1042 results about "Voltage stability" patented technology

The invention relates to the technical field of electrical equipment monitoring, in particular to a power distribution equipment state intelligent diagnosis system and method, and the system comprises a current fluctuation detection module, a voltage stability evaluation module, a heat effect diffusion analysis module, a fault point positioning module and an equipment state evaluation module. According to the invention, through extracting current change characteristics of key nodes and judging continuity of fluctuation differences, rapid identification of current anomalies can be realized, a voltage distortion region and a distribution range thereof can be positioned in combination with phase deviation and symmetry change of voltage waveforms, and the current anomalies can be identified based on a temperature gradient path and jump point screening. A hot spot diffusion trend and a thermal disturbance boundary can be described, morphological analysis and coordinate labeling are performed on the basis of multiple fault areas, multi-point concurrent positioning is realized, association between thermal disturbance and connection defects is identified in combination with temperature difference and current path change characteristics, fault diffusion trends and state disturbance blocks can be accurately presented, and the accuracy of fault diagnosis is improved. And the power distribution state identification and intervention efficiency is improved.

The invention discloses a game reinforcement learning-based reactive power dispatching method for an electric vehicle to participate in a power distribution network, and the method comprises the steps: collecting node voltage, line current, electric vehicle charging and discharging states and topological information, and constructing graph attention embedding; generating an initial reactive power regulation action in the multi-agent game reinforcement learning framework, and shaping and updating a strategy gradient through double rewards; the improved particle swarm is initialized according to the updating strategy gradient, and a self-adaptive inertia coefficient is set; iteratively searching according to the node voltage sensitivity, the line reactive margin and the expected convergence step number to obtain an optimized particle swarm; the particle speed is mapped to a main strategy network through online cooperative training, the inertia coefficient is synchronously adjusted, a cooperative optimization strategy is output, a reactive power dispatching instruction is generated, and the algorithm is updated in a closed-loop mode according to real-time feedback. According to the invention, rapid and cooperative reactive dynamic scheduling of an electric vehicle group is realized, and the voltage stability and the electric energy quality are remarkably improved.

The invention relates to the technical field of power distribution network operation optimization, and discloses an intelligent power distribution network distributed power scheduling system based on edge computing, which comprises a data acquisition and preprocessing module, an edge computing and local scheduling module, an SDN network control module, an application layer global scheduling module and a scheduling execution and control module, according to the invention, by introducing the edge computing node, local preprocessing of data and generation of a preliminary scheduling strategy are realized, delay of data transmission to the central server is significantly reduced, and the system can dynamically adjust the scheduling priority in combination with the improved particle swarm optimization algorithm, so that the scheduling efficiency is improved. Three core indexes of renewable energy utilization rate, power distribution network loss and voltage stability are comprehensively considered, and a more accurate and efficient local scheduling strategy is generated. And meanwhile, the SDN network control module ensures that high-priority data can still be efficiently transmitted when the network is congested by calculating a link priority coefficient, so that the real-time performance and the reliability of the system are further improved.

The invention relates to the technical field of intelligent control, in particular to an intelligent power optimization scheduling method in a new energy grid-connected scene, which comprises the following steps of: acquiring a current load, a rated load, an adjustment rate and a temperature rise value through a data interface, and normalizing to generate a characteristic parameter matrix; the product of the adjusting rate and the temperature rise value is used for calculating the correlation degree with the aging factor to obtain an elastic weight, extracting the voltage stability and the weight, inputting the voltage stability and the weight into a Dijkstra algorithm to screen a path meeting the safety margin, monitoring the slope of an inertia change curve, adjusting a compensation coefficient through fuzzy PID control, and feeding back the compensation coefficient to correlation degree calculation. According to the method, multi-source parameters are fused through a rule tree structure, the load regulation rate and the aging factor weight are dynamically distributed, bus voltage stability and elastic weight path optimization are combined, a synchronous inertia margin safety correction system is constructed, the system response precision, the state cooperation efficiency and robustness are improved, local optimum is avoided, and the system reliability is improved. And the standby capacity configuration and the frequency advance correction capability are optimized.

