1606 results about "Power quality" patented technology

The invention discloses a computing power load stabilizing and energy-saving management system based on a flywheel energy storage system, and belongs to the technical field of energy storage and management, and the system comprises a data collection module which is used for collecting and calculating a real-time current harmonic spectrum of a cluster and server rack vibration data to generate an electric energy quality characteristic spectrum; the prediction modeling module is used for establishing a prediction model output computing power demand dynamic distribution matrix based on multi-dimensional space-time correlation; the optimization control module is used for analyzing a peak load phase in the power demand dynamic distribution matrix to generate a dynamic coordination control strategy; and the power execution module is used for executing the dynamic coordination control strategy to adjust the phase parameter of the reverse electromotive force of the flywheel so as to offset the voltage harmonic component of the server bus. Harmonic phase compensation is realized through dynamic reverse electromotive force modulation, the calculation load prediction precision can be effectively improved, and the energy utilization efficiency and the equipment operation reliability are remarkably improved.

The invention relates to the technical field of data processing, in particular to an intelligent analysis system for electric energy quality and read data, which comprises a data fusion module, a modeling module, an analysis module, a detection module, an optimization module and a control module. The data fusion module aligns data of an electric meter terminal, power grid monitoring equipment and an environment sensor through a sliding time window, and the analysis module calculates a power grid node loss transfer coefficient based on a graph neural network and fuses transformer no-load loss and line contact resistance parameters to generate a dynamic line loss evaluation matrix. And the detection module identifies the power consumption characteristic deviation degree through a random forest classifier, and generates a priority management strategy in combination with a multi-dimensional abnormal scoring model. The control module adaptively selects a communication protocol to execute a regulation and control instruction according to a network state, a heartbeat detection mechanism feeds back operation data of a governance device in real time, model parameters are driven to be iteratively updated, and dynamic cooperation of power supply quality optimization and line loss governance is achieved.

The invention relates to the technical field of intelligent power grids, and provides an intelligent operation centralized control center intelligent scheduling interaction method and system, and the method comprises the steps: generating a heat distribution gradient through environment noise filtering, reflecting the temperature field change of equipment, obtaining a voltage amplitude envelope through fundamental wave and harmonic wave separation, and monitoring the power quality; a current fluctuation coefficient is extracted by combining segmented deviation analysis to evaluate a line load state, and frequency fluctuation parameters are captured by using time domain statistics to track system stability. By constructing a dynamic association map, heterogeneous data such as thermodynamics, electrical quantity, load characteristics and synchronous states are mapped to power grid topological nodes, and a cross-dimension association relationship is established to realize whole-network state coupling analysis. An overload risk, a voltage out-of-limit probability and a system instability threshold are quantified through a hierarchical evaluation mechanism, a multi-target optimization constraint condition is formed, and finally a scheduling strategy considering equipment safety, economy and power supply reliability is generated. When the power system operates, intelligent scheduling is carried out according to the operation state of the power grid.

The invention relates to the technical field of power systems, in particular to a multi-dimensional network performance index evaluation system and method based on measured data of a new energy station. Comprising a data acquisition preprocessing unit; a multi-dimensional index construction unit; the weight adjustment unit dynamically adjusts the index weight according to the operation condition based on a fusion algorithm of an improved analytic hierarchy process and an entropy weight method; the performance evaluation model unit adopts a comprehensive evaluation model fused with a random forest algorithm to generate multi-dimensional performance scores and risk early warning; and the visual interaction terminal unit is used for displaying the evaluation result in real time and generating a trend analysis report. According to the invention, the three-dimensional evaluation system covering the static electrical parameters, the dynamic stability indexes and the harmonic pollution indexes is constructed, so that the limitation of single-dimensional evaluation in the prior art is broken through, and the extension of the network-related performance of the new energy station from local detection to full-dimensional coverage is realized; and the multi-scene evaluation requirements of the power grid on the steady-state operation, the transient response and the electric energy quality of the station are accurately matched.

