1207 results about "Electricity distribution systems" patented technology

The invention relates to a power distribution system optimization method considering a space-time game under vehicle-station-network interaction, and the method employs a double-layer optimization framework integrating the space-time game and dynamic electricity price, an upper decision maker is a power distribution system operator, and the power distribution system operation cost is minimized and the renewable energy consumption rate is maximized. Generating a dynamic electricity price signal in a time-sharing and partition manner; the lower-layer main body comprises an electric vehicle user and a charging station operator, and the electric vehicle user optimizes a charging time period and a charging station and forms charging demand distribution through a non-cooperative game based on a dynamic electricity price signal and a charging service charge by taking the maximum self-charging decision utility as a target; and a charging station operator optimizes and adjusts a charging service fee decision by taking charging demand distribution as input and taking revenue maximization as a target. Compared with the prior art, the method can collaboratively optimize the economic operation of the power grid and the consumption of renewable energy sources, promotes the efficient flow and balanced distribution of resources among regions, and provides decision support for the dispatching of the power distribution network.

This invention pertains to an intelligent electronic device designed for sophisticated monitoring and analysis of electrical power distribution. The device integrates at least one sensor for detecting electrical parameters from a distribution system to a load, coupled with an analog-to-digital converter to transform sensed analog signals into digital data. A processing module, linked to the converter, employs customized moving average filters to calculate the frequency of electrical power distribution, enhancing measurement accuracy by adjusting for transient fluctuations. It retrieves frequency threshold settings from memory to define operational bounds, logging frequency data around identified deviation events when measurements surpass these thresholds. This system facilitates precise frequency analysis and robust event logging, providing a comprehensive solution for maintaining electrical power distribution within defined standards.

The present invention relates to the technical field of power systems and operations research. Disclosed are a method and system for coordinated source-grid-load-storage dispatch optimization during post-disaster restoration of a power distribution system. The method comprises: acquiring network topology constraint data for a power distribution system, wherein network topology constraints for the power distribution system comprise a virtual network topology constraint for the power distribution system, a geometric network topology constraint for the power distribution system, and an electrical network topology constraint for the power distribution system; on the basis of fault situations of a power source device, a load device and an energy storage device that are caused by a disaster, generating operational characteristic constraint data for devices in the power distribution system, wherein the operational characteristic constraint data for the devices in the power distribution system comprises operational characteristic constraints for the power source device, the load device and the energy storage device; and inputting the network topology constraint data for the power distribution system and the operational characteristic constraint data for the devices in the power distribution system into a pre-established coordinated source-grid-load-storage dispatch optimization model for power distribution systems in a post-disaster restoration scenario, such that a coordinated dispatch optimization result is output.

The invention discloses a power distribution switchgear remote monitoring and maintenance method based on the Internet of Things, relates to the technical field of power system operation and maintenance, and solves the problems that in an existing power distribution system, the edge anomaly recognition capability is weak, a control feedback chain is not closed, and multi-terminal control conflicts occur frequently. According to the scheme, a structured time sequence index of multi-source data is constructed on edge equipment, and equipment state drift is judged based on residual function included angle change; a control command management mechanism of a unique transaction identifier is introduced, a dual-channel feedback structure and a control mutual exclusion stack are combined, and a remote command consistency control chain is established; a hidden danger propagation chain is constructed on the cloud based on the abnormal Boolean bitmap and the topological relation, and a multi-node state linkage analysis and risk priority intervention strategy is achieved; according to the invention, the abnormity identification accuracy, the remote control stability and the system-level operation and maintenance response efficiency of the power distribution switch equipment are obviously improved.

The invention discloses a power distribution topology dynamic reconstruction risk assessment method, system and device and a medium, and relates to the technical field of data processing. The method comprises the following steps: acquiring real-time state data of an intelligent component to construct an initial topological structure, and identifying a changed target node by sending a detection signal; and then carrying out dynamic reconstruction on the topological structure in the three logic layers. And performing electrical characteristic verification on the reconstructed topological structure. And after the electrical characteristic verification is passed, determining a connection relationship of upstream and downstream power distribution cabinets and a component association link based on the target node, and calculating a risk level in combination with historical operation parameters. And formulating a temporary coping strategy according to the risk level, and generating a risk assessment report containing the topological influence range, the risk level and the coping strategy. Real-time monitoring and risk early warning of topological change of the power distribution system are realized in the whole process. By implementing the technical scheme provided by the invention, the risk assessment accuracy of the dynamic reconstruction of the power distribution topology can be improved.