The present invention relates to the technical field of power distribution networks. Disclosed are a multi-energy storage power distribution network voltage regulation method and apparatus, and a device. The method comprises: establishing a voltage optimization model for a power distribution network, converting an energy storage constraint in the voltage optimization model of the power distribution network on the basis of physical information of an energy storage system, establishing a security model of the energy storage system, forming a training guide model of the energy storage system on the basis of a Markov decision model, training each energy storage system by using a TD3 algorithm, sharing network parameters obtained through training between different energy storage systems, and adjusting the voltage of the power distribution network. By means of optimizing an operation strategy of an energy storage system, the present invention realizes efficient and sustainable operation of the energy storage system. A charging and discharging strategy of the energy storage system is optimized by means of a DRL algorithm having shared parameters, improving voltage stability of the power distribution network, reducing energy loss, improving the overall efficiency of the system, enhancing the collaboration performance of multiple energy storage systems, and optimizing control of the energy storage system in an active power distribution network.

The invention discloses an asynchronous motor energy-saving monitoring and dynamic early warning method based on situation awareness, and relates to the technical field of asynchronous motor energy-saving monitoring. The method comprises the steps that S1, multi-source heterogeneous data are synchronously collected, power supply parameters and operation parameters are obtained in real time, and a frequency conversion working condition self-adaptive deviation value and a current stability coefficient are obtained; s2, generating four-dimensional situation factors including an overtemperature danger value, a current stability coefficient, a voltage stability coefficient and a frequency deviation value; s3, constructing a fourth-order transmission network, and generating a primary early warning signal based on the path mark combination; s4, calculating the motor efficiency in real time, triggering an efficiency abnormity mark, fusing the efficiency abnormity mark with the primary early warning signal, and reconstructing a final early warning instruction; and S5, executing hierarchical control according to the final early warning instruction. Through multi-parameter coupling and dynamic early warning transmission, the early-stage capture capability of the composite fault is improved, the early warning response delay is shortened, energy-saving optimization and fault protection of the motor are realized, and the method has a remarkable practical value.

The invention relates to the technical field of electric power operation and maintenance, in particular to a distributed optical storage unit cooperative scheduling control method and system, the method is applied to a distributed optical storage system comprising a plurality of optical storage units, each optical storage unit comprises a photovoltaic unit, an energy storage unit and a load unit, and is configured with a local unit controller. Comprising the following steps: collecting real-time operation data of an optical storage unit, and extracting local collaborative scheduling characteristics and a local DC bus voltage instantaneous fluctuation ratio from the real-time operation data; each unit controller inputs the corresponding local cooperative scheduling feature into a preset local scheduling strategy generation model, and outputs an initial scheduling action instruction set; and performing global voltage stability evaluation on the distributed optical storage system based on the local direct current bus voltage instantaneous fluctuation rates corresponding to all the optical storage units, and calculating to obtain a system voltage fluctuation index. The distributed local control capability and the global collaborative demand are organically fused, and the global voltage stability and the collaborative scheduling consistency are ensured.

The invention discloses a phase modifier unit state monitoring and load control method and system for reactive power compensation of a power grid, belongs to the technical field of automatic control of power systems, and mainly solves the problem that service life loss is aggravated or a control target is single due to the fact that the health state of equipment is not fully considered when an existing phase modifier unit responds to reactive power requirements of the power grid. The method comprises the following steps of: calculating reactive vacancy and extracting vibration frequency band energy characteristics by acquiring voltage and frequency of a power grid as well as vibration, temperature and exciting current signals of a unit in real time, and constructing a health state index HSI in combination with self-adaptive wavelet basis selection; taking minimum equipment life loss and optimal power grid voltage stability as multiple objectives, dynamically generating a load control instruction by adopting a particle swarm algorithm, realizing weight adaptive adjustment based on HSI, and introducing an online life loss model as a constraint condition; finally, reactive power output is adjusted through an excitation system, and cooperative control of power grid stability and equipment life extension is achieved.