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 electronics, in particular to a photovoltaic off-grid inverter control method and system, and the method comprises the following steps: applying a test signal to identify an output interaction characteristic parameter, predicting the power generation power through combining with weather and attenuation, calculating the power fluctuation, and adjusting a current control parameter set. And calculating voltage and reactive power compensation parameters to generate an inverter control instruction, and combining a temperature load prediction trend to adjust a power allowable value to obtain a predictive power calibration coefficient. According to the invention, by analyzing the output interaction characteristics, enhancing the perception capability of the inverter to the actual operation environment, combining with the prediction of the photovoltaic power generation amount, realizing the prediction and influence evaluation of the power fluctuation, improving the adaptive adjustment capability of the current control parameters, improving the output voltage and reactive power control precision by utilizing the interaction characteristics, and optimizing the electric energy quality; and through thermal management of multi-point temperature and load prediction, the operation safety is improved, the service life of equipment is prolonged, and the operation performance of the photovoltaic off-grid system in a complex environment is improved.

The invention belongs to the technical field of artificial intelligence, and relates to an artificial intelligence-based electric energy quality disturbance identification and positioning method, which comprises the steps of constructing an electric energy quality disturbance signal data set, performing segmented preprocessing on electric energy quality disturbance voltage data, enhancing time-frequency joint features and encoding disturbance sensitive areas. And constructing a deep learning model for power quality disturbance identification and positioning, and identifying and positioning the power quality disturbance. According to the invention, through adaptive denoising processing, boundary detection and multi-resolution time-frequency feature extraction, the identification precision and positioning precision of power quality disturbance are significantly improved; self-adaptive wavelet denoising and dynamic segmentation are combined, noise interference is effectively suppressed, and the edge characteristics of voltage sudden change points are kept; according to the dual-task sharing network, disturbance identification and positioning tasks are cooperatively optimized, so that the network can consider disturbance classification and time positioning at the same time; and through Bayesian reasoning, the system can output confidence estimation, provides credibility quantification of identification and positioning results, and effectively improves the reliability of the system.

The invention relates to the technical field of power electronics, in particular to a control method for a low-voltage intelligent reactive compensation system of a submerged arc furnace. Comprising the following steps: acquiring three-phase voltage, current, power factor, harmonic content and temperature parameters of the low-voltage side of the submerged arc furnace through a sensor network; the load fluctuation of the submerged arc furnace in the future 1-5 minutes is predicted based on a deep learning algorithm, and a compensation demand pre-judgment value is generated; according to a load prediction result and a real-time working condition, performing dynamic switching from three modes of fixed compensation, grouped switching and continuous adjustment; harmonic component dynamic tracking compensation is carried out by combining an active power filter (APF) and a static var generator (SVG); the system overvoltage, overcurrent and temperature parameters are monitored in real time, and a grading protection mechanism is triggered and fed back to the compensation strategy adjusting module. The invention provides a control method for a low-voltage intelligent reactive compensation system of a submerged arc furnace so as to improve the response speed of the system, prolong the service life of equipment and guarantee the electric energy quality of a power grid.

The invention relates to the technical field of electrical detection, in particular to an electricity meter load monitoring method and system based on an electric energy quality analyzer, and the method comprises the following steps: extracting three-phase voltage phase deviation characteristics in a disturbance period, combining with the comparison of a frequency band change trend and fundamental frequency power, recognizing an interference coupling section, and analyzing a jump frequency point; and outputting an ammeter load monitoring result. According to the method, the phase deviation angle of the three-phase voltage is extracted in the voltage disturbance period, and the cross-phase synchronization index is constructed, so that the synchronous response characteristics of different loads to disturbance can be accurately revealed, and the accuracy of load response attribution judgment is enhanced. On the basis of cross-phase synchronous analysis, a corresponding relation between frequency band characteristics and response attribution is constructed, so that load response subdivision has a phase difference identification capability and a frequency behavior calibration capability, and the discrimination robustness under a multi-source interference background is improved.

