacity, the field operation capacity and the historical overhaul resource distribution information of the power distribution station. According to the method, fault diagnosis and an intelligent scheduling mechanism are fused, and the fault response speed and the operation and maintenance cooperation efficiency of the power distribution system under complex working conditions are improved.

The invention discloses a power distribution network feeder line self-healing online dynamic simulation test method and device and a computer program product, and the method comprises the steps: generating a self-adaptive topology recognition and fault self-healing scheme based on the on-site test characteristics of a power distribution network feeder line self-healing protection function; constructing a power distribution network feeder line self-healing model by combining the self-adaptive topology identification and fault self-healing scheme with the goal of meeting the requirements of recovering load power, isolating load and path loss; key parameters of a northern eagle optimization NGO algorithm are optimized by adopting chaos initialization and an elite individual learning strategy; and analyzing the self-healing model of the feeder line of the power distribution network by using an improved NGO algorithm, simulating the operation process of the whole feeder line group under different fault conditions on a dynamic model test platform, and outputting an optimized self-healing processing strategy. According to the invention, the stability, reliability and operation efficiency of the power distribution network are significantly improved, and an efficient and intelligent self-healing control solution is provided for a complex and changeable power distribution network environment.

The invention relates to the field of power distribution system simulation, in particular to a power distribution and micro-grid coordination wide-area balance regulation and control method and system in a multi-micro-grid access scene, and the method comprises the steps: carrying out the cluster division of a plurality of micro-grids based on the electrical coupling degree and net power between the micro-grids; using a pre-constructed multi-energy coupling source load prediction model to cluster resources of an area where the micro-grid is located, and performing load prediction on the divided clusters based on the clustered resources to obtain a group composed of the clusters, the resources and corresponding loads; based on the group, a target cascade method is adopted to solve a pre-constructed zone area or micro-grid layer optimization model, a feeder line level optimization model and a region layer optimization model to realize dispatching optimization of the power distribution network and the micro-grid; by constructing the multi-layer optimization model, the power exchange cost, the power generation cost and the environment cost between the micro-grid and the power distribution network can be optimized, and economic operation of the system is achieved.

The invention relates to the technical field of power network space optimization management, and particularly discloses a power network space optimization analysis method and system based on a power grid GIS, and the method comprises the steps: firstly enabling a power grid GIS port to firstly match the space coordinates of a high-voltage side bus of a power transmission substation and a power distribution feeder starting node, building an electrical connection topology after verification, and evaluating a capacity coupling factor; dividing feeder segments according to topology, calculating a loss rate and a risk index, and correcting the risk index in combination with a capacity coupling factor, thereby realizing accurate quantification of the feeder state and improving risk assessment scientificity; secondly, feature vectors are constructed according to the GIS center points, the loss rates and the risk indexes of the feeder line sections for clustering, GIS layers with labels are output, feeder line clusters in the same state can be recognized conveniently, and support is provided for regional analysis; and finally, detecting a loop gap based on a layer, analyzing connectivity, identifying a weak link and optimizing feedback, accurately positioning a network short board, and providing a targeted reference for an optimization scheme.

The invention belongs to the field of power dispatching management, and discloses an intelligent substation energy management method based on cloud computing, which comprises the following steps: constructing a'prediction-dispatching 'game framework; a three-dimensional uncertainty cloud picture with space-time coupling characteristics is generated by fusing regional meteorological data and output correlation of adjacent substations, and an edge layer solves a Nash equilibrium point based on the three-dimensional uncertainty cloud picture to generate a scheduling scheme; performing dynamic electrical partitioning based on the feeder line voltage-power sensitivity matrix to obtain a partitioning result, implanting programmable impedance characteristics in a photovoltaic inverter and an energy storage power conversion system, and performing equipment autonomous response based on a scheduling scheme; the source load fluctuation event chain model carries out cross-time-scale linkage control based on a partitioning result; and updating a scheduling scheme based on an execution result, and adjusting an equipment operation state based on the updated scheduling scheme, thereby realizing intelligent substation energy management based on cloud computing.

