2017 results about "Grid connection" patented technology

An available transfer capability evaluation method and apparatus for a multi-region power system, belonging to the technical field of new energy grid connection. The method comprises the steps: in view of multi-dimensional uncertainty of new energy output and a load demand, on the basis of a conditional generative adversarial network method, determining a typical daily source-load scenario set; constructing an initial operation point set on the basis of the typical daily source-load scenario set, and determining a limit operation point of a multi-region power system; on the basis of the initial operation point set and the limit operation point, constructing an ATC evaluation model on the basis of safety indexes of multi-region power grid operation; and, on the basis of the ATC evaluation model and the typical daily source-load scenario set, determining available transfer capability probability distribution of the multi-region power system.

The invention discloses a non-impact grid-connected recovery method, system and device for a coal mine isolated network power supply system and a medium, and belongs to the technical field of non-impact grid-connected recovery of power supply systems, and the method comprises the steps: monitoring the operation state of an isolated network, and obtaining voltage, frequency and phase parameters; preparation before grid connection is executed, and main network parameter confirmation and equipment verification are completed; performing parameter synchronous adjustment based on the controller to complete dynamic matching of voltage, frequency and phase; pre-synchronization control is implemented to realize phase prediction and power pre-balance; executing closing operation and performing impact suppression; carrying out stability regulation and control after grid connection, wherein the stability regulation and control comprise oscillation suppression and smooth load loading; and when grid connection is abnormal or fails, an emergency processing branch is entered, and standby power supply switching or island splitting control is triggered. Through multi-dimensional synchronous control, impedance reconstruction and hierarchical coordination mechanisms, high-precision and low-impact grid connection of multiple energy units under extreme working conditions is realized, and the grid connection stability and success rate of a coal mine isolated network power supply system are remarkably improved.

The invention relates to the technical field of hybrid inverters, and discloses a hybrid inverter supporting reactive compensation and a control method thereof, and the hybrid inverter comprises a DC input unit, a three-phase full-bridge inversion unit, a grid-connected switching unit, a signal acquisition unit and a digital control unit. The direct current input unit comprises a photovoltaic interface, a battery interface and a direct current bus and is used for converging photovoltaic and energy storage electric energy; the three-phase full-bridge inversion unit is composed of a power device and an LCL filter and converts direct current into alternating current. The grid-connected switching unit comprises a static switch and an isolation transformer and is used for controlling power grid connection; the signal acquisition unit detects voltage and current signals; and the digital control unit judges a grid-connected mode or an off-grid mode according to the signal, calculates a reactive current reference value and generates a PWM (Pulse Width Modulation) control signal so as to realize reactive compensation control in the grid-connected mode and the off-grid mode. According to the invention, reactive power compensation capability is provided in both grid-connected and off-grid operation modes, and stable operation of the inverter in various working conditions is ensured.

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 invention belongs to the technical field of electric power system information processing, and particularly relates to an electric power information analysis method based on big data, through semantic fusion of multi-source heterogeneous data and dynamic feature mining of a time sequence attention mechanism, in a load prediction scene, compared with a traditional single data source model, the electric power information analysis efficiency is improved. After the meteorological data, the user power consumption behavior data and the power grid operation data are fused, the prediction average error rate is reduced; in an equipment fault early warning scene, through multi-dimensional correlation analysis of vibration signals, oil temperature data and environmental factors, transformer latent faults can be early warned in advance, and the fault identification accuracy is improved; meanwhile, a self-adaptive modeling engine and a closed-loop feedback mechanism enable the system to have a self-evolution capability: when the power grid topology is adjusted or the new energy grid-connected proportion is changed, the model does not need to be manually retrained, and self-adaptive adaptation can be completed in two scheduling cycles through dynamic feature weight adjustment and meta-learner parameter optimization, so that the analysis performance is maintained to be stable.