The invention discloses a power distribution network harmonic suppression and heat loss evaluation method and system, and relates to the technical field of electric energy quality optimization and heat loss evaluation, and the method comprises the steps: collecting a power distribution network signal, extracting harmonic features, and calculating the harmonic contribution degree of each load based on a harmonic power flow; cable additional heat loss caused by harmonic current is calculated, and cable temperature prediction is carried out based on a transient heat conduction equation; and dynamically adjusting parameters of the harmonic compensation device according to harmonic treatment and heat loss evaluation results, and optimizing load scheduling. According to the method, more accurate harmonic source identification and harmonic power flow calculation are provided, and the harmonic treatment accuracy is improved; in cable heat loss evaluation, eddy current loss modeling, heat conduction analysis and dynamic temperature prediction are introduced, so that the operation safety of the cable is enhanced; dynamic harmonic suppression optimization and load scheduling are combined, a closed-loop regulation mechanism is formed, the electric energy quality is improved, and meanwhile, the cable overheating risk is effectively avoided.

The invention provides an intelligent management method and system for photovoltaic energy storage equipment, and the method comprises the steps: analyzing the power fluctuation trend through monitoring the output power and environment parameters of the photovoltaic energy storage equipment in real time, and pre-judging the power fluctuation characteristics; according to the operation state parameters of the supercapacitor and the vanadium redox flow battery and the power fluctuation pre-judgment result, the power distribution proportion and the cooperative working mode of the energy storage element are determined; based on industrial load demand characteristics, an energy storage element is controlled to be flexibly switched between an active adjustment mode and a reactive compensation mode; and voltage regulation and harmonic compensation are realized by monitoring electric energy quality indexes of parallel connection points. According to the invention, the rapid response capability of the photovoltaic energy storage system to the industrial load can be effectively improved, the power supply stability and the electric energy quality are remarkably improved, the system power fluctuation is reduced, the utilization efficiency of the energy storage equipment is improved, and reliable clean energy support is provided for industrial users.

Provided in the present invention is a transformerless unified power quality conditioner, comprising a three-phase conditioner substructure, wherein each phase of the conditioner substructure can comprise an ANPC three-level converter and an output half-bridge module connected to the ANPC three-level converter. Also provided are a corresponding modulation method and system and a corresponding control method and system. Compared with existing voltage regulation apparatuses, the transformerless unified power quality conditioner and the modulation method and control method therefor provided in the present invention do not include a power-frequency transformer in the topology, but use a three-level converter to expand ports to realize voltage regulation, thus having the advantages of lower costs, smaller size, smaller footprint, lower loss, etc.

The invention discloses an output conversion system and method for a UPS (Uninterrupted Power Supply), and the system comprises a main power input end which is connected with a bridge rectifier through a first electromagnetic relay; the energy storage module comprises a super capacitor group and a parallel lithium battery group, and is coupled with the bus capacitor through a bidirectional DC / DC converter; the input end of the multi-path regulation and control module is connected with the bus voltage sensor, and the output end is connected with the switching execution unit through a second electromagnetic relay group; the dynamic switching unit comprises an I-GBT matrix and a reverse blocking diode array which are respectively connected with the inverter and the bypass circuit in parallel; and the real-time monitoring module is provided with a current harmonic analysis unit and a load break variable detection unit, and the output end of the real-time monitoring module is connected with the ADC port of the central processor. According to the invention, systematic improvement is realized in three dimensions of electric energy quality guarantee, equipment reliability and dynamic response capability through an original multi-path regulation and control architecture and a deep cooperative intelligent control strategy.

