1239 results about "Power quality" patented technology

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 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 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.

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 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 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 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 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 provides an APF and SVG cooperative control-based electric energy quality comprehensive treatment system, and belongs to the technical field of intelligent power grid industry and electric energy quality comprehensive treatment, and the system comprises the steps of obtaining a power grid current signal and a voltage signal, and detecting a harmonic component and a voltage deviation through a harmonic detection module; a collaborative decision controller is adopted to determine a compensation strategy according to the harmonic component and the voltage deviation, and compensation tasks of an active power filter channel and a static var generator channel are distributed; harmonic compensation current is generated through an active power filter channel, and high-frequency harmonics are suppressed; reactive compensation current is generated through a static var generator channel, and voltage fluctuation is stabilized; and the compensation current is filtered through the filtering module and is output to a power grid. The electric energy quality comprehensive treatment system can effectively inhibit power grid harmonic waves, stabilize voltage fluctuation and improve electric energy quality, and is suitable for a complex power grid environment.

The invention belongs to the technical field of new energy power generation and grid connection, and particularly relates to a wind power plant electric energy quality optimization method and system based on an improved particle swarm algorithm. Aiming at the problems of voltage fluctuation, frequency deviation and high harmonic content during grid connection of a wind power plant, a wind power plant simulation model is built through Matlab / Simulink, a multi-target fitness function is built according to the voltage deviation, the frequency deviation and the total harmonic distortion (THD), the self-adaptive inertia weight and learning factors of a particle swarm optimization algorithm are improved, and a wind power plant grid connection model is built. And dynamically adjusting voltage adjustment gain, reactive compensation amount and filter parameters. According to the embodiment, compared with a traditional method, the number of iterations is reduced by 40%, the voltage fluctuation suppression ratio is improved by 10%, the frequency adjusting time is shortened to be within 0.3 second, the THD is reduced to 2.1% from 5.2%, and the power grid stability and the electric energy quality are improved.

The invention belongs to the technical field of novel power system photovoltaic and energy storage system optimization configuration, and discloses an optical storage system optimization method based on carbon emission and line loss rate collaborative modeling, which comprises the following steps: constructing a double-layer planning structure of an upper layer planning model and a lower layer operation model, a carbon emission calculation model and an improved line loss rate calculation model are introduced into the lower layer, joint optimization of configuration and operation is realized through parameter coupling, and the charge and discharge efficiency loss power consumption of the energy storage device is introduced as an independent parameter in line loss rate calculation, so that the line loss calculation precision is improved; and solving by adopting an improved particle swarm optimization algorithm, and objectively sorting candidate schemes in combination with an information entropy method and a TOPSIS comprehensive evaluation method. A simulation result based on an IEEE33 node power distribution system shows that the model can effectively reduce carbon emission and line loss rate, improves node voltage level, and has good convergence and engineering applicability.

The invention relates to the technical field of intelligent monitoring and fault diagnosis of a photovoltaic power generation system, in particular to a photovoltaic grid-connected box electric energy quality monitoring system based on data acquisition of the Internet of Things. Comprising an environment perception and time domain synchronization unit which is used for triggering sampling by using a unified clock source and generating a full-dimensional synchronous original data stream; the ideal reference physical reconstruction unit is used for calculating a theoretical output amplitude envelope and generating an ideal state reference vector; the fault mechanism parameterization evolution unit is used for converting the fault mechanism into a fault operator, selecting a high-risk fault mode according to the current operation condition, and superposing the corresponding fault operator onto the ideal state reference vector to generate a theoretical damaged state waveform; the double-rail-difference manifold extraction unit is used for obtaining a real residual vector and a theoretical fault residual vector; and the isomorphic feature coupling judgment unit is used for calculating the similarity between the real residual vector and the theoretical fault residual vector. According to the invention, the robustness of power quality monitoring under complex meteorological conditions is significantly improved.

The invention relates to the technical field of electric energy quality management of an electric power system, and discloses an industrial power grid voltage fluctuation suppression method and system, and the method comprises the steps: firstly building a system-level voltage and current forward transmission model composed of a power unit, a filter circuit and power grid impedance which are cascaded; reversely constructing a feedforward controller based on a voltage and current forward transfer model, and generating a main compensation voltage instruction according to the power grid disturbance quantity detected in real time; state parameters of each power unit are obtained, a differential equation is constructed, and a comprehensive real-time health degree index is obtained through fuzzy reasoning; dynamically correcting an equivalent impedance parameter in the forward transfer model by using the index, and calculating a voltage distribution weight of each unit; and decomposing the total compensation voltage instruction into each unit modulation signal according to the weight. Through systematic modeling, intelligent state evaluation and dynamic fault-tolerant distribution, high-speed, accurate and high-reliability suppression of the voltage fluctuation of the industrial power grid is realized.