The invention relates to the technical field of new energy, and particularly discloses a new energy short-term intelligent optimization scheduling method under high-proportion new energy grid connection, and the method comprises the steps: data collection and preprocessing, multi-source data fusion prediction, hierarchical supply and demand balance, distributed collaborative optimization, and real-time regulation and feedback. According to the scheme, a multi-time-scale hierarchical supply and demand balance mechanism is adopted, fine management of different scheduling targets is achieved, the supply and demand relation is coordinated in combination with a dynamic weight adjustment mechanism, key load requirements are met preferentially, economy and stability are considered, and meanwhile the real-time performance and adaptability of scheduling decisions are improved; a distributed collaborative optimization structure is designed, the adaptability and robustness of a scheduling system to operation environment changes are effectively enhanced, a global scheduling problem is decomposed into a plurality of regional sub-problems, parallel solution and asynchronous update are achieved, the scheduling efficiency and the computing resource utilization rate are improved, and the requirements for real-time performance and high concurrency of large-scale new energy grid-connected scheduling are met.

The invention belongs to the technical field of optical storage cooperative control, and discloses a new energy grid-connected optimization control method based on an energy storage system, which comprises the following steps: collecting a power grid impedance fluctuation amplitude, a harmonic distortion rate and environment temperature data, obtaining an initial SOC value, correcting the SOC value, calculating an adjustable power margin and a response delay parameter of a photovoltaic unit, and calculating the optimal power grid impedance fluctuation amplitude and the optimal power grid impedance fluctuation amplitude. Generating an efficiency responsibility table; constructing a response cluster, generating a frequency modulation task package, and further generating a three-dimensional efficiency mapping table; the inertia demand is dynamically calculated in combination with the power grid frequency change rate, a responsibility transfer strategy is automatically activated in a high-altitude and high-temperature scene, and an efficiency instruction set is generated; analyzing response deviation by simulating typical disturbance of a high-altitude weak power grid scene, positioning a deviation source in combination with historical data, and dynamically adjusting an efficiency weight correction factor; and updating a responsibility allocation rule of the efficiency responsibility table, disrupting the low-efficiency cluster, and recombining the high-adaptability unit.

The invention relates to the field of electricity transaction, in particular to an electricity transaction intelligent algorithm platform based on block chain consensus. The method comprises the following steps: acquiring a real-time green electricity encrypted data set, uploading the real-time green electricity encrypted data set to a block chain node, and generating an unactivated digital green certificate data set; based on the non-activated digital green certificate data set, generating a grid-connected verification instruction, updating the non-activated digital green certificate data set to a tradable state, and generating a tradable digital green certificate data set; obtaining a power grid dynamic parameter set, and generating a green certificate time pricing data set through a space-time right dynamic pricing strategy based on the power grid dynamic parameter set and the tradable digital green certificate data set; and according to the green certificate time pricing data set, the digital green certificate is cancelled after verification in the power utilization process of the user, and a green power consumption traceability report is output. In the green electricity transaction process, fair and orderly development of the green electricity transaction market is promoted.

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 an optimal scheduling method for grid connection of a power distribution network and a distributed power supply, and particularly relates to the technical field of optimal scheduling, which comprises the following steps of: determining employment performance information during grid connection of the distributed photovoltaic power supply according to the difference between real-time and historical solar photovoltaic output models; based on charge state data of an energy storage system connected with the distributed photovoltaic power supply, determining energy storage performance information during grid connection of the distributed photovoltaic power supply, determining a grid connection strategy of the distributed photovoltaic power supply, and determining a grid connection strategy of the distributed photovoltaic power supply based on consideration of a node system topology connection relation of the power distribution network and related data of nodes and branches; possible risks existing in distributed photovoltaic power grid-connected nodes in the power distribution network are simulated, grid-connected risk information of the power distribution network is determined, the matching degree of output power and required power of the distributed photovoltaic power is considered, grid-connected load matching information of the power distribution network is determined, and the overall grid-connected performance of the power distribution network is quantified. According to the invention, stable operation of the power distribution network can be ensured.

The invention discloses a flexible control method for new energy grid connection, and relates to the technical field of new energy grid connection control. The method comprises the steps of obtaining grid-connected point electrical parameters through a self-measurement mode or a communication interface mode, performing harmonic feature extraction and compensation based on a deep learning network, and adopting a state estimation method to fuse multi-source data to estimate power grid parameters; and constructing a multi-objective optimization function including voltage quality, a power factor and harmonic suppression, dynamically adjusting a weight coefficient of the optimization function by using a swarm intelligence algorithm, and realizing inverter switching sequence optimization through multi-objective model prediction control. Through a dual-mode communication redundancy mechanism and local intelligent control, while a communication function of a traditional main link is reserved, a standby wireless communication link is introduced to realize real-time backup transmission of a control instruction, and through a local autonomous decision-making capability, the problem of control failure caused by a communication problem in a traditional scheme is fundamentally solved.