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.

The invention discloses a protocol conversion and protocol self-learning method and system for transformer area optical storage and charging cooperation, and the method comprises the steps: constructing a digital twinborn body of a transformer area optical storage and charging system, carrying out the parallel operation of a protocol agent and a protocol agent in a virtual environment, and achieving the cooperative training of the protocol agent and the protocol agent through a hierarchical reinforcement learning architecture, the protocol agent is responsible for learning a dynamic priority scheduling and compression strategy for heterogeneous protocol messages such as Modbus, CAN and IEC 104, the protocol agent is responsible for learning a power balance and voltage stability control strategy based on photovoltaic output, energy storage SOC and charging load, and the two agents realize cross-domain collaborative optimization through a reward function mutual coupling mechanism. And finally, safely deploying the collaborative strategy obtained by training to the edge control equipment of the physical transformer area. According to the method, the problems of disjunction of protocol conversion and cooperative control, protocol strategy solidification, insufficient cross-domain cooperation and the like in the prior art are solved, and the operation efficiency and the self-adaptive capability of the transformer area optical storage and charging system are improved.

The invention discloses a response control method for a charging station participating in a low-voltage treatment scene, and the method comprises the following steps: S1, collecting the voltage data of a charging pile, calculating a deviation, and judging a low-voltage grade; s2, when the deviation is in a light interval, outputting reactive power support voltage in proportion; s3, when the deviation exceeds a heavy threshold value, reducing active power and starting V2G feedback; s4, constructing a graph structure model, and extracting inter-node power coupling and user behavior factors; s5, inputting the model into an improved prediction controller, predicting a future voltage state, and optimizing and outputting a current period power control value; s6, power adjustment is executed, and feedback power is slowly output in the V2G stage; and S7, comparing the control deviation with the behavior factor change, updating the node control priority, and feeding back for rolling optimization of the next period. According to the invention, while the charging regulation and control precision is improved, the user experience and the voltage stability are effectively considered, and the method is suitable for various low-voltage treatment scenes.

The invention provides a power supply control method for a prefabricated cabin type energy storage system, and the method comprises the steps: obtaining a turn-off signal trigger of a secondary output channel, and forming an initial voltage fluctuation data set; according to the initial voltage fluctuation data set, the influence degree of turn-off energy dissipation on a main output channel is analyzed, and specific parameters of a fluctuation interference source are determined; obtaining a turn-off frequency range of a secondary output channel and real-time data of response delay after turn-off, and judging an adaptive frequency adjustment interval; dynamically calibrating the voltage according to the judged frequency regulation interval to obtain a preliminarily stable voltage output curve; and through the final voltage stability regulation scheme, obtaining system response data after the secondary output channel is turned off, and determining voltage stability guarantee parameters under long-term operation.

The invention discloses a hydroelectric generating set speed regulation control method considering excitation coordination. The method comprises the steps that 1, system state information is collected and preprocessed; step 2, on-line identification of excitation speed regulation coupling characteristics; 3, decomposing a multi-time-scale control target; step 4, designing a self-adaptive multivariable controller; 5, working condition self-adaptive parameter optimization; step 6, intelligently inhibiting the water attack effect; 7, multi-machine cooperative reactive power optimization control is carried out; 8, optimizing and executing a control strategy in real time; the technical problems that excitation speed regulation dynamic coupling, multi-time scale response mismatch, multi-machine cooperative control and the like in a hydroelectric generating set control system cannot be comprehensively solved in the prior art are solved, and the regulation response speed and the system operation safety are improved while the frequency and voltage stability is ensured.

