86469 results about "Electrical current" patented technology

The invention discloses a distribution line fault intelligent diagnosis method based on multi-source information fusion, and belongs to the technical field of power system fault detection and diagnosis, and the method comprises the steps: obtaining distribution line data and meteorological data; superposing the distribution line data with the meteorological data to generate a space-time fusion feature matrix based on the wire space displacement; dynamically adjusting a preset initial threshold value by using the space-time fusion feature matrix; and performing multi-round verification on the abnormal fluctuation of the electrical parameters of the line according to the fault judgment threshold, generating a fault positioning instruction, performing real-time matching with the topological structure of the line, correcting the priority queue of the fault section based on the switching action feedback data of the feeder terminal, and triggering the fault removal action matched with the priority. According to the method, spatial-temporal feature fusion of current, voltage, weather and spatial displacement data and a dynamic threshold adjustment mechanism are adopted, the fault type can be accurately identified, the fault section can be positioned in real time, and the diagnosis precision and the response speed in a complex environment are remarkably improved.

The invention provides a power cable fault detection method, which comprises the following steps of: obtaining a cable material, a laying environment and an insulation aging degree attribute parameter of each monitoring segment according to a pre-established power cable segment model, determining a correction coefficient of the segment model according to load current magnitude at different operating temperatures, and determining a power cable fault detection result according to the correction coefficient; the correction coefficient is used for adjusting the electrical parameter of each segment to adapt to the actual operation condition; in the fault positioning process, a time sequence analysis method is introduced, the dynamic change trend of current and voltage data before and after a fault occurs is considered, the fault occurrence moment is recognized through an anomaly detection algorithm, and the position coordinates of a fault point are corrected according to the difference between the cable material and the laying environment in combination with a judged fault area.

The invention discloses a predictive maintenance strategy optimization method for transformer area equipment maintenance, relates to the technical field of transformer area equipment maintenance, and is used for solving the problem of poor maintenance effect of transformer equipment. Sensors are installed in a transformer area to collect current, voltage, temperature and other key data, preprocessing, frequency alignment and fusion are carried out to generate the same equipment state data, and when data fluctuation exceeds a threshold value, re-collection and calibration are triggered, a health state model is constructed, and a health index is calculated to evaluate the equipment state. The method comprises the following steps: predicting a future health state through an LSTM model, triggering early warning when the future health state is lower than a baseline, dividing risk levels according to health indexes and risk factors, setting maintenance priorities based on health assessment and fault prediction, applying a multi-objective optimization algorithm in combination with an emergency degree and equipment importance to assess resource requirements, and dynamically monitoring resource use conditions. The prediction precision is improved, and the equipment resource allocation efficiency and the maintenance response speed are improved.

The invention relates to the technical field of online calibration, in particular to a multi-parameter fusion intelligent electric energy meter online calibration method and system, and the method comprises the following steps: collecting voltage waveforms, current harmonics and active power data, dividing windows, calculating a covariance matrix, and generating a feature set; a power factor curvature extreme value and a temperature inflection point offset are analyzed to generate an interference identifier, current density distribution and a voltage distortion spectrum are jointly analyzed to extract a harmonic energy ratio to generate a feature vector, and phase compensation is performed on a pulse sequence to generate a calibration instruction set. According to the method, the covariance matrix is constructed by synchronously collecting voltage and current power parameters, the abnormal mark section is generated by combining the temperature change and the covariance difference value, the environment disturbance and the real deviation are effectively distinguished, and the temperature hysteresis effect is identified through the power factor curvature extreme value and the temperature inflection point offset. And combining current density and voltage distortion spectrum analysis to extract a fundamental wave and harmonic wave energy ratio, establishing a composite calibration reference, and dynamically adjusting a pulse duty ratio to realize harmonic wave energy compensation.