The invention relates to a power distribution network voltage partition control method and system based on a hierarchical K-means clustering algorithm, and belongs to the technical field of power distribution system voltage partition optimization. According to the technical scheme, power distribution network node parameters are collected in a self-adaptive partition mode, a node sensitivity coefficient and an eigenvector of an electrical distance are constructed, and then a K-means algorithm is used for fine region division; selecting a dominant node: solving a Jacobi matrix through load flow calculation, extracting a voltage sensitivity coefficient, and selecting a node with the maximum sensitivity as a dominant node in each partition; multi-objective optimization: constructing an optimization model with minimum network loss, minimum voltage deviation and highest voltage stability as objectives; and partition cooperative control: accessing wind power and photovoltaic power to the dominant node, adjusting reactive power output in real time according to an optimization result, and realizing partition autonomy and global cooperation. According to the invention, voltage fluctuation and out-of-limit are inhibited, system network loss is reduced, control efficiency and economy are improved, and the method is suitable for complex topology and high permeability scenes.

In an approach to a state of health for grid applications, a system includes one or more battery energy storage systems having a plurality of batteries; energy sources; power distribution systems; and computing devices. The computing devices are configured to: for each of the battery energy storage systems: receive battery parameters for each of the batteries from the battery energy storage systems; determine a lithium plating state, a solid electrolyte interface (SEI) thickness, and a dendrite length for each of the plurality of batteries; determine a battery state of health (SOH) for each of the batteries based on at least one of the lithium plating state, the SEI thickness, and the dendrite length; determine a battery charge profile to mitigate aging for each of batteries based on the SOH; and send updated battery parameters and control thresholds for each of batteries to each of the battery energy storage systems.

The embodiment of the invention provides a digital simulation modeling method and device of a tandem type hybrid electric propulsion system, computer equipment and a medium, and relates to the technical field of simulation modeling, and the method comprises the following steps: constructing a turboshaft prime mover model, constructing a generator model, connecting the turboshaft prime mover model and the generator model in series to generate a generator set, the power generation groups are connected in parallel to construct a turbine power generation system; constructing a propulsion system; constructing a battery energy storage system; constructing a power transmission and distribution system, and respectively connecting the power transmission and distribution system with a turbine power generation system, a propulsion system and a battery energy storage system; and constructing a comprehensive control and energy management system, and outputting a digital simulation modeling result through a turbine power generation system, a power transmission and distribution system and a battery energy storage system. According to the scheme, a simulation modeling method based on multi-physics field coupling double-power-source dynamic response and energy flow regulation and control provides reliable modeling technical support for engineering application of a tandem type hybrid electric propulsion system.

The invention provides a charging pile cluster power coordination method, device and equipment and a storage medium, relates to the technical field of charging pile optimization, and is applied to a charging pile power distribution system which comprises a plurality of charging piles. The method comprises the following steps: acquiring current state data, historical use data and position data of each charging pile in different time periods, and determining corresponding priority weight data according to the position data and the historical use data; based on a preset prediction model, obtaining use probability data of the corresponding charging pile according to the historical use data and the corresponding current state data; obtaining corresponding power reference data according to the power grid dispatching plan data, the current state data and the use probability data; and obtaining a power adjustment strategy of each charging pile according to the current state data, the priority weight data and the power reference data based on a deep reinforcement learning model. According to the method, the prediction model and the deep reinforcement learning technology are combined, and intelligent and efficient power coordination is realized.

The invention discloses a flood disaster scene-oriented urban power distribution network toughness evaluation method and system, and belongs to the technical field of power distribution network toughness evaluation, and the method comprises the steps: obtaining rainfall data, land utilization data, elevation data and the like, and inputting the data into a waterlogging simulation module; the waterlogging simulation module simulates rainfall runoff production and runoff convergence to generate ponding distribution; the disaster judgment module obtains the fault probability of the power distribution equipment and the line in combination with the power distribution equipment and line disaster fault model, and generates a system disaster scene under the flood disaster; the load reduction optimization module constructs a power distribution system load reduction optimization model, and takes the minimization of the total load reduction amount of the power distribution system as a target; and the system toughness evaluation module measures the overall toughness of the power distribution system in the flood disaster scene. According to the method, the overall toughness level is quantitatively evaluated based on the system load reduction amount, the node load importance degree and the ponding condition are combined to recognize the weak links of the system, reference is provided for differential reinforcement and operation and maintenance strategies, and subsequent waterlogging prevention planning and operation and maintenance management are guided.