The invention discloses a self-adaptive switching system and method for power supply and distribution, and the system comprises a data collection module, an analysis module, a modeling module, a decision module, an execution module and an early warning module, and the data collection module generates a real-time monitoring signal; the analysis module performs dynamic weighted evaluation according to the real-time monitoring signal and generates an evaluation signal; the modeling module constructs a virtual model of the power supply system and generates an analog signal; the decision signal generates a control signal containing a path selection instruction; the execution module controls the semiconductor device to switch the physical connection state of the power supply according to the control signal and generates a switch feedback signal; and the early warning module forms an equipment health assessment result according to the switch feedback signal and an abnormal arc signal when the execution module switches the connection state and transmits the result to the decision module. The self-adaptive switching system for power supply and distribution can solve the problem that a traditional power supply and distribution switching system depends on a single threshold to judge the state of a power supply and cannot comprehensively evaluate the quality of electric energy.

The invention provides an electric energy quality device power smooth flexible capacity expansion method for a new energy access scene. The method comprises the following steps: acquiring three-phase voltage, current and power signals, obtaining standardized three-dimensional tensor data through multi-dimensional tensor spectrum projection decomposition, calculating a characteristic value and a characteristic tensor base, and generating a dynamic characteristic vector and a weight coefficient set; a multi-layer probability graph matrix is constructed, a feature mapping matrix and a hierarchical contribution coefficient are obtained through iterative calculation, a fluctuation feature tensor is constructed, and a multi-time scale prediction model is established; constructing a control manifold space and a measurement tensor, calculating a topological connection matrix, designing a multi-dimensional control law and performing stability optimization; and constructing an embedded feature matrix and an inter-module distance matrix, calculating a capacity expansion weight and a power distribution scheme, and performing spectral domain equalization control and grid-connected coordination control. According to the invention, the power smoothing effect is obviously improved, and the system capacity expansion flexibility is enhanced.

The invention provides an electric energy quality compensation method and system based on power electronics, and relates to the technical field of power grid dispatching, and the method comprises the steps: collecting the voltage, current, harmonic content, reactive power, three-phase unbalance degree and other real-time multi-mode data of a power grid, and extracting key frequency spectrum features through wavelet transform denoising and windowing interpolation Fourier transform; and constructing a power quality feature vector. A self-adaptive fuzzy logic algorithm and power grid operation parameters are combined, a threshold value of a power quality index is dynamically adjusted, a multi-stage optimization strategy is divided based on the number of standard-exceeding indexes and importance analysis, and a dynamic compensation priority and a compensation strategy are generated. An improved particle swarm optimization algorithm is introduced, an inertia weight is dynamically adjusted, a constraint penalty function is introduced, output parameters of a power electronic compensation device are optimized, and effective compensation of power quality is realized by taking minimization of total active loss as a target.

The invention discloses an electric energy quality comprehensive treatment method and device based on multilevel collaborative optimization, and belongs to the technical field of electric energy quality treatment of an electric power system. According to the method, voltage and current data of a power grid are collected in real time and multi-parameter monitoring is performed; processing the data by using an adaptive wavelet transform and singular value decomposition combined algorithm, extracting disturbance characteristics and identifying the type and position of a disturbance source; a multi-objective optimization function including harmonic suppression, voltage stabilization, three-phase balance and power factor improvement is constructed, a Pareto optimal solution set is solved, and an optimal solution is selected; and according to an optimization result, generating and executing a cooperative control strategy of each type of electric energy quality treatment equipment. Cooperative treatment of various electric energy quality problems and cooperative control of various treatment devices are realized, the accuracy, self-adaptability and economical efficiency of electric energy quality treatment are improved, and the reliability and stability of an electric power system are enhanced.

The invention relates to the technical field of micro-grid control, and discloses a micro-grid adaptive switching control method and system based on multi-source information fusion, and the method comprises the steps: obtaining the internal operation parameters of a micro-grid, and the state parameters of an external large power grid connected with the micro-grid; the internal operation parameters and the external large power grid state parameters are fused, and a real-time comprehensive operation state model of the micro-grid is constructed; based on the real-time comprehensive operation state model, adaptively determining a target operation mode of the micro-grid; and according to the target operation mode, generating and executing a smooth switching control instruction of the micro-grid. According to the method, the multi-source operation information of the large power grid inside and outside the microgrid is fused, the comprehensive operation state model is constructed in real time, the target operation mode is adaptively selected, and switching control is smoothly executed, so that efficient and stable switching of the microgrid between multiple modes such as grid connection and island can be realized, and the power supply reliability, the system stability and the electric energy quality are improved.