The invention discloses a distributed intelligent power distribution method and system for a power network, and belongs to the technical field of power distribution control, and the method comprises the steps: collecting multi-dimensional electrical parameters of a power generation node in real time, and carrying out the dynamic power monitoring at a feeder terminal of a transformer substation through an edge calculation node; executing line loss calculation and load prediction in the power distribution unit, generating a demand feedback instruction to a feeder terminal node, and triggering an adaptive power distribution strategy; and on the basis of a digital twin system of a regional dispatching center, credibility verification is carried out on operation decisions of all edge nodes, and global optimization compensation control is executed. The method has the remarkable advantages in the aspects of optimizing power distribution, reducing line loss, improving system stability and safety and achieving efficient energy utilization, and intelligent management of a power network becomes possible.

The invention relates to the technical field of three-dimensional visualization, in particular to a power grid line loss intelligent diagnosis and visualization method based on multi-source data acquisition, and the method comprises the steps: obtaining a sensor data grouping sequence, detecting power fluctuation synchronism, extracting a change trend, analyzing a power difference and a node trend, marking an abnormal path, generating a line loss map, and positioning an abnormal node coordinate level. And mapping the topological graph to adjust the style, and generating a visual layer result. According to the invention, through obtaining the multi-dimensional data of the feeder line and performing efficient analysis, capturing power fluctuation and abnormity, identifying abnormal nodes in combination with the power difference of adjacent nodes, analyzing the fluctuation rate to reveal the line loss area and the structure abnormity, calibrating the abnormal position by using the three-dimensional coordinate, realizing spatial positioning and risk assessment, and clearly displaying the operation state by the three-dimensional layer. The monitoring accuracy is improved, path connection and node positioning help to quickly identify a high-risk area, the operation and maintenance efficiency and the diagnosis comprehensiveness are optimized, and a precise basis is provided for power grid management.

Computational algorithms or “solvers” may be executed on intelligent electronic devices (IEDs) in an electric power delivery system to perform tasks such as locating and isolating electrical faults and restoring service to an area after an electrical fault occurs. However, executing the solvers may become a computationally prohibitive task, particularly where computing power is limited (e.g., low-power pole-top computers). In certain embodiments, computing power may be offloaded onto multi-instance networks that may enable processing of large amounts of complex data. It may be difficult for the multi-instance networks to obtain real-time or near real-time data from the electric power delivery system due to cybersecurity concerns. As such, multiple stateless services may be used to evaluate limited and / or obfuscated representations of a portion (e.g., a single feeder circuit) of the electric power delivery system.

An antenna device and a radar wherein the antenna device comprises a decoupling network and at least two antenna units. Each antenna unit comprises a radiating body and a feeder line, one end of the feeder line is connected with the radiating body, and the feeder line is used for feeding a radio frequency signal into the radiating body; and a preset distance is formed between the feeder lines of two adjacent antenna units. The decoupling network is arranged between the feeder lines of the two adjacent antenna units and is in indirect coupling connection with the feeder lines, and the decoupling network is used for enabling the phases of currents transmitted to the decoupling network from the feeder lines of the two adjacent antenna units to be opposite. According to the invention, the decoupling network is arranged, so that the coupling current generated by the feeder lines of the two adjacent antenna units can be introduced into the decoupling network, and two paths of coupling current from different feeder lines can be offset on the decoupling network, thereby achieving the purpose of decoupling. Meanwhile, by arranging the decoupling network, decoupling of the two adjacent antenna units with the distance smaller than 0.5 lambda can be achieved, and the isolation degree of the high-density array antenna is improved.

The invention provides a power distribution network fault section rapid calibration method based on a feeder terminal. According to the method, power distribution network line electrical quantity and distributed power supply output information are collected in real time through a feeder terminal and preprocessed, then fault transient signals are processed through complete set empirical mode decomposition of mean value self-adaptive noise, and intrinsic mode components are obtained to judge fault types. Thirdly, fault section preliminary positioning is carried out, and an approximate area is determined according to a positive sequence voltage vector for a symmetric short-circuit fault, a negative sequence voltage vector for an asymmetric short-circuit fault and a zero sequence current amplitude for a single-phase earth fault; then accurate calibration is carried out, a single-phase earth fault is judged through a filter and correlation coefficients, and short circuit and broken line faults are calibrated through a model or an intelligent algorithm in combination with line topology and electrical parameters. And finally, establishing a target function containing a penalty term, converting the target function into a Markov decision process, solving through an approximate dynamic programming algorithm, realizing rapid and accurate calibration of a fault section, and improving the power supply reliability of the power distribution network.