The invention provides a mining circuit fault self-diagnosis method and system. According to the method, current and voltage waveforms and three-dimensional vibration signals of a cable are collected, and anti-interference data are generated through self-adaptive noise reduction and time sequence synchronization; a waveform interception window is dynamically adjusted based on the correlation between the mechanical vibration intensity and the current transient rate, the wave crest slope variable quantity is extracted from the current transient segment, high-frequency harmonic energy is separated from the voltage transient segment, time-frequency analysis is carried out on the vibration signal to extract an energy sudden increase frequency point, and a mechanical damage spectrum feature set is constructed; inputting the features into a space-time correlation model, and verifying space-time consistency of current distortion and voltage abnormity to generate composite features; dynamically correcting a fault threshold based on the environmental interference factor; and finally, a short-circuit peak or open-circuit oscillation diagnosis result is output according to the association strength of the electrical and mechanical characteristics. According to the invention, accurate fault self-diagnosis of the mining cable under a complex working condition is realized.

The invention discloses an intelligent power distribution layered self-healing fault isolation and power supply recovery method, which is suitable for realizing rapid fault isolation and power supply recovery of a non-fault area when a power distribution system has a fault. According to the method, a hierarchical control framework is adopted, and intelligent switch equipment on the lower layer is responsible for collecting the current and voltage states of a line in real time and immediately completing local identification and fault section removal after a preset fault signal is detected; the fault information is then uploaded to a power distribution automation master station on the upper layer, the master station analyzes a recoverable power supply area in combination with the current network topology and generates a network reconstruction scheme, and a non-fault area is switched to a standby power supply path by controlling an interconnection switch; the system supports the backtracking analysis of historical data such as waveform distortion and partial discharge signals before a fault, identifies a potential abnormal trend, optimizes an operation strategy, and achieves a self-adaptive early warning function. The method has the advantages of being rapid in response, clear in structure and high in autonomy, and the reliability and continuity of the power distribution system can be remarkably improved.

The invention relates to the technical field of power supply or power distribution circuit systems, in particular to a photovoltaic module fault monitoring system and method, and the system comprises an acquisition module, a power supply dynamic compensation module, a control optimization module, a power supply module and a digital twin module. The acquisition module acquires multi-source data through the infrared thermal imaging sensor, the electroluminescent detection unit and the current and voltage characteristic curve acquisition module, the power supply dynamic compensation module dynamically adjusts wavelet basis function parameters based on an improved whale optimization algorithm, and the power supply module fuses hot spot distribution, current and voltage abnormity and aging trend data. And driving the dynamic adjustment of the protection threshold. And the digital twin module synchronizes real and virtual system data through transfer learning, rehearses a fault path to generate a maintenance instruction and feeds back the maintenance instruction to an optimization prediction model, so that a monitoring, protection and self-optimization closed-loop system is formed, and the fault diagnosis precision and the system reliability in a complex environment are improved.

The invention discloses a transformer substation electric power parameter real-time monitoring and analysis platform, and relates to the technical field of electric power monitoring. The monitoring analysis platform is in communication connection with a real-time monitoring module, a data acquisition and processing module, a data storage and management module, a fault feature extraction module, an event early warning module, a fault diagnosis module and a data visualization module. The transformer station electric power parameter real-time monitoring and analysis platform timely discovers abnormal conditions of electric power equipment by collecting and analyzing key parameters of voltage, current, power, temperature and humidity in real time, so that potential faults and accidents are prevented, and the real-time monitoring and analysis of the electric power parameters of the transformer station is realized by learning historical fault data and identifying modes. The platform can predict and identify an abnormal trend which may cause a fault, gives out an early warning in advance, remarkably improves the reliability and safety of a power system, reduces the risks of accidental power failure and equipment damage, and guarantees the continuity and stability of power supply.