The invention discloses an SVG-based photovoltaic grid-connected reactive power compensation method and system, and relates to the technical field of photovoltaic grid-connected compensation, and the method comprises the steps: monitoring the output power fluctuation of a photovoltaic array, and building a first electrical parameter feature vector; photovoltaic grid-connected impedance fluctuation characteristics are monitored, and a second electrical parameter feature vector is established; extracting a dynamic harmonic component and a reactive demand spectrum; generating a dynamic adjustment instruction set of SVG trigger pulse phase-amplitude according to the dynamic harmonic component and the reactive demand spectrum; and issuing the dynamic adjustment instruction set to a carrier phase shift controller of the SVG power unit for grid-connected interleaving compensation modulation. The technical problems that in the prior art, due to output power fluctuation and impedance change, harmonic waves of a photovoltaic grid-connected system are difficult to restrain, and then the electric energy quality is poor, and the system operation stability is insufficient are solved, and the technical effects that optimal modulation of SVG trigger pulses is achieved, and the electric energy quality and the operation stability of the photovoltaic grid-connected system are improved are achieved.

The invention discloses a switching control method and system for a photovoltaic inverter and a capacitor in a power distribution network. The method comprises the following steps: establishing a dynamic voltage sensitivity matrix according to operation data of a plurality of observation nodes in a power distribution area; predicting a reactive power demand value by adopting a rolling time window mechanism and a deep learning model; obtaining a virtual reactive power compensation amount according to the available capacities of all the reactive power compensation devices, optimizing a matching relationship between the reactive power demand value and the virtual reactive power compensation amount, and obtaining an optimal device combination mode between the reactive power demand value and the available capacities of the reactive power compensation devices; and determining a final switching strategy according to the optimal equipment combination mode, the multi-dimensional switching decision factor and the hierarchical switching strategy so as to perform cooperative switching control on the photovoltaic inverter and the capacitor. According to the invention, through accurate cooperative switching control of the photovoltaic inverter and the capacitor, the real-time performance, accuracy and flexibility of reactive power adjustment can be improved, so that the electric energy quality and stability of a power distribution network are improved.

The invention relates to the technical field of micro-grid control, in particular to a source-grid-load storage and charging integrated control method and system based on a micro-grid, and the method comprises the steps: considering the current SOC, health state and charging and discharging rate of a battery energy storage system, and evaluating the available capacity and charging and discharging capability of the battery energy storage system; according to the predicted charging load curve, the photovoltaic output curve and the energy storage state evaluation result, taking peak load shifting, photovoltaic consumption and charging station power supply guarantee as targets, generating a scheduling strategy by using an optimization algorithm, and determining a power distribution relationship among a photovoltaic system, a battery energy storage system and a charging station in each time period; and executing a scheduling strategy generated by the energy management module through three stages of regulation and control units, wherein the three stages of regulation and control units are respectively used for limiting grid-connected power fluctuation of the micro-grid, optimizing local energy distribution and island switching, regulating active power and reactive power and carrying out harmonic suppression. And stable operation of the micro-grid and stability of electric energy quality are ensured.

The invention relates to the technical field of power distribution network electric energy quality optimization, and discloses a distributed energy access power distribution network electric energy quality optimization method and system, and the method comprises the steps: collecting distributed energy output and power grid node voltage data in real time, and quantifying the system discordance state through calculating the volatility and dispersion; performing multi-unit preliminary time sequence coordination based on the state, and determining an output time sequence; node estimated voltage is obtained through load flow calculation, the harmonic level is evaluated, and an amplitude optimization process is triggered; constructing an optimization model by taking harmonic suppression and voltage stabilization as targets, fitting a nonlinear relationship between output and voltage / harmonic, generating a constraint set, and solving to obtain a final output amplitude sequence; and integrating the time sequence and the amplitude sequence, and generating a cooperative control instruction. According to the method, voltage fluctuation and harmonic pollution are effectively suppressed, and the electric energy quality and the operation stability of the power distribution network under high-proportion distributed energy access are improved.