The invention discloses a multi-mode self-learning diagnosis and early warning method and system for a power distribution system, and relates to the technical field of intelligent operation and maintenance of power systems. According to the method, a visible light image, an infrared thermal image, a sound signal, an environmental parameter and an electrical parameter of the power distribution equipment are collected through a multi-mode sensor, and time synchronization and feature extraction are carried out; multi-modal features are constructed into a hypergraph structure, and cross-modal feature fusion is realized by using a graph attention mechanism; adopting a strategy of combining self-supervised pre-training and supervised fine tuning to carry out multi-objective joint optimization on the fused features to obtain a self-learning diagnosis model; the system inputs multi-modal data in real time during operation, outputs an equipment operation state and a health degree index, and realizes early warning and fault alarm through threshold comparison. According to the method, deep fusion and adaptive learning of multi-source information can be realized, high-precision diagnosis, real-time early warning and online updating capabilities are realized, and the intelligence and safety of a power distribution system are remarkably improved.

The invention discloses a power distribution control method and device for an optical storage DC flexible power distribution system, and relates to the technical field of power distribution control methods, and the method comprises the steps: determining a power consumption path of each power distribution region based on a power load and a photovoltaic power generation path of each power distribution region, and an energy storage path corresponding to the optical storage DC flexible power distribution system; and the power distribution balance event of each power distribution area is determined according to each power consumption path, the power distribution level of each power distribution area and the power distribution control relationship among the power distribution areas, so that the accuracy of the power distribution balance event of each power distribution area is improved. Therefore, the dynamic restoration event of the power distribution area is determined based on the autonomous management and control system and the abnormal power distribution position of the power distribution area, and the flexible regulation and control event of the optical storage direct-current flexible power distribution system is determined based on each dynamic restoration event, the working process of the optical storage direct-current flexible power distribution system and the flexible management and control path. And the autonomous flexible regulation and control effect of the optical storage direct-current flexible power distribution system is ensured.

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 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 provides a ship power battery state monitoring method and system based on multi-sensor data fusion, and relates to the technical field of batteries, and the method comprises the steps: interactively obtaining multi-mode monitoring data of a ship power battery in a ship matched intelligent power distribution system; generating a mapping confidence score by using the expected output prediction of the reliable twin of the sensor and the residual error of the multi-modal monitoring data; the method comprises the following steps of: after preprocessing multi-modal monitoring data, respectively extracting transient, trend and accumulation characteristics based on a multi-time scale sliding window; inputting the multi-modal feature set into a hierarchical fusion model, executing coupling fusion analysis in a module layer and a cabin ship layer, and outputting comprehensive operation state features; constructing an abnormal probability value according to a multi-dimensional abnormal index calculation result and the mapping confidence score; and monitoring and managing the state of the ship power battery according to the abnormal probability value. According to the invention, the technical problem of low monitoring efficiency of the state of the ship power battery in the prior art can be solved.

The invention discloses a power distribution system planning operation collaborative optimization method integrated with multi-flexibility resources. Comprising the steps of obtaining a reference data set of a power distribution system, and fitting wind power and photovoltaic edge distribution to construct a joint probability model; and fitting the relationship between the energy storage discharge depth and the capacity attenuation, establishing a full life cycle cost model, and outputting equivalent operation cost parameters changing along with the operation strategy. Based on wind-solar combined distribution parameters, operation cost parameters and load electricity price prediction, a multi-temporal-spatial-scale scene set is generated by adopting Latin hypercube sampling, and a typical scene is obtained through clustering and scene reduction. And constructing a two-stage robust capacity planning model in combination with the typical scene and the equivalent operation cost. The model is solved through a main-sub problem decomposition coordination strategy, an installation and capacity configuration scheme is obtained, and integrated collaborative optimization of long-term planning and short-term operation of the power distribution system is achieved. According to the invention, the safety, economy and flexibility of the power distribution system in a high-volatility environment can be effectively improved.