Disclosed in the present invention are a grid-connect control method and apparatus for a grid-connect inverter. The method comprises: on the basis of a control structure of a grid-connect inverter in a dp domain, passing a deviation signal of a power outer loop through power outer loop controllers, so as to generate reference values of a current inner loop, and comparing the reference values of the current inner loop with an actual output current, so as to obtain error signals, wherein the control structure comprises a PQ power control outer loop and a current control inner loop, and the actual output current is obtained by means of performing phase tracking, on the basis of a synchronous reference frame phase-locked loop, on the voltage of a point of common coupling; and adjusting the error signals by means of a current inner loop controller, so as to generate modulation signals, performing pulse width modulation (PWM) on the modulation signals, so as to generate an on-off signal of an inverter bridge power semiconductor device, and controlling the state of connection and disconnection between the grid-connect inverter and a power grid on the basis of the on-off signal. In the present embodiment, the connection and disconnection between a grid-connect inverter and a power grid are controlled, so as to improve the stability of the grid-connect inverter in weak power grids.

The invention discloses an intelligent control system for a current transformer, and particularly relates to the technical field of power system monitoring, which comprises a fluctuation identification unit, a redundancy acquisition unit, an error fitting unit, a protection delay unit and a fault response unit, realizes real-time identification and classification of current fluctuation, and has standby path high-speed sampling and fusion signal construction capabilities. The fluctuation trend is judged through error regression, a protection strategy is dynamically set, response is delayed to avoid misoperation, finally, a high-level protection instruction is triggered and a fault event is output when offset overruns or alignment fails, and the data accuracy and the system response stability in the power supply switching process are guaranteed; according to the method, accurate identification of current fluctuation is realized through multi-dimensional feature extraction, data reliability is enhanced by using redundant sampling and error fitting, and by combining delay control and a hierarchical response mechanism, the risk of misoperation is effectively reduced, the fault judgment accuracy and the system protection stability are improved, and the method is suitable for a complex power supply switching scene.

The invention discloses a data driving-based power battery safety risk assessment method and system, particularly relates to the technical field of battery safety monitoring, and is used for solving the problems of false alarm and missing detection caused by confusion of electrochemical relaxation effect and real fault signal characteristics in the existing standing stage fault detection method. Through multi-source data acquisition based on voltage, temperature and state of charge in a standing stage, a current slope extreme point is identified through charge and discharge mode weighted correction, a time-delay mapping relation with a voltage curve geometrical morphology abrupt change point is established, abnormal inflection points are screened, and fractal dimension attenuation characteristics are quantified; according to the method, abnormal distribution density and material damage indexes are fused to generate a dynamic threshold value, composite criterion analysis is carried out by combining frequency domain energy offset characteristics extracted by time-frequency transformation and heat conduction time-lag phase difference, relaxation interference signals are effectively stripped, hidden danger characteristics are locked, full-dimension safety state evaluation from microdefect evolution to macroscopic parameter abnormity is realized, and the safety state evaluation accuracy is improved. And the reliability of power battery fault detection under complex working conditions is improved.

The invention discloses a full-effect electric energy optimization rapid detection system and method, and particularly relates to the technical field of electric energy detection. The method comprises the following steps: acquiring voltage, current, frequency, harmonic component and three-phase unbalance degree of a power grid in real time, calculating a power grid impedance value and a load dynamic characteristic ratio, drawing an impedance frequency characteristic curve, analyzing a harmonic amplification abnormal degree and a load dynamic response characteristic, and evaluating the accuracy of a detection instruction generated by the full-effect electric energy optimization device. The error correction is carried out on the inaccuracy detection instruction, the duty ratio is dynamically adjusted by utilizing the PWM technology, the accurate matching of the amplitude and the phase of the output current is realized, the error correction effect is evaluated by comparing the real-time detection value with the theoretical calculation value, and the detection model and the compensation strategy are automatically optimized. The problems of detection precision reduction and error compensation caused by complex power grid conditions in the prior art are solved, harmonic amplification, reactive power over-compensation and three-phase balance damage are avoided, and efficient and accurate electric energy optimization and power grid stability improvement are achieved.