The invention provides a voltage control method based on dynamic cluster division of a high-permeability photovoltaic power distribution network, and the method comprises the steps: carrying out the Newton-Raphson method load flow calculation of a power distribution network power system based on the topological structure data of the power distribution network, line parameters, the access position of a photovoltaic inverter and energy storage equipment, and equipment parameter information, and constructing a comprehensive modular function; based on the comprehensive modularization function, according to the load capacity of each moment, taking the average load capacity as a standard, utilizing an improved artificial hummingbird algorithm to dynamically divide time segments of the clusters and selecting dominant nodes of each cluster; based on the dominant node, taking the minimum node voltage deviation and the minimum system loss as objective functions, and constructing a second-order cone programming model when a preset constraint condition is satisfied; and solving the second-order cone programming model by using a solver CPLEX to obtain the reactive power regulation quantity of the distributed photovoltaic inverter and the active power regulation quantity of the energy storage equipment, thereby improving the power supply reliability and the electric energy quality of the photovoltaic power distribution network.

The invention discloses a new energy electric vehicle ordered charging method considering multiple factors, which realizes ordered charging through a closed-loop framework of data driving, multi-objective optimization, intelligent scheduling and dynamic feedback based on multi-dimensional data such as user demand, power grid stability, economical efficiency and renewable energy utilization, and can improve the charging efficiency on the basis of meeting the charging demand of a user. Peak clipping and valley filling of power grid loads, efficient utilization of renewable energy sources and user charging cost optimization are achieved, power grid load fluctuation is reduced, the electric energy quality is improved, the renewable energy sources are utilized to the maximum extent, it is ensured that the requirements of new energy electric vehicle users are met, and meanwhile the economical efficiency and stability of a power grid are achieved. Meanwhile, through an intelligent scheduling system and load prediction, charging tasks are uniformly distributed to night valley periods, so that a power grid load curve is more stable, and the utilization efficiency of power grid resources is optimized; and meanwhile, through an intelligent algorithm and a big data technology, the charging demand prediction accuracy is improved, and charging scheduling is more intelligent and accurate.

The invention discloses a cooperative scheduling method for a zero-carbon park complementary energy storage system, and the method comprises the steps: enabling an electric energy quality index to be explicitly incorporated into an optimization target through multi-source resource dynamic modeling and scene prediction, and building a strong coupling relation between a physical constraint and a scheduling decision; the hierarchical execution mechanism gives consideration to global optimization and local quick response, realizes undisturbed switching under abnormal working conditions, forms a prediction-optimization-execution-feedback closed-loop control system, and can accurately describe physical connection and electrical characteristics of a park power grid by establishing a power distribution network equivalent model and acquiring topological parameters, thereby realizing the optimal control of the park power grid. And basic network data is provided for subsequent optimization. By determining the controllable resource set and completing topological mapping, the position and the regulation and control range of each device in the power grid can be determined, and mistaken sending or conflict of instructions can be avoided. An apparent power upper limit constraint and SOC dynamic model is established, overload operation of equipment can be avoided, the energy storage charging and discharging capacity can be accurately represented, and the performability of a scheduling scheme is ensured.