The invention discloses a power grid transient stability margin prediction method based on steady-state power flow and anticipated faults, and the method comprises the steps: carrying out the sample generation based on different operation conditions of a power system, an AC power flow, operation modes under different time sequences, and faults under N-1 and N-2 scenes; labeling the generated sample according to two transient stability margin evaluation indexes of power angle stability and voltage stability; the labeled sample data and the anticipated fault data after the embedded coding are combined to serve as input features to be input into a deep learning model and trained, and a trained deep learning model is obtained; and predicting the transient stability margin of the power grid according to the trained deep learning model, and judging the stable state of the power system. The transient stability evaluation sample generation method is provided, the steady-state power flow and the expected fault before the fault are considered, the transient stability margin prediction of the power grid is realized by using the deep learning model, and the transient stability margin prediction speed, precision and reliability are improved.

The invention relates to the technical field of power electronics and power system control, and discloses an intelligent control method and system for a multi-network converter, and the method comprises the steps: collecting the frequency deviation, the power change rate and the voltage amplitude of a power grid in real time, carrying out the filtering and feature extraction, and analyzing the coupling relation, thereby obtaining the parameter coupling strength. And if the intensity exceeds the threshold value, an inertia adjusting signal is generated through a fuzzy logic controller. And calculating a deviation correction value by combining the state evaluation response performance of the converter, and generating an optimization instruction by fusing the frequency deviation. And solving a voltage stability threshold based on the instruction, updating a coupling index, and issuing and executing after verification. And finally, updating the fuzzy rule base by adopting neural network iterative learning according to feedback data, and forming an inertia support frame with self-learning capability. According to the method, the inertia response speed and the operation stability of the multi-network converter system under high-proportion new energy access can be effectively improved, and adaptive cooperative control is realized.

The invention provides a photovoltaic access power distribution network voltage stability evaluation method, which comprises the following steps: acquiring ship docking time, staying duration and crane working frequency in a port area in real time, fusing obtained meteorological information, identifying a photovoltaic power generation output power change trend, and obtaining a daily power load peak-valley time period and a load fluctuation amplitude; according to the adjusted voltage value of each node, generating a switch operation instruction and a power adjustment instruction of the shore power supply equipment, identifying load abrupt change by executing the instructions, and determining a real-time power dispatching scheme by combining the power adjustment instruction and the ship arrival time; and according to the target voltage control value, determining the power utilization safety state of the port power distribution network, and evaluating the voltage stability of the photovoltaic access power distribution network through the operation data of the photovoltaic power generation access point.

The invention discloses a low-voltage power grid voltage fluctuation control method and system based on artificial intelligence. The method comprises the steps of obtaining a multi-source data set from a power grid; if the line loss estimation deviation in the multi-source data set exceeds a preset deviation range, iteratively optimizing a preset initial resource allocation scheme according to a multi-objective optimization algorithm to obtain a computing resource allocation scheme; obtaining final line loss distribution characteristics through task grading and parallel decoupling calculation according to a calculation resource allocation scheme; and generating a generator set output adjustment scheme according to the final line loss distribution characteristics, and regulating and controlling the power grid. According to the artificial intelligence-based low-voltage power grid voltage fluctuation control method and system provided by the invention, power grid data are integrated, line loss distribution is analyzed, and a voltage fluctuation trend is predicted, so that the output of a generator set is regulated and controlled, and voltage stabilization and line loss control are realized; therefore, the problem that effective control and line loss treatment are difficult to carry out on the power grid voltage fluctuation can be solved.

The invention discloses a mobile phone data line performance test and fault prediction method and system, and belongs to the technical field of electronic product detection and fault prediction. The power-on resistance, the voltage stability, the charging current response and the data transmission rate of a target data line are collected, and under the conditions of different bending angles, insertion and extraction cycles and environment temperatures, the data transmission rate of the target data line is calculated; acquiring stress response data, and extracting multi-dimensional stress principal component characteristics; the electrical property and stress data are fused, a performance degradation correlation model is established, and coupling modeling of data line internal structure damage and electrical property degradation is achieved; historical use data are input, analogue simulation is carried out through the model, and residual performance indexes are generated; judging whether a fault risk exists or not according to a set threshold value, and outputting early warning information if the fault risk is lower than the threshold value; meanwhile, a fault position and a mode type are inferred in combination with an internal characteristic spectrum of the model; the method has high prediction precision, strong structural adaptability and good expansibility, and is suitable for quality control and intelligent diagnosis of consumer electronic cable products.