The invention discloses a grid-connected inverter control method based on second-order linear active disturbance rejection, and particularly relates to the field of grid-connected inverter control. Voltage and frequency error signals between the output side of the inverter and the power grid are obtained, a pre-synchronization control model is constructed, and voltage amplitude and frequency synchronization is achieved; a second-order linear active-disturbance-rejection controller is introduced in the frequency synchronization control process, an extended state observer is adopted to estimate the output frequency, the frequency change rate and a disturbance term, and a state error feedback control law is combined to generate a frequency regulation control quantity, so that accurate frequency control is realized; after grid connection, a dual-channel LADRC power regulation controller is constructed, and decoupling tracking control is carried out on active power and reactive power; meanwhile, on the basis of fast Fourier transform processing as a stable grid-connected state criterion, the method has the advantages of being high in control precision, high in anti-interference capability, good in current waveform quality, high in adaptability and the like, and is suitable for various grid-connected application scenes.

The invention discloses a micro-grid automatic power regulation and control method, and relates to the technical field of micro-grid power regulation and control and resource management. In order to solve the defects of poor new energy consumption capability, high distributed resource management difficulty, poor power grid regulation and control flexibility, poor resource cooperation effect and poor power and load prediction accuracy of an existing micro-grid power regulation and control method, grid-connected and off-grid flexible switching of a power grid A and a power grid B is realized by constructing an integrated construction framework. And multi-source data are integrated, and new energy power generation and load demands are intelligently predicted through data center management. And during grid connection, the distribution and dispatching integrated system determines power dispatching, and the micro-grid management system B makes a dispatching plan. And during off-grid, power is supplied according to the user priority. And in the grid-connected and off-grid mode, power distribution, load regulation and control and resource optimization configuration are carried out, and distributed resources are regulated and controlled in real time through the coordination controller, so that stable operation of the power grid is ensured. The method is mainly used for flexibly regulating and controlling the micro-grid.

The invention relates to the technical field of on-load voltage regulation, in particular to a transformer on-load voltage regulation control method. According to the technical scheme, the transformer on-load voltage regulation control method comprises the following steps that S1, a transformer cluster running in parallel is decomposed into distributed intelligent nodes, and each node executes local voltage prediction and constraint condition management; s2, adopting a distributed model prediction control framework, and cooperatively solving a voltage regulation optimization target through an edge calculation unit; s3, a harmonic disturbance signal with a preset amplitude is injected into the transformer, equivalent impedance is dynamically identified based on response data, and virtual impedance compensation is triggered; and S4, establishing a hierarchical cooperative control architecture, and realizing clock synchronization, dynamic weight distribution and multi-objective optimization decision among nodes. Through a cooperative mechanism of distributed predictive control and dynamic impedance compensation, the response speed and the regulation precision of the on-load voltage regulation system to the power grid voltage fluctuation are remarkably improved, and the voltage out-of-limit problem under the complex working conditions of new energy grid connection, load sudden change and the like is effectively solved.

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 belongs to the technical field of emergency power supply of power supply vehicles, and particularly discloses and provides an emergency power supply system of a large mobile storage and charging power supply vehicle, which comprises a vehicle-mounted energy storage unit, a power conversion unit, a PWM (Pulse Width Modulation) signal generation unit, a load monitoring unit and a control unit. The control unit determines a grid-connected mode or an off-grid mode by collecting the on-off state of a power grid and the total power of a load and calculating the power change rate. During grid connection, a voltage instantaneous value is monitored, and a power supply process is executed after locking cooperative control is triggered. Load impact components are identified and verified in the off-grid process, loads are cut off in a graded mode and cyclic verification is conducted if the load impact components do not pass or power exceeds the limit, and after the load impact components pass, time sequence graded loading control is executed according to the adjustment stage number determined by the load type and the proportion. According to the invention, flexible selection between grid connection and grid disconnection can be realized according to actual working conditions, the condition of single power supply mode is changed, the adaptive capacity to different scenes is improved, the real uninterruptible power supply requirement is met, and the impact load is precisely controlled.