The invention relates to the technical field of electric energy quality monitoring and treatment, and discloses an electric energy quality abnormity traceability and purification strategy generation system, which comprises an electric energy acquisition module, a feature analysis module, an abnormity traceability module, a pollution evaluation module, a parameter optimization module and a strategy generation module. The electric energy acquisition module acquires waveform data of key nodes of a group network in real time and sets a monitoring interval; the feature analysis module decomposes the spectrum features to generate pollution feature vectors; the abnormity traceability module extracts a core index to establish a traceability rule; the pollution evaluation module identifies a propagation path and calculates a pollution index; the parameter optimization module deduces an optimal parameter generation deviation sequence; and the strategy generation module integrates the sequence to form a purification strategy. The system realizes accurate traceability and dynamic management of abnormities, improves analysis comprehensiveness and strategy intelligence level, and is suitable for power grid electric energy quality management and control.

The invention provides a light storage coordinated feed-in new energy microgrid power quality improving device and method, and relates to the technical field of microgrid distributed control. The light storage coordinated feed-in new energy microgrid power quality improving device comprises a series converter, a parallel converter, a battery energy management system and a direct current power supply unit. According to the optical storage coordinated feed-in new energy microgrid power quality improvement method, a prediction equation is established for a series converter to decouple a control target, and power grid current can be accurately compensated. An adaptive compensation control technique based on a VLLMS algorithm is employed for the parallel converter to generate a control signal for the parallel converter. A virtual inertia control strategy is provided for a battery energy management system, and inertia support is provided for a series converter and a parallel converter. And aiming at a non-ideal voltage condition, constructing a PB-SM compensation strategy of the new energy micro-grid power quality improving device based on optical storage coordinated feed-in.

The invention relates to the technical field of energy storage control, and discloses a cooperative control method and device for energy storage converters, and the method comprises the steps: carrying out the recognition and judgment of the strength of a power grid through employing an artificial intelligence algorithm based on the grid-connected point electrical parameters of a target energy storage converter, selecting a target operation mode, controlling each energy storage converter in a field to be switched to the target operation mode, the target operation mode comprises a network following mode or a network construction mode; and for each energy storage converter, if the system is disturbed, issuing a corresponding charging and discharging active power instruction to the energy storage battery according to the output of the energy storage battery in the energy storage converter and the SOC state. According to the invention, the power grid strength is intelligently judged based on the grid-connected electrical parameters, and the operation mode is automatically switched, so that the energy storage system can stably operate under different power grid conditions, the power quality can be improved by adopting a grid following mode in a strong power grid, and the system supporting capability is enhanced by adopting a grid construction mode in a weak power grid, and the overall power grid adaptability is improved.

The invention provides a grid-connected and off-grid seamless switching method and system for a network-constructed energy storage micro-grid, belongs to the technical field of grid-connected and off-grid switching, and realizes rapidity and stability of micro-grid mode switching through multi-stage cooperative control. The method comprises the following steps: a power grid state real-time monitoring stage: acquiring power grid short-circuit capacity, impedance angle, voltage amplitude, frequency and phase parameters through impedance spectrum analysis and phase-locked loop cooperative detection; a pre-synchronization-hybrid control-dynamic damping three-stage switching stage; a steady state maintaining stage: maintaining a system damping ratio gt through a multi-target cooperative controller; and in the whole switching process, the bus voltage fluctuation is less than or equal to 2%, and the frequency deviation is less than or equal to 0.1 Hz. According to the method, MPC pre-synchronization, hybrid control of dynamic weight, virtual impedance adaptive compensation and multi-target collaborative optimization are controlled through model prediction, so that the problems are solved, seamless switching is realized, and the quality of electric energy is improved.

The invention relates to the technical field of electric energy quality monitoring, and discloses an electric energy quality monitoring method and system for a low-voltage power distribution system, which are used for acquiring parameter fluctuation information in a dynamic power grid environment and performing data quality evaluation and adaptive adjustment. According to the method, feature extraction and systematic deviation correction are performed on the acquired power grid operation data, a parameter change trend prediction model is constructed, and the potential influence of future short-term power grid parameter fluctuation on the operation stability is analyzed. According to the prediction result, the service influence level is evaluated, the quality monitoring report is generated, and the monitoring precision improvement scheme is determined. By updating the complex scene adaptation module, adaptation to different power grid operation environments is achieved. The method can effectively improve the accuracy and prediction capability of power grid operation state monitoring, and provides important support for safe and stable operation of a power grid.