The invention is suitable for the technical field of electrical measurement and state monitoring, and provides an aluminum electrolysis cell power distribution system regionalization independent blanking control method based on pseudo resistance monitoring, and the method comprises the steps: collecting the anode current and the cell voltage of each measurement point; dividing the plurality of measurement points into a plurality of control areas, and calculating a pseudo resistance value of each control area; screening control areas meeting conditions from all the control areas to form a reference area set; determining an aluminum oxide concentration reference state of each control region in the reference region set through a preset concentration state mapping relation; with the reference region set as a starting point, according to the proximity relation between the control region with the undetermined state and the reference region set in space and the similarity of pseudo resistance values, the aluminum oxide concentration state is propagated to all the control regions through iterative matching; according to the aluminum oxide concentration states of all the control areas, independent discharging control instructions of all the control areas are generated; and the regionalized independent control on the concentration of aluminum oxide in the aluminum electrolysis cell is realized.

The invention provides an electric energy hybrid game method for multi-agent collaborative scheduling. By constructing a three-layer collaborative game framework, dynamic decisions of a power distribution system operator, an electric vehicle charging station and an electric vehicle user are incorporated into a unified optimization model. According to the hierarchical iteration mechanism of the three-level game model, firstly, a power distribution system operator publishes node marginal electricity price on an outer layer, a middle-layer charging station is driven to adjust a bidding strategy, and then an inner-layer user is guided to dynamically update a charging station selection proportion. The closed-loop optimization from electricity price conduction to user response effectively breaks the limitation of unbalanced benefit distribution in the traditional two-party game. Through the nested design of the master-slave game, the non-cooperative game and the evolutionary game, the results of the three layers of games are finally converged to an equilibrium state, so that the charging station selection, power distribution interaction and pricing strategies form a collaborative optimal solution, the global optimization of network-station-vehicle three-party resource scheduling is realized, and the power resource allocation efficiency is remarkably improved.

The invention provides a power load regulation potential assessment method and system based on a total incoming line, and relates to the field of power data analysis, and the method comprises the steps: obtaining the total incoming line load data of a target power distribution system, and extracting feature factors; a causal directed graph with feature factors as nodes is constructed, the causal relationship between the nodes is determined through an improved PC algorithm, and the improvement comprises time delay expansion, chi-square statistic correction, time sequence constraint and dynamic adjacency optimization; performing anti-fact reasoning based on a causal diagram to obtain a predicted value of the total load; according to the multi-dimensional adjustment potential index, calculating the load adjustment potential under virtual intervention through the predicted value of the total load; according to the method, non-intrusive, explainable and dynamic evaluation of the user load flexibility adjustment potential is realized.

The invention relates to the technical field of electrical safety, and discloses a multistage cooperative fault detection method and system based on an intelligent air switch, and the method comprises the steps: intelligent air switch terminals disposed at all levels of a power distribution network are used for synchronously collecting a multi-physical-quantity time sequence signal; the intelligent air switch terminal calculates the dynamic correlation entropy of the collected current signal and executes local fault diagnosis according to the dynamic correlation entropy; the terminals carry out cooperative communication, and dynamic correlation entropy is collected to construct an entropy migration spectrum so as to carry out cooperative traceability on faults; and finally, integrating local diagnosis and collaborative traceability results, and executing corresponding hierarchical collaborative protection actions. The system comprises an acquisition module; an entropy calculation module; a local diagnosis module; a communication module; a collaborative traceability module; and a protection execution module. According to the invention, through multi-stage cooperative fault detection of the intelligent air switch, accurate identification, rapid response and state early warning of hidden faults are realized, and the safety and reliability of a power distribution system are improved.

The invention discloses an intelligent electricity larceny prevention power distribution system and method, electronic equipment and a storage medium, and the system comprises a data collection module which is used for obtaining current data, electric quantity data and temperature data of a power distribution line; the data processing module is used for performing space-time alignment processing on the current data and the temperature data to obtain a current temperature data matrix, and constructing a node current balance equation according to the current temperature data matrix and the electric quantity data; the confidence coefficient generation module is used for constructing a Bayesian network based on a preset historical electricity stealing case library, and inputting a calculation result of the node current balance equation into the Bayesian network for time sequence probabilistic reasoning calculation to obtain electricity stealing behavior confidence coefficient; the instruction generation module is used for matching a preset risk level according to the electricity stealing behavior confidence and generating a risk disposal instruction according to the risk level; and the execution module is used for determining a target line to execute target operation according to the risk disposal instruction. By implementing the technical scheme provided by the invention, the technical problem of single detection dimension can be solved.