The invention relates to the technical field of power battery packs, and discloses a power battery pack state evaluation method and system, and the method comprises the steps: collecting an operation characteristic data set of a power battery pack under various working conditions, and constructing a hybrid evaluation model; performing parameter configuration on the double-extended Kalman filter to obtain an improved filter; acquiring real-time voltage, current and temperature data, and inputting the real-time voltage, current and temperature data into the improved filter for state calculation to obtain a charge state value and an internal parameter value; inputting the charge state value and the internal parameter value to perform multi-branch adversarial neural network analysis to obtain a fault mode type and a fault severity; according to the method, the multi-factor health index is calculated, particle swarm optimization fitting is carried out on the degradation curve of the power battery pack, the residual service life prediction value is obtained, more accurate residual service life prediction is further achieved, the precision in a wide temperature range is remarkably improved, and the difference between monomers in the power battery pack can be effectively processed.

A power distribution network cable fault point location method and system, a computer device and a medium, belonging to the technical field of power distribution networks. The location method comprises: S101, when a cable has a fault, a transient signal of a wide-area frequency band is generated, a fault traveling wave containing high-frequency components; a traveling wave line mode component having a relatively small chromatic dispersion is used to perform measurement; decoupling an extracted fault traveling wave signal; S102: the traveling wave voltage and current will have a sharp change when the traveling wave generated by the fault point reaches a measurement end, and the traveling wave head can appear as a high-frequency sudden change in a time-frequency graph, the sudden change point being the position of the wave head; S103: performing EEMD decomposition on the fault traveling wave line mode component, and extracting a first IMF component for Hilbert transform to obtain a time-frequency graph thereof, a sampling moment corresponding to the position of a first frequency sudden change point on the time-frequency graph being the arrival time of the fault traveling wave head; and using a double-end fault location algorithm to calculate a distance with respect to the fault point. The result of the location method has relatively high precision, and, compared with the actual fault position, has a relative error not more than 4%.

The invention discloses a switching loss evaluation method and system based on a semi-soft switching modulation technology, and relates to the technical field of information. According to the method, parasitic inductance parameters and buffer capacitance parameters of a device are obtained, a resonant circuit working model is established, an initial voltage waveform and an initial current waveform are obtained by solving the model, and corresponding voltage stress and current stress are calculated; a parasitic inductance parameter and a buffer capacitance parameter of the device are optimized by using a genetic algorithm; adjusting the design of the buffer circuit according to the optimized device parameters, carrying out the simulation of the resonance process again, carrying out the frequency domain analysis of the optimized resonance voltage waveform and resonance current waveform, and optimizing the device parameters and the design of the buffer circuit. And finally, semi-soft switching modulation simulation is carried out, a temperature coefficient mapping relation between simulation switching loss and actually measured switching loss is constructed, an optimal design scheme of the device is determined, the switching loss of the device is effectively reduced, and it is ensured that the device works in a safe working area.

The invention relates to the technical field of power system fault monitoring, and discloses a 10kV voltage transformer ground fault real-time monitoring method and system, and the system comprises a ground fault data collection module, a waveform distortion analysis module, a transient signal detection module and the like. Three-phase current, zero-sequence current and voltage waveform data are collected, a current harmonic component proportion, a zero-sequence current high-frequency transient energy value and the like are analyzed, a fault type is determined by combining a phase difference, and a fault position is positioned according to topological parameters and line impedance. And the temperature of the grounding down lead can be monitored, and the fault probability is evaluated and the threshold value is dynamically adjusted by machine learning. According to the invention, real-time accurate monitoring can be realized, fault types and positions can be accurately diagnosed, potential hidden dangers can be comprehensively monitored, the intelligence of a monitoring system is improved, the operation and maintenance cost and risks are effectively reduced, and safe and stable operation of the 10kV power distribution network is ensured.

The invention discloses a high-precision voltage measurement method and system based on multi-parameter adaptive compensation, and relates to the technical field of intelligent voltage measurement. The high-precision voltage measurement method and system based on multi-parameter adaptive compensation comprises the steps that S1, voltage signal data and disturbance source characteristic data are collected, preprocessing is completed, and an analysis basis is constructed; s2, analyzing voltage excursion in combination with disturbance current characteristics, and dynamically adjusting a compensation path; s3, evaluating a compensation correction effect, and driving a compensation output strategy in real time; and S4, comprehensively analyzing the offset characteristics and the correction result, judging an abnormal section and triggering adaptive adjustment. The problems that disturbance components cannot be comprehensively extracted from multiple parameters such as PWM modulation frequency, wire harness impedance and working condition load change and a compensation function cannot be reversely constructed in an existing method, and a measured value does not have stability are solved.