The invention provides a mainboard power supply output voltage stability test method and system, and the method comprises the steps: generating a dynamic stepped load current based on a load demand parameter and a limit working condition defined by a hardware specification when a mainboard operates in a preset multi-mode switching state, and setting a first synchronization window before each step switching moment, setting a second synchronization window after the step switching time, collecting voltage waveform data, inputting the voltage waveform data into a preset filtering algorithm, extracting an overshoot amplitude and recovery time, constructing an asymmetric coupling model, and taking a difference value between the overshoot amplitude and a preset fluctuation range as a first stability index; the ratio of the recovery time to the response time threshold value is used as a second stability index, nonlinear weight distribution of the two indexes in multiple step intervals is calculated, a stability grade judgment result is generated in combination with a circuit board wiring impedance characteristic library, and the test compatibility of high-density mainboard multi-phase power supply and high-frequency devices is improved.

The invention provides a transient voltage stability control method and system based on transmission and distribution cooperation. The method comprises the following steps: constructing a power distribution network reactive power support capability quantification model; quantizing a reactive power support capability boundary in real time by solving a power distribution network reactive power support capability quantification model, and determining a reactive power support power feasible region capable of being provided; and based on a quantitative evaluation result, dynamically adjusting a reactive power interaction value between the power transmission and distribution networks by adopting an improved droop control strategy, and realizing power transmission network transient voltage stability control based on active support of the power distribution network. Power distribution is carried out according to the dynamic reactive power margin of the reactive power regulation equipment by considering the transient voltage support requirement of the power transmission network and the reactive power transmission loss of the power distribution network; and obtaining a reactive power regulation instruction, and coordinating reactive power resources at the power distribution network side according to transient voltage stability control and power distribution of the power transmission network to realize cooperative control. Based on the method, the invention further provides a transient voltage stability control system based on transmission and distribution cooperation. The optimal transient voltage support is provided for the power transmission network.

The invention relates to the technical field of voltage sensitivity photovoltaic stability regulation and control of a power distribution network, in particular to a multi-parameter photovoltaic grid-connected voltage stability control method, system equipment and a medium, and aims to improve the transient modeling precision by constructing a second-order equivalent transient model of a photovoltaic system and decoupling a mapping relation between phase-locked loop parameters and equivalent inertia and damping; quantifying a transient stability boundary under voltage disturbance based on a phase-locked loop sensitive parameter, and determining a photovoltaic power angle critical safety threshold; for the whole voltage fluctuation process, dynamically and cooperatively regulating and controlling phase-locked loop parameters according to the voltage and frequency of the power grid; equivalent damping and inertia suppression oscillation are enhanced in the voltage drop period, inertia acceleration recovery is reduced while high damping is maintained in the voltage recovery period, rated parameters are reset in the steady state, the transient stability of the system for coping with voltage sag is remarkably improved, and the risk of power angle instability is avoided.

The invention provides a photovoltaic energy storage system power distribution method, device and equipment and a storage medium, and the method comprises the steps: carrying out the combined prediction of photovoltaic power generation power and load power according to time sequence data, and generating a power generation power prediction value and a load power prediction value in a scheduling period; determining a power gap index according to the generated power predicted value and the load power predicted value, and determining a target power boundary interval in combination with a preset voltage stability limit value and a response rate upper limit of the energy storage unit; grouping and screening the equipment states of the energy storage units according to a preset response efficiency model and a power gap index to generate an energy storage unit set; and determining an output power amplitude range of the energy storage unit according to the energy storage unit set and the target power boundary interval, and determining a power output value of the energy storage unit in combination with the state parameter and the priority rule of the energy storage unit. According to the scheme, screening and power distribution are carried out on the energy storage units in a self-adaptive mode, and the energy storage resource utilization efficiency can be effectively improved.