The invention relates to the technical field of intelligent monitoring of power distribution systems, and discloses an intelligent digital electric box power utilization monitoring management system based on the Internet of Things. The system comprises a data acquisition module, a data processing and analysis module, an intelligent control module, an Internet of Things communication module and a user interaction and management module. The data acquisition module acquires electrical and environmental parameters in real time; the data processing and analyzing module constructs an electricity utilization fingerprint database of the equipment, calculates a real-time threshold value through a dynamic threshold value engine, and realizes equipment-level anomaly recognition in combination with an anomaly detection engine; the intelligent control module executes a control action according to a detection result; the Internet of Things communication module realizes two-way data transmission; and the user interaction and management module provides a visual operation interface. According to the invention, through a dynamic threshold mechanism, equipment fingerprint identification and multi-level early warning control, equipment-level hidden faults are accurately identified, and the power utilization safety and the intelligent management level are improved.

The invention relates to the technical field of data processing, and particularly provides an automatic fault tracing method, system and device based on topological coding and a medium, and the method comprises the steps: distributing a unique topological code reflecting the hierarchical position of physical equipment for the physical equipment in a factory power distribution system; the method comprises the following steps: collecting real-time operation data through an edge collection terminal, and binding topological codes to form a real-time data stream with a label; constructing a topology dependency degree model, and defining the inherent failure rate of each node and the dependency degree of each node on a superior node; when the fault of the target equipment is detected, reversely traversing upstream nodes along a topological path based on the model, and calculating the fault suspicion probability of each upstream node by adopting a probability propagation algorithm; and carrying out normalization processing on the probabilities, fusing real-time state data, carrying out weighted correction, and finally generating a fault diagnosis report sorted according to the probabilities. According to the invention, by introducing a multi-level topological coding system and a probability propagation algorithm, rapid and accurate positioning and intelligent diagnosis of faults are realized.

The present invention provides a system and method for monitoring conditions within an electrical distribution system. According to a first preferred embodiment, the present invention provides a sensor module delivery system which uses UAVs to deploy sensor modules within the electrical distribution system. According to a first preferred embodiment, the system includes a drone mounting system and a gripper mechanism for attaching to a sensor module. The system also includes an extended carbon fiber shaft which vertically extends down from the drone mounting system and which supports a controller module, a transceiver, a battery module, a camera and the gripper mechanism. According to a further preferred embodiment, the gripper mechanism includes two or more gripping arms which are movable by the controller module between a first open position and a second closed position.

The invention discloses a power distribution network island grid-connected smooth switching control method and system, belongs to the field of power distribution networks, and particularly relates to power distribution system control, and the method comprises the steps: carrying out the feature extraction of a first voltage signal at the island side of a power distribution network and a second voltage signal at the main network side of the power distribution network, and obtaining a quantitative feature value; inputting the quantized characteristic value into an inrush current prediction model to output a closing inrush current prediction range, calculating a width value and a peak amplitude of the prediction range corresponding to each phase time sequence to identify a target phase interval, and evaluating stability contribution of each phase time sequence in the target phase interval to determine a target closing time sequence; and adjusting the output characteristic parameters of the inverter according to the target closing time sequence to obtain an inverter output signal, performing iterative optimization to adjust phase difference compensation, and generating a grid-connected control instruction to control grid-connected smooth switching of the power distribution network island, so that smooth switching during grid connection of the power distribution network island and the main network can be realized, and the stability of the power distribution system is improved.

The invention discloses a resource scheduling method and device of a power distribution system and electronic equipment. The method comprises the following steps: acquiring multi-source heterogeneous data related to a power distribution system; a graph neural network and a space-time attention mechanism are adopted, a target coupling relation is determined according to the multi-source heterogeneous data, a heterogeneous data association graph is obtained, and the target coupling relation comprises the coupling relation among the equipment state, the environmental factor and the load demand; determining a current scene of the power distribution system by using a multi-stage classifier and a heterogeneous data association graph; an objective function corresponding to the current scene is called, and the objective function comprises a first sub-function considering a day-ahead stage and a second sub-function considering an intra-day stage; and solving the target function under the corresponding constraint condition to obtain a scheduling strategy corresponding to the power distribution system. According to the invention, the technical problem that it is difficult to formulate a scheduling strategy in a targeted manner in the prior art is solved.