The invention relates to the technical field of electrochemical energy storage, in particular to an intelligent management system for electrochemical energy storage application, which comprises a state real-time monitoring module, a dynamic regulation control module, a fault diagnosis and analysis module, an emergency response module, a health monitoring and analysis module and a charging and discharging strategy module. According to the invention, by monitoring key performance parameters such as voltage, current and temperature of the electrochemical energy storage equipment in real time and combining data of the environment monitoring sensor, external and internal changes can be responded in real time, the response speed and preventive maintenance capability of the equipment are improved, and upcoming load requirements are met by adjusting discharge parameters in time; according to the invention, the device can be used for preventing overdischarge and potential equipment damage, effectively prolonging the service life of the battery, optimizing the energy consumption, adjusting the maintenance period according to real-time data, reducing the risk of sudden failure, improving the stability and safety of the electrochemical energy storage equipment in a complex environment, and supporting the stable operation of the equipment.

The invention provides a single-tube boost PFC circuit control method and system for single-cycle control, and relates to the technical field of data processing, and the method comprises the steps: generating a self-adaptive PWM control signal according to a duty ratio adjustment amount and a frequency compensation factor, and dynamically limiting the pulse current amplitude of a power switch tube through a peak current prediction algorithm, a load current change rate is generated based on the real-time relevance between the pulse current amplitude and the load current; setting a first monitoring point in a dynamic duty ratio change path of the PWM control signal, and extracting a duty ratio change rate and a switching frequency fluctuation parameter in real time; setting a second monitoring point in a feedback path of a load current change rate, and extracting a load current slope characteristic and a transient change amplitude in real time; and based on the parameters of the first monitoring point and the second monitoring point, generating a correction factor through a dynamic response correlation model. According to the invention, a high power factor can be realized under wide input voltage and load fluctuation.

An electric power assisted steering assembly comprises a steering mechanism which operatively connects a steering wheel to the roadwheels of a vehicle, a torque sensing means adapted to produce a first output signal indicative of the torque carried by a portion of the steering mechanism, a means for producing a second output signal indicative from a signal indicative of the angular velocity of the portion of the steering mechanism, an electric motor operatively connected to the steering mechanism, a signal processing unit adapted to receive the two output signals and to produce therefrom an overall torque demand signal representative of a torque to be applied to the steering mechanism by the motor, and a motor drive stage adapted to provide a drive current to the motor responsive to the torque demand signal. The overall torque demand signal includes a damping component that is dependent upon the second output signal. The means for producing the yaw damping component includes a filter having one pole and one zero, and in use the second signal is passed through the filter to produce the damping component, the frequency of the pole and zero being selected such that the filter provides a band between the pole and zero within which the phase of the filtered second signal and the velocity signal are further out of phase or in phase than within the band.

The invention provides an electric vehicle battery health state monitoring and service life estimation method and system, and the method comprises the steps: S1, obtaining a real-time data flow of a battery during the operation of a vehicle, extracting the original records of charging and discharging depth, temperature change, internal resistance parameters and capacity data from the real-time data flow, a dynamic monitoring sample is calculated through voltage, current and temperature values collected by a sensor; s3, calculating a capacity attenuation rule through the time sequence feature set, analyzing the decrease amplitude of the capacity after each charge-discharge cycle by adopting an exponential attenuation model, obtaining a long-term operation trend from historical data, and obtaining a dynamic curve of capacity attenuation; and S8, if the confidence interval of the final estimation probability distribution is greater than a preset threshold value, recollecting data with higher frequency for the dynamic monitoring sample, and performing iterative optimization on the life estimation model through the updated sample to obtain an adjusted life detection result.