The invention relates to the technical field of power system control, in particular to a distributed power supply parameter adaptive control method, system and device based on an improved grey wolf algorithm and a medium. Obtaining distributed power supply parameters to construct a VSG model; establishing an objective function by taking the rotational inertia and the damping coefficient as optimization variables and setting stability constraints; adopting an improved grey wolf algorithm comprising a Tent chaotic mapping initialization population, a nonlinear convergence factor, an adaptive weight strategy and a Levy flight mechanism to optimize parameters; and the rotational inertia and the damping coefficient are dynamically adjusted according to the angular velocity change rate to realize parameter adaptive control. The problems that a traditional grey wolf algorithm is prone to falling into local optimum, VSG parameter optimization lacks systematicness, and fixed parameters are difficult to adapt to changing working conditions are solved, parameter optimization precision is improved, coordinated optimization of rotational inertia and damping coefficients is achieved, the system can intelligently adjust control parameters according to the disturbance degree, system power and frequency oscillation is effectively restrained, and the system performance is improved. And the grid connection stability and dynamic response performance of the distributed power supply are improved.

The invention discloses an electric power control method based on a diesel generator, commercial power and photovoltaic grid connection. The method comprises the following steps: acquiring operation data of commercial power, a diesel generator and photovoltaic-energy storage through an energy management system, constructing a multi-target dynamic optimization model, and distributing power by taking the lowest comprehensive operation cost, the highest power supply reliability and the minimum carbon emission as targets; the power analysis and regulation unit adopts a double-loop mechanism of outer-loop Kalman filtering prediction compensation and inner-loop model prediction control, synchronizes the voltage, frequency and phase of the side to be connected with the grid and the power grid side, and smoothly switches the power change rate of each energy source in the process through a self-adaptive sliding mode control strategy; and the grid-connected switching unit intelligently pre-judges the grid-connected switching opportunity by using a long short-term memory (LSTM) network and fuzzy logic fusion model. According to the invention, the energy utilization efficiency and the power supply stability are improved, multi-energy intelligent dynamic regulation and control are realized, the comprehensive operation cost of the system is effectively reduced, and reliable power supply under complex working conditions is ensured.

The invention relates to the technical field of boiler control, and discloses a gas-fired boiler starting control method and system. The method comprises the following steps: acquiring initial operation parameters such as hearth pressure, water inlet temperature, flue gas oxygen content and fuel valve opening of the gas-fired boiler, establishing a thermodynamic state model in a starting stage according to the initial operation parameters, and dividing dynamic response thresholds of different load intervals; and calculating a theoretical fuel supply rate of the combustor based on the model, generating and dynamically updating a fuel supply correction coefficient in combination with a threshold value, synchronously marking key nodes according to abnormal distribution of hearth temperature, and adjusting a spatial air distribution strategy of the combustor. And after the correction coefficient is subjected to multi-stage buffer smoothing, a fuel control instruction is output to an executing mechanism. And switching to steady state control after the boiler reaches the preset load. The method adapts to the characteristics of a power plant unit, so that the starting process is more stable, the damage to a heated surface and pollutant emission are reduced, and rapid grid connection is assisted.

The invention provides a photovoltaic energy storage inverter power coordination control method based on an adaptive algorithm, and relates to the technical field of data processing, and the method comprises the steps: collecting the output power data of a photovoltaic module, the state data of an energy storage device, and the load demand data of a grid connection point, and carrying out the normalization processing of the data; calculating to obtain an initial power distribution parameter of the current period; respectively calculating a load change trend factor and a power fluctuation trend factor based on the load demand data and the output power data of the historical period, and coupling the load change trend factor and the power fluctuation trend factor to form a trend coupling factor; carrying out self-adaptive repair through a trend coupling factor; combining real-time grid-connected point load demand data with energy storage device state data to generate a target power distribution instruction and an energy storage charging and discharging adjustment instruction, and respectively issuing the instructions to an inverter control unit and an energy storage device control unit; according to the invention, the accuracy of the photovoltaic energy storage inverter power coordination control method is improved.