The invention relates to the technical field of battery management, and particularly discloses a dynamic control method for an intelligent balance management system of a lithium battery module, which comprises the following steps of: acquiring load current of the battery module and end voltage signals of each monomer in real time; calculating instantaneous internal resistance and polarization voltage parameters of each single battery in real time; the terminal voltage is compensated in real time, and a purified open-circuit voltage signal is generated; fusing the charge state reference value with the current integral result, dynamically calculating a confidence index according to a current standing condition and voltage stability so as to perform adaptive weighting, and outputting a smooth charge state estimation value; calculating a balance urgency degree index by combining the estimated value, the real-time temperature and the inconsistency change trend, and generating a differentiated balance control instruction; an energy transfer path is established and controlled according to the instruction, the rate is dynamically adjusted in the process, and operation is terminated when the duration or state consistency condition is met; according to the method, the stability of state estimation and the accuracy, safety and efficiency of balance control under the dynamic working condition are improved.

The invention relates to the technical field of new energy automobile electric control, and discloses a self-adaptive voltage dynamic stability control method for a new energy automobile converter. The method comprises the following steps: acquiring a real-time voltage time sequence data sequence of the new energy automobile converter in an operation period; performing voltage disturbance characteristic analysis on the real-time voltage time sequence data sequence based on a rated voltage interval of the converter, and identifying voltage disturbance modal information of the converter; then, according to an embedded voltage control strategy library and a voltage stability threshold condition, an initial voltage regulation and control instruction sequence is generated in combination with voltage disturbance modal information of the converter; performing voltage change trend prediction on the voltage disturbance modal information of the converter to obtain predicted voltage disturbance modal information; performing voltage control compensation optimization on the initial voltage regulation and control instruction sequence based on the predicted voltage disturbance modal information to generate an optimized voltage regulation and control instruction sequence; and performing adaptive voltage regulation on the new energy automobile converter according to the optimized voltage regulation instruction sequence.

The invention discloses a power distribution network photovoltaic openable capacity dynamic evaluation method fusing voltage stability margin and neural network optimization, and aims to solve the problems that a traditional method does not fully consider dynamic stability and is low in calculation efficiency. Firstly, a prediction method combining kernel density estimation and quantile regression is adopted to accurately quantify the uncertainty of distributed photovoltaic output. The core innovation of the method is that on the basis of traditional security constraints, a static voltage stability margin (VDSM) is introduced as a key constraint condition, and a double-layer interval analysis model capable of guaranteeing the dynamic stability of a power grid is constructed. Secondly, in order to efficiently solve, the invention provides a framework of'neural network pre-screening + parallel optimization ': after a model is decomposed into optimistic sub-problems and pessimistic sub-problems through an interval decoupling technology, massive candidate solutions are quickly screened by utilizing a neural network model, so that a feasible solution space is greatly reduced, and the solution efficiency is improved; and carrying out parallel optimization solution on the sub-models in combination with an improved particle swarm optimization algorithm.

The invention provides a voltage stability control method for a multi-output switching power supply, which comprises the following steps of: sampling a main output channel in real time to obtain a voltage signal; the voltage signal is processed through a wide bandwidth error amplifier, a main channel adjusting signal is generated, and the main channel adjusting signal is used for driving a main power switch device; receiving an input voltage fluctuation frequency band of an auxiliary channel, a load current transient change gradient and a frequency spectrum coupling characteristic of a main channel adjusting signal through a dynamic prediction model, and generating an auxiliary channel adjusting signal with a phase lead compensation characteristic; a cross coupling active offset mechanism is constructed, time domain-frequency domain characteristics of coupling interference are extracted through a high-precision differential detection circuit, amplitude-frequency adjustable reverse correction signals are generated in real time through an adaptive compensation algorithm and injected into control nodes of an auxiliary output channel, and dynamic decoupling and ripple suppression are carried out. According to the method, high-stability control of multi-channel voltage under all working conditions is realized, and the dynamic response speed and the anti-interference capability are improved.