To enable accurate estimation of a degree of deterioration of a secondary battery with a metal lithium layer on an anode.SOLUTION: A battery deterioration estimation device comprises a current measurement part, a voltage measurement part, a calculation part, and an estimation part. The current measurement part measures a discharge current of a secondary battery at predetermined timing immediately after the start of discharge of the secondary battery. The voltage measurement part measures a drop voltage that is a difference between a voltage of the secondary battery before the start of discharge and a voltage of the secondary battery at the predetermined timing. The calculation part calculates an internal impedance of the secondary battery at the predetermined timing from the measured discharge current and the measured drop voltage. The estimation part estimates a degree of deterioration of the secondary battery from the calculated internal impedance.SELECTED DRAWING: Figure 1

The invention relates to the technical field of motor control, and discloses a control method and system of a permanent magnet direct current brushless slotless motor. The method comprises the following steps: performing temperature compensation and signal filtering on voltage data of a Hall sensor to obtain rotor position information and temperature characteristic data; performing magnetic field intensity dynamic compensation calculation according to the rotor position and the temperature data to obtain magnetic field intensity parameters; adjusting the amplitude and phase of the three-phase current according to the magnetic field intensity parameter, and generating a current control quantity; extracting and compensating a harmonic component to obtain a torque smooth control instruction; all losses are calculated and optimized, and efficiency optimization parameters are generated; and performing feature extraction and anomaly judgment on the operation parameters, and outputting a protection control strategy. Accurate detection of motor position signals, stable control of torque, optimal control of loss and real-time monitoring and protection of abnormal states are achieved under the high-temperature working condition, and therefore stable operation and the service life of the motor under the high-temperature environment are guaranteed.

A DC relay for anti-short circuit current and arc extinction includes two static contact leading-out ends, a movable contact piece in a straight sheet type, a pushing rod assembly, a fixed upper yoke, a follow-up yoke and a lower armature. The fixed upper yoke is fixed above the movable contact piece, corresponding to a position between the two movable contacts. The follow-up upper yoke is fixed on the pushing rod assembly, above the movable contact piece, corresponding to a position between the two movable contacts. The lower armature is fixed on a bottom end face of the movable contact piece. The fixed upper yoke, the follow-up upper yoke and the lower armature are respectively arranged in a width direction of the movable contact piece, and two magnetic conductive loops are formed in the width direction of the movable contact piece.

The invention relates to the technical field of MOS semiconductors, and discloses a variably doped planar gate silicon carbide VDMOS device and a preparation process thereof, the variably doped planar gate silicon carbide VDMOS device comprises a plurality of MOS cells which are parallel to each other, and each MOS cell comprises a drain electrode, a semiconductor epitaxial layer, a source electrode and a grid electrode; the semiconductor epitaxial layer comprises an N substrate layer, an N drift layer, a P + layer, an N well layer and a P well layer, and a lightly doped N layer is arranged in the middle of the N drift layer of a single MOS cell; lateral symmetric P-layers are arranged in the single MOS cell and located on the left side and the right side of the N drift layer, and the section contours of the corresponding sides of the lateral symmetric P-layers on the two sides are in an arc shape. By arranging the lightly doped N layer in the middle of the N drift layer and introducing the arc-shaped laterally-symmetrical P-layers to the two sides, the electric field distribution of the device is optimized, the local electric field concentration is reduced, the breakdown voltage is remarkably improved, and the charge balance capability is enhanced and the leakage current is reduced through the contact between the laterally-symmetrical P-layers and the N substrate layer.

The invention discloses a data anomaly detection system and method based on power equipment, and belongs to the technical field of power system data processing and fault monitoring, and the method comprises the steps: obtaining a multi-dimensional operation parameter sequence of voltage, current, temperature, harmonic waves, switching states, topological energy transfer vectors and the like; constructing a local disturbance response map, extracting a micro-disturbance driving factor, and generating a high-dimensional feature embedding matrix; constructing a multi-scale state density map on the basis of the embedded matrix, and mapping an equipment behavior evolution track; introducing a coupling evolution path tracking algorithm based on the density map, identifying an abnormal state set, and constructing a cross-time-period risk channel; matching the current monitoring data with the risk channel, and calculating a risk evolution value; when the value exceeds a set threshold value, abnormal early warning is triggered, and an evolution path model is output; the method has the advantages of high accuracy, strong trend identification capability and early warning, and is suitable for intelligent operation and maintenance of power equipment under complex working conditions.