The invention relates to the technical field of arc fault detection, and discloses a method and device for detecting an arc fault in a switch cabinet, and the method comprises the steps: collecting a three-phase current signal of each feeder loop in the switch cabinet, and obtaining target current data through preprocessing; decomposing the target current data to obtain a plurality of current mode components, and performing clustering reconstruction on the plurality of current mode components to obtain an arc feature set; and inputting the arc characteristic set into the time sequence convolutional network embedded with the Mayr arc physical model to carry out fault identification, and obtaining a fault identification result, the Mayr arc physical model is embedded into the time sequence convolutional network, the arc fault detection accuracy is improved, the full-process automatic response from early warning monitoring to emergency isolation is realized, and the fault identification efficiency is improved. A protection action can be completed before a series arc fault evolves into a serious inter-phase short circuit, and the real-time protection capability of the switch cabinet is improved.

The invention discloses a power distribution network resonance grounding system high-resistance fault detection method and device and a medium. The method comprises the following steps: extracting fault features from zero-sequence current of each feeder line based on a multi-modal feature algorithm; obtaining correlation coefficients, feature kurtosis and feature energy based on the fault features; based on the correlation coefficient, the feature kurtosis and the feature energy, constructing three fault detection criteria; and formulating a comprehensive voting mechanism based on the three fault detection criteria, and obtaining a diagnosis result according to the comprehensive voting mechanism. According to the method, the comprehensive voting mechanism is formulated through three fault detection criteria, and the diagnosis result is obtained according to the comprehensive voting mechanism, so that the situation that misjudgment is easily caused by a single criterion is avoided, and the diagnosis result is more accurate; fault features are extracted from zero-sequence currents of all feeder lines through a multi-mode feature algorithm, and the problems that when a high-resistance fault occurs in the resonance grounding power distribution network, the fault features are weak, and complex and changeable working conditions are difficult to adapt are effectively solved.

The invention provides an NTN feeder line link time delay parameter determination method and device, a base station and a storage medium, and the method comprises the steps: solving satellite-ground distances corresponding to a plurality of sample moments of a detection time period according to ephemeris information and epoch time corresponding to the detection time period by the base station; according to the method, the fitting coefficient of the distance time function corresponding to the detection time period is determined by performing curve fitting on the satellite-ground distance, and the public time delay parameter is determined according to the fitting coefficient, so that the accuracy and the efficiency of determining the public time delay parameter are improved; therefore, the user terminal can accurately estimate the public time delay of the feeder line link according to the public time delay parameter and perform corresponding timing compensation, signal synchronization is ensured, and the technical problem that the base station cannot accurately determine the public time delay parameter in the prior art is solved. In addition, the variation trend of the satellite-to-ground distance in a long time period can be determined according to the calculation of fewer sample points, and the accuracy of time delay evaluation is ensured with lower operation overhead.

The invention discloses a distributed power supply-containing power distribution network self-healing method and system based on defect identification, and the method comprises the steps: inputting operation data into a defect identification model, obtaining a defect identification result, correcting a feeder load rate and a weighted structure entropy according to the defect identification result to generate a candidate solution set, inputting the candidate solution set into an upper layer optimization model, and obtaining a defect identification result; taking the maximization of the load recovery amount in the island as a target, combining with a line medium to guide a search direction and adopting a second-order cone relaxation method to carry out optimization solution to obtain a load recovery scheme in the island, and inputting the candidate solution set and the load recovery scheme into a lower-layer optimization model to obtain a load recovery scheme in the island; carrying out iterative solution under a constraint condition by combining an improved star-sparrow optimization algorithm which introduces an inertia weight and a learning factor, and obtaining a load recovery result after fault reconstruction; and determining a target switch operation sequence and a load recovery strategy based on the load recovery result to perform self-healing of the power distribution network so as to improve the self-healing capability and the operation reliability of the power distribution network.