The embodiment of the invention discloses a collaborative optimization method and device for the power quality of a high-permeability transformer area. The method comprises the following steps: acquiring three-phase voltage, three-phase current and environment temperature data; the voltage deviation, the three-phase unbalance degree, the total harmonic distortion rate and the reactive vacancy of the high-permeability transformer area are calculated based on the three-phase voltage and the three-phase current; taking voltage deviation as a primary optimization target, considering optimization of three-phase unbalance degree, total harmonic distortion rate and reactive vacancy, constructing a multi-target optimization function, and carrying out dynamic constraint on an optimization process based on environment temperature data; solving the multi-objective optimization function by adopting an optimization algorithm to obtain a group of optimal decision variables, and converting the decision variables into corresponding control instruction sets; and the control instruction set is issued to the on-load voltage regulating transformer, the reactive compensation equipment and the power electronic compensation module for execution. Therefore, the problems of voltage out-of-limit, harmonic pollution and imbalance are effectively solved through a multi-target cooperation and temperature self-adaption mechanism.

The invention discloses a synchronous generator excitation method based on mathematical modeling and gain scheduling, and relates to the technical field of synchronous generator control, and the method comprises the steps: building a synchronous generator global dynamic mathematical model comprising the electromagnetic dynamic characteristics of a stator winding, a rotor winding and a damping winding through a modeling module; a discretization simulation platform is constructed in a Matlab / Simulink environment by utilizing a simulation module, model parameters are corrected, dynamic adjustment is realized through a gain scheduling excitation controller, an automatic voltage regulator (AVR) adopts PID (Proportion Integration Differentiation) control and comprises a voltage deviation integral separation strategy, and a power system stabilizer (PSS) dynamically adjusts parameters of a lead-lag compensator based on active power. According to the method, the deviation between a model and an actual system can be reduced by more than 30%, the electromechanical oscillation damping ratio within the rated power range of 10%-150% is increased by 25%-40%, the harmonic content of exciting current is reduced to be lower than 5%, the stability of an electric power system and the electric energy quality are remarkably improved, the engineering practicability is high, and the method is easy to transform and upgrade on an existing synchronous generator.

The invention provides an electric energy quality on-line monitoring device and a cloud platform cooperation system, and relates to the technical field of electric energy quality management, and the device comprises a signal collection unit which obtains three-phase voltage and current signals in parallel through a Rogowski coil and a capacitive voltage divider; the event detection unit is used for synchronously executing harmonic spectrum analysis and transient event capture by adopting a parallel processing architecture realized by an FPGA (Field Programmable Gate Array); the edge processing unit is connected with the event detection unit, and is configured to encode the transient event features into a Gramer angle field image and compress steady state data into feature vectors; the multimode communication unit comprises a 4G / 5G wireless module and an optical fiber Ethernet interface; and the strategy execution interface outputs a treatment instruction to the compensation device through the D / A converter and the current loop. Through collaborative innovation of the device and the cloud platform, the power quality monitoring and treatment efficiency is remarkably improved.

The invention discloses a non-contact power supply three-stage control system based on series redundancy, and belongs to the field of non-contact power supply control. Comprising a power correction module, a voltage conversion module, a full-bridge inversion module, a cooperative control module, an analysis adjustment module, a monitoring switching module, a simulation maintenance module, a communication security module, a remote interaction module, an energy efficiency optimization module and a diagnosis recording module. High conversion efficiency can be dynamically kept under different loads and working conditions, energy loss is reduced, electric energy quality is remarkably improved, damage and misoperation under abnormal working conditions are prevented, high-reliability continuous power supply is achieved, PID parameters can be dynamically adjusted or direct control quantity can be generated, the system adapts to complex and changeable operating environments, and failure rate and shutdown loss are reduced.

The invention relates to the technical field of power quality monitoring, in particular to a method and system for constructing a power quality disturbance recognition model based on multidimensional data, and the method comprises the steps: obtaining voltage and current waveform data and environmental parameter data of a key node of a power transmission line, carrying out the hardware defect self-inspection and phase compensation of the voltage and current waveform data, and obtaining a power quality disturbance recognition model; clean transmission electric energy data is obtained; and performing multi-scale noise suppression and time sequence correlation analysis on the clean transmission electric energy data, and constructing a high-fidelity disturbance sequence. According to the method, through the hardware defect self-inspection and phase compensation steps, denoising preprocessing is carried out by utilizing wavelet packet transformation, the frequency response deviation of equipment is identified through Fourier transformation, a frequency domain interpolation method is adopted to reconstruct a frequency-closed defect mark segment, the phase deviation error can be accurately compensated, and the detection accuracy is improved. And self-systematic errors of hardware are eliminated from a data acquisition source, high fidelity of clean transmission electric energy data used for subsequent analysis is ensured, and a foundation is laid for high-precision identification.