The invention discloses a DC-DC power supply dynamic response optimization system based on digital PID, which relates to the technical field of DC-DC power supply dynamic response optimization, and comprises a voltage and current sampling module, a reference signal generation module, an output signal generation module, a digital signal generation module, a control module and an output signal generation module, the digital PID controller calculates control output according to errors, the PWM signal generation module generates corresponding PWM signals according to the control output, the power switch driving module amplifies the signals to drive a switch tube, the load monitoring module monitors load changes in real time, output of the load monitoring module can be fed back to other modules, and power supply dynamic response optimization is achieved. According to the invention, the dynamic response performance of the DC-DC power supply is remarkably improved, the output fluctuation is reduced, the recovery time is shortened, the power supply efficiency is improved, the stability is guaranteed by adopting multiple anti-interference design, peripheral elements are reduced, miniaturization is realized, the cost is reduced, fault diagnosis is realized, and the service life is prolonged.

The invention discloses a power grid power flow risk control method based on topology analysis, and relates to the technical field of power flow risk control, and the method comprises the following steps: obtaining first data of a power grid in real time, and constructing a node admittance matrix; when a switch displacement signal or distributed power supply power mutation is detected, topology reconstruction is carried out based on a node admittance matrix, and a dynamic topological graph is generated; establishing a fault current characteristic matrix based on the dynamic topological graph in combination with the bidirectional power flow characteristics of the active power grid; establishing an adaptive risk early warning model based on the dynamic topological graph and the fault current characteristic matrix, and outputting the overload probability and the voltage out-of-limit risk index of each branch; and performing analysis according to the branch overload probability and the voltage out-of-limit risk index, and generating a multi-target optimization control instruction set. Through adaptive topology adjustment, load flow calculation and a risk early warning model, automatic power grid optimization control can be realized, and in combination with convergence verification of a virtual impedance observer, effectiveness of topology adjustment and control operation is ensured.

The invention relates to the technical field of new energy grid-connected converter control, in particular to a grid-connected converter control method based on grid-following and grid-construction hybrid control, which flexibly adjusts the characteristic proportion of grid-following and grid-construction by constructing a self-adaptive hybrid synchronous control model, ensures the smooth and efficient grid-connected process, and improves the grid-connected efficiency. A voltage and current double-loop control model is constructed to accurately regulate and control output voltage and current, the high-standard electric energy quality requirement of a power grid for new energy power generation is met, meanwhile, power grid impedance estimation is introduced for virtual impedance control, and the anti-interference capability and the response speed of the system are further enhanced. In conclusion, according to the grid-connected converter control method based on grid following and grid construction hybrid control, the adaptability and stability of the system to the complex power grid environment are remarkably improved, and the overall operation efficiency and reliability of the system are improved.

The invention discloses a self-adaptive nanosecond driving protection method for a high-voltage IGBT power module. The method comprises the steps that data such as high-voltage side voltage, collector current, grid voltage and junction temperature are collected and preprocessed, and standardized feature vectors are obtained; extracting statistical features, frequency domain features and trend features to obtain a comprehensive feature vector; density clustering is carried out based on historical fault data, and an extreme value model is established by using generalized Pareto distribution to generate an optimized threshold value; constructing a time sequence feature matrix, predicting a fault probability by adopting a time sequence convolutional network and a long-short term memory network, and generating a protection strategy parameter; and generating an optimal driving waveform and a control signal, and updating parameters according to an actual response effect. According to the invention, predictive protection and nanosecond-level precise control of faults are realized, and the reliability and performance of the high-voltage IGBT module are remarkably improved.