The invention provides a coordination control method and device of a photovoltaic energy storage inverter for automobile charging based on artificial intelligence, and belongs to the technical field of automobile photovoltaic energy storage coordination control, and the method comprises the steps: monitoring the output power of a photovoltaic array, the state of charge (SOC) of an energy storage system, the state of a power grid and the power demand of a load in real time; a reinforcement learning algorithm is introduced, weather forecast and historical load data are combined, photovoltaic output and load demands in a future time period are predicted, and a power distribution instruction is generated; deciding a current operation mode and generating a mode switching instruction; seamless switching between grid connection and grid disconnection is controlled, and after switching is completed, the charging and discharging proportion of the lithium battery and the super capacitor is coordinated; integrating the energy storage real-time state and the power distribution instruction, and optimizing and adjusting the control parameters of the inverter in real time; continuously monitoring a running state and a switching process, and starting a standby mode when a fault is detected; and the data is uploaded to a monitoring platform. The system operation is efficiently optimized, the service life is prolonged, and stability is guaranteed.

The present application relates to the technical field of wind power generation, and discloses a control method and apparatus for a grid-forming doubly-fed wind turbine generator, a generator, and a medium. In embodiments of the present application, a current reference value of a grid connection point is determined on the basis of measurement parameters of the grid connection point in combination with an internal potential parameter of a grid-forming doubly-fed wind turbine generator and a virtual impedance reference value, a voltage reference value of a grid-side converter is further determined on the basis of the current reference value of the grid connection point, and the grid-side converter is modulated on the basis of the voltage reference value, thereby implementing closed-loop control of the grid-side converter, such that a difference between an output voltage value and the voltage reference value of the grid-side converter is less than a preset threshold.

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 discloses a CFD (computational fluid dynamics) analogue simulation-based wind power plant wind resource evaluation method and a CFD analogue simulation-based wind power plant wind resource evaluation device. The evaluation method comprises the following steps: collecting and processing landform and meteorological data of a wind power plant site; establishing a three-dimensional CFD simulation model of the wind power plant according to the processed landform and meteorological data of the wind power plant site, performing grid division on a wind power plant area, and setting simulation boundary conditions; performing numerical simulation on the three-dimensional CFD simulation model of the wind power plant, and analyzing wind speed field distribution information of each position in the wind power plant; and according to the wind speed distribution information, calculating and evaluating the wind resource condition of the wind power plant to obtain a wind resource evaluation result. According to the technical scheme, through the three-dimensional simulation-evaluation-optimization closed loop with the CFD as the core, the wind speed and turbulence can be accurately quantified in the design stage, so that unit model selection, tower height, blade length and machine position layout are matched with a real wind field, key parameters can be determined at a time, the design period can be shortened, and the operation and maintenance and grid connection cost can be reduced.

The invention discloses a photovoltaic cluster flexible grid-connected regulation and control method and system, and the method comprises the steps: collecting the state data of a power distribution network node and a photovoltaic cluster, carrying out the data cleaning and timestamp alignment preprocessing, and obtaining a system state comprehensive data flow; constructing a multi-target optimization model containing power grid friendliness and photovoltaic power generation benefits based on the system state comprehensive data flow, and solving by utilizing a reinforcement learning algorithm to obtain a control strategy of a photovoltaic inverter and an energy storage unit; according to the control strategy, active power output and reactive power output of the photovoltaic inverter and charging and discharging power of the energy storage unit are controlled in a coordinated mode, and flexible grid connection of the photovoltaic cluster is achieved; and based on system response data, optimizing a control strategy by adopting an optimal decision tree algorithm, updating the reinforcement learning model, and establishing an optimized experience knowledge base. According to the invention, efficient flexible grid-connected regulation and control of the photovoltaic cluster are realized, and the problems of voltage out-of-limit, reverse power transmission and the like when large-scale photovoltaic access to the power distribution network are solved.