The invention discloses an electric energy quality data monitoring method, and relates to the technical field of electric power system monitoring and analysis, and the method comprises the following steps: S1, obtaining an original voltage and current waveform set; s2, performing time-frequency domain decomposition by using the waveform set; s3, performing feature fusion by using the feature component set; s4, performing time serialization by using the electric energy quality index set; and S5, performing multi-dimensional structured integration by using the time sequence index data. By setting a voltage and current characteristic component coupling mechanism, unified expression of voltage and current characteristics can be ensured on an original signal level, and fine-grained description of electric energy quality characteristics is realized in an index calculation link, so that the problems of data dimension separation and insufficient index precision in the prior art are effectively solved. The method not only improves the comprehensiveness and reliability of the electric energy quality monitoring result, but also lays a solid data foundation for subsequent time serialization and structuralization integration.

The invention relates to the technical field of energy management, and provides a park light storage and charging energy distribution control method and system, and the method comprises the steps: transmitting an instruction to an energy storage system in an emergency, enabling the energy storage system to release an electric energy pulse to a micro-grid at the maximum available power within a preset time, and enabling the micro-grid to be in the maximum available power; providing time buffer for the power reduction process of the load units in the park; after the power reduction instruction is executed, identifying response characteristics of each load unit in the park to the power reduction instruction, and grading each load unit according to the response characteristics to obtain grading information; during the time buffering period, according to the grading information of the load units, a grading decreasing load reduction plan is formulated and executed, and a reduction instruction is issued in a peak shifting manner, so that the overall load is smoothly reduced; and continuously monitoring the power quality of the micro-grid, and finely adjusting the output of the energy storage system according to the power quality of the micro-grid. The method has the effect of improving the stability and reliability of light storage and charging in the park.

The invention is suitable for the technical field of data processing, and provides a new energy station voltage and frequency coupling cooperative control performance online evaluation method, which comprises the following steps: acquiring a three-phase voltage signal, a frequency signal, a unit output power signal and a power grid dispatching instruction signal of a new energy station grid-connected point, and calculating a voltage and frequency coupling characteristic matrix; performing collaborative quantitative analysis to generate a collaborative parameter matrix; performing control performance evaluation on the collaborative parameter matrix based on the collaborative evaluation network structure to generate collaborative evaluation parameters; constructing a dynamic coupling constraint function, and calculating to obtain a collaborative stability boundary representing the operation state of the station; and dynamically correcting the collaborative evaluation parameters to generate a station control performance optimization sequence. And the safety, the stability and the electric energy quality of the operation of the new energy station are effectively improved.

The invention relates to the technical field of low-voltage single-phase energy storage, and discloses a low-voltage line single-phase distributed energy storage system and a control method thereof.The energy storage system comprises a control system and a plurality of distributed independent energy storage systems, and each independent energy storage system comprises a controller, a converter and an energy storage unit; the controllers are respectively connected with the converters and the energy storage units, the energy storage units are connected with the single-phase low-voltage lines through the converters, the controllers are in communication connection with the control system, and the control system controls the converters to charge and discharge electric energy according to the power grid environment where the energy storage units are located. The safety detection of each independent energy storage system is realized through a single battery self-checking device and a system self-checking component of each independent energy storage system, the charging and discharging states of each battery are safely controlled, and each independent energy storage system realizes precise voltage support and flexible energy buffering through single-phase independent regulation and control; dynamic optimization of single-phase electric energy quality is realized by adopting a power control strategy, and the technical blank of traditional centralized energy storage in the field of single-phase electric energy regulation and control is filled.

The invention, which relates to the technical field of distributed power generation, discloses a modularized distributed photovoltaic inverter cluster intelligent regulation and control system comprising an impedance identification module, an impedance control module, a state sensing module, a fault diagnosis and isolation module, a power distribution module and a cluster fault control module. The power grid impedance monitoring module is used for monitoring voltage and current signals of a grid-connected point of the photovoltaic inverter, calculating a power grid equivalent impedance value, an impedance change trend and a harmonic component proportion of the current photovoltaic inverter, and generating power grid impedance information. The impedance identification module and the impedance control module are arranged, adjustment is carried out based on the virtual impedance parameters, the resonance problem caused by power grid impedance fluctuation is effectively suppressed, the situation that grid-connected current distortion affects the electric energy quality is avoided, the photovoltaic inverter cluster stably operates in a power grid impedance change scene, and the power grid impedance change efficiency is improved. And the cluster grid-connected power quality and the adaptability to the power grid environment are improved.