The invention discloses an intelligent charging pile core module based on a VIENNA structure, an electric energy quality management method, system and equipment and a storage medium, and belongs to the field of electric power system energy storage equipment.The intelligent charging pile core module based on the VIENNA structure comprises the steps that an integrated power conversion unit is constructed, the power conversion unit adopts a VIENNA rectifier topology, three-phase alternating current is converted into direct current, and the direct current is converted into direct current; a harmonic suppression structure linked with the control interface is arranged; state information in the operation process is collected and serves as input of the control strategy module; based on the state information, a modulation control instruction is generated in the control strategy module to drive the switching action of the power conversion unit; on the basis of the modulation control instruction, the switch control is executed, meanwhile, the direct-current side midpoint potential of the power conversion unit is synchronously adjusted, and the distribution of direct-current bus capacitor voltage is controlled; and identifying the current operation condition according to the state information, switching to a control template corresponding to the operation condition in the control strategy module, and generating a modulation control instruction.

The invention discloses a short-circuit power flow control device and a control method thereof, and relates to the technical field of power flow control, through mutual cooperation of a power flow adjusting unit, a reactive power coordination unit, a short-circuit blocking unit and a parallel compensation unit, specifically, the first end of the power flow adjusting unit serves as a first common connection point and is connected with a primary power supply connection end; the second end of the power flow adjusting unit serves as a second common connection point; the third end of the power flow adjusting unit is connected with the tertiary power supply connecting end; the second common connection point is connected in series with one end of the short circuit blocking unit through the reactive power coordination unit; the other end of the short circuit blocking unit serves as a third common connection point and is connected with the secondary power supply connection end; the parallel compensation unit is connected to any common connection point. By adopting the embodiment of the invention, the interconnection of the power grid can be realized with less equipment, multiple functions of power flow regulation, fault isolation and electric energy quality treatment are realized, and the operation reliability and stability of the power grid can be improved.

The invention discloses a TCM-mode-based Si-SiC hybrid power multi-phase staggered H-bridge converter structure and a control method thereof, according to the scheme, a three-phase staggered parallel topology of a two-phase low-frequency Si-IGBT bridge arm and a one-phase high-frequency SiC-MOSFET bridge arm is adopted, and a TCM control strategy is combined, so that zero voltage switching (ZVS) of a Si device is successfully realized, the switching loss is remarkably reduced, and the switching efficiency is improved. The system efficiency is greatly improved; and meanwhile, through pilot frequency interleaving and ripple compensation technologies, total output current ripples are greatly reduced, and optimal balance between system performance and manufacturing cost is realized while the power capacity of the converter is remarkably expanded and the dynamic response speed and the output electric energy quality are improved.

The invention relates to the technical field of energy storage converter control, and discloses a dynamic voltage regulation and control method and system for an energy storage converter, and the system comprises a data collection module and an evaluation management module. According to the system, voltage change data and current change data are acquired through a data acquisition module and classified to form a data set, and an intelligent management module sets a monitoring period, analyzes the change trend of each phase voltage instantaneous value, generates a corresponding fluctuation data set, quickly locates a problem source, monitors the waveform of each phase voltage amplitude in real time, and generates corresponding monitoring data. The energy storage converter can adapt to power grid systems or energy storage devices of different scales, the intelligent management module analyzes deviation loss of electric energy in each conversion process and accurately evaluates the energy conversion efficiency of the energy storage converter in a rectification / inversion mode, the integration evaluation accuracy is high, the intelligent management module judges the power grid electric energy quality and harmonic distortion problems, and the energy conversion efficiency of the energy storage converter in a rectification / inversion mode is improved. And corresponding regulation and control suggestions are output, and the dynamic regulation and control response speed is high.