The invention relates to the technical field of power system safety analysis, in particular to a source-grid-load-storage integrated n-1 scene voltage safety analysis method, which comprises the following steps of: acquiring and preprocessing n-1 scene data; constructing a static voltage safety analysis model based on the gradient boosting regression tree; constructing a dynamic voltage safety analysis model based on a long short-term memory network; analyzing safety collaboration of the static voltage and the dynamic voltage; and verifying and optimizing the static voltage safety analysis model and the dynamic voltage safety analysis model. According to the method, the static voltage stability margin and the dynamic response characteristic are fused, so that the comprehensive risk identification accuracy is improved; a gradient boosting regression tree and a long-short-term memory network are adopted to capture nonlinear characteristics, and the voltage prediction error of an n-1 scene is remarkably reduced; characteristics and weights are customized for different source network load storage integrated project types such as industrial and incremental power distribution networks, and the pertinence and engineering practicability of analysis are improved.

The invention is suitable for the technical field of power electronics and power transmission, and provides a low voltage ride-through control method and system for a network construction type converter, and the method comprises the steps: carrying out the conventional VSG control according to a VSG control strategy, and continuously monitoring the difference between the voltage of a power grid and a set reference value, so as to judge whether a fault occurs or not; when it is detected that the power grid breaks down, homodyne control is carried out on an active power control ring and a reactive power control ring of the grid-forming type converter so as to fix the phase and the amplitude of the output voltage of the converter; calculating and injecting a positive sequence compensation voltage and a negative sequence compensation voltage according to the drop degree of the power grid voltage; and according to the predicted impact current value, dynamically calculating and inputting adaptive virtual impedance. The power angle and the voltage in the fault period can be ensured to be stable, transient overcurrent is effectively restrained, and large power fluctuation is not caused.

The invention relates to the technical field of bidirectional PCS, and discloses a bidirectional PCS converter multi-target power balance optimization method and system based on model predictive control. According to the method, real-time operation parameters are analyzed by using a first-order lag initial model, prediction of power disturbance in a plurality of control periods in the future is realized, power balance optimization is converted from passive response to active pre-judgment, and a linear time-varying prediction model is constructed, so that the real-time performance of power balance optimization is improved. According to the method, the evolution trajectory of the direct current bus voltage in a period of time in the future is predicted, the power balance optimization behavior is continuous and prospective through a rolling optimization mechanism of prediction, evaluation and preferential selection, and meanwhile, the three targets of ensuring voltage stability, reducing switching loss and suppressing current harmonic content are fused into power balance optimization, so that the power balance optimization efficiency is improved. The problems of control hysteresis and target singleness existing in a traditional control method are solved, and quick and accurate power balance control of the bidirectional PCS is realized.

The invention discloses a three-level flexible excitation dynamic regulation and control method and system for a large-scale hydroelectric generating set, and relates to the technical field of flexible excitation control of the large-scale hydroelectric generating set, and the method comprises the steps: setting a DC bus voltage, and initializing a mapping relation between a capacitor voltage and an excitation output level; collecting operation parameters of a machine end, constructing a disturbance identification model and outputting a disturbance level; the excitation voltage output gear is set according to the disturbance level, the capacitor voltage difference is controlled, and dynamic voltage sharing is achieved by modulating the midpoint duty ratio. According to the method, through setting a bus target voltage and constructing excitation voltage output mapping, in combination with a disturbance level identification mechanism and a dynamic voltage-sharing strategy, closed-loop linkage of disturbance perception-voltage regulation-voltage difference control is realized. According to the method, the identification precision of the system on light disturbance and strong disturbance is effectively improved, the voltage stability and capacitance symmetry of the excitation system are enhanced, the overshoot risk is reduced, and the control robustness and safety of the system under extreme working conditions are improved.