The invention provides a method for automatically generating a vertical power distribution system diagram based on BIM in forward design, and relates to the technical field of building electrical, comprising the following steps: performing intelligent analysis on a building BIM three-dimensional model of forward design, and accurately identifying electrical professional components; key data of the distribution boxes are extracted, and a three-level electrical system topology network of a total distribution cabinet, layer distribution boxes and terminal distribution boxes is constructed; standardized data are generated through multiple verifications of data formats, logic relations and parameter thresholds; automatic drawing output is achieved in a tiled mode and an aligned mode, and a bidirectional linkage mechanism of a BIM model and a system drawing is established. The method aims at solving the problems that traditional AutoCAD two-dimensional manual drawing is low in efficiency, disordered in version management, lack of three-dimensional space expression and insufficient in design accuracy.

The invention discloses a renewable energy penetration power distribution system scheduling method and system based on a block chain, and relates to the technical field of power distribution system scheduling, and the method comprises the following steps: constructing a cross-hierarchy time sequence integrity observation layer, introducing a multi-source high-precision reference signal into a synchronous time service link, and carrying out the multi-source high-precision reference signal; the fingerprint acquisition module is used for acquiring external environment electromagnetic disturbance and atmospheric propagation delay data in real time and generating a phase offset fingerprint corresponding to a time service state; and performing causal decomposition operation based on the phase offset fingerprint, performing noise stripping processing on the acquired electromagnetic disturbance signal, and extracting a real time service error trajectory. Through combination of multi-source time service correction, phase fingerprints and virtual impedance time marks, time self-calibration and cross-node synchronization of the block chain power distribution system are realized, account book wrong sequence caused by time service drift is eliminated, power flow reversal is suppressed through time reversal traction and dynamic constraint, scheduling stability and energy flow consistency are ensured, and the power distribution efficiency is improved. The system safety and the clean energy utilization efficiency are improved.

The invention relates to an RCBO-oriented fault positioning distribution box control method and system, and belongs to the technical field of intelligent power distribution and fault diagnosis in the field of electrical engineering, and the method comprises the following steps: S1, collecting a three-phase current signal and a residual current signal of a power distribution system; s2, calculating a harmonic distortion rate and a load unbalance degree based on the three-phase current signal; s3, based on the residual current signal, calculating a residual current waveform complexity index; s4, combining the harmonic distortion rate, the load unbalance degree, the residual current waveform complexity index and a preset basic threshold to generate an adaptive threshold; s5, selecting one of a plurality of preset fault judgment modes according to the numerical value of the residual current waveform complexity index; and S6, the selected fault judgment modes are adopted, the residual current signals are processed to generate fault judgment results, at least one fault judgment mode uses a self-adaptive threshold value, and a solid data basis is provided for subsequent self-adaptive adjustment.

The invention provides a new energy automobile endurance prediction method based on working condition identification and prediction, and belongs to the technical field of new energy automobile endurance mileage estimation. According to the method, sliding window statistical characteristics are constructed through speed, current, voltage and other signals, typical working conditions of cities / suburbs / highways and the like are identified, the working condition of a next time window is predicted, and energy consumption priori which can be updated in real time along with changes of road conditions is formed. Secondly, a rolling capacity estimation model is provided, the available capacity of the battery is continuously evaluated based on historical charging and discharging data, and dynamic changes of the SOH of the battery along with time and use conditions are recorded; according to the method, working condition prior, rolling SOH and time sequence energy consumption characteristics are fused, a TCN-BiLSTM multi-model cooperation framework is constructed, short-term dynamic and long-term attenuation trends are considered, high-precision and generalizable endurance mileage prediction under complex working conditions and battery state fluctuation is realized, reliable support is provided for intelligent energy consumption management and journey planning of vehicles, and the method is suitable for popularization and application. The method can also be applied to an intelligent power distribution system with a high reliability requirement, and provides a core solution for technology promotion service in related fields.