The invention discloses a current and voltage signal synchronous correction and output method and system, and relates to the technical field of power system analysis and control. Compared with a previous current and voltage signal correction method, the method solves the problems that traditional multi-channel signal acquisition depends on conventional clock control, and synchronization precision is insufficient; a conventional sampling circuit is weak in anti-interference capability. The problem that an existing scheme lacks efficient error prediction and dynamic optimization capability is solved. Through a multi-channel FPGA clock synchronization and double-differential sampling technology, complete acquisition of high-frequency transient characteristics of voltage and current signals is ensured; a dynamic calibration algorithm and multi-stage composite filtering are combined, so that common-mode interference and non-linear errors are effectively suppressed; and finally, through optical fiber isolation output and intelligent feedback control, signal full-link synchronous correction is realized, the electric energy metering error can be reduced, the fault positioning precision is improved, the characteristics of high precision, strong anti-interference and low energy consumption are realized, and a reliable data reference is provided for intelligent power grid and new energy grid connection.

The invention relates to the technical field of power management, in particular to a multi-source data fusion photovoltaic power scheduling control system, which comprises a sensing extraction module, a disturbance identification module, an offset trend analysis module, a path switching module and a frequency band suppression module. According to the method, a disturbance pre-judgment interval is identified by constructing a time derivative sequence and combining illumination and wind speed trend change in a continuous period, a disturbance time period is accurately discriminated, the disturbance interval is confirmed and disturbance characteristics are extracted through conjoint analysis of photovoltaic and energy storage current change trend and grid-connected point fluctuation amplitude, and the disturbance accuracy is improved. An offset trend curve is formed by calculating photovoltaic and energy storage current change differences, the energy supply offset degree is judged in real time to trigger scheduling conditions, dynamic suppression adjustment is performed on regulation and control signal parameters according to spectrum energy distribution, the accuracy and timeliness of disturbance recognition, energy supply offset judgment and frequency band regulation and control are improved from multiple levels, and the energy storage and energy supply efficiency is improved. And more stable and efficient optical storage combined scheduling control is realized.

The invention relates to a cable joint resonance real-time diagnosis method and device and a medium, and belongs to the technical field of power equipment state monitoring, and the method comprises the following steps: obtaining a high-frequency current signal collected by a high-frequency current sensor and an ultrasonic vibration signal collected by an ultrasonic sensor array; performing signal synchronization on the high-frequency current signal and the ultrasonic vibration signal, and extracting a high-frequency current feature and an ultrasonic array feature; calculating a dominant frequency synchronization index, a normalized phase stability index and a nonlinear coupling index based on the high-frequency current characteristics and the ultrasonic array characteristics, and performing weighted summation to determine a fusion confidence coefficient function; and judging whether resonance exists or not based on the fusion confidence coefficient function, and if so, carrying out resonance source positioning. Compared with the prior art, the method has the advantages of high precision, low false alarm and high adaptability, and is suitable for key power system scenes such as new energy grid connection, urban smart power grids and wind power.

The invention discloses an active island detection method and system based on harmonic impedance characteristic identification, and the method comprises the steps: analyzing the harmonic impedance difference of grid-connected points in a grid-connected state and an island state, and building a state criterion based on resonant frequency deviation and impedance amplitude through the comparison of the frequency response characteristics of island impedance and grid-connected impedance; fitting the grid impedance into an RLC parallel model in a selected frequency band, and mapping the topological difference of the power grid into a parameter difference; embedding a low-voltage ride-through strategy in the control of the voltage source converter, and adjusting reactive current in a grading manner according to the voltage drop degree of a grid-connected point; fundamental waves and harmonic waves are separated through a cascade notch filter, two synchronous harmonic waves are injected into the system through constant current control, and it is ensured that injection signals of a multi-voltage source converter are in the same phase in a phase locking link; and solving an overdetermined equation set based on the double-frequency response data to identify RLC parameters, setting an island criterion, and synchronously completing island judgment in a low-voltage ride-through time window. Detection precision is improved, dynamic response is optimized, and power generation efficiency is improved.

The embodiment of the invention relates to the technical field of energy storage, and provides an off-grid operation method of an energy storage system, the energy storage system and electric equipment, and the operation method comprises the steps: determining whether the grid connection of the energy storage system is powered down or not; under the condition of grid-connected power failure of the energy storage system, port voltage and port current of a load of the energy storage system at the grid-connected power failure moment are obtained, the port voltage of the load is the voltage of one end, connected with a filter of the energy storage system, of the load, and the port current of the load is the current of one end, connected with the filter of the energy storage system, of the load; the arc extinguishing current of the energy storage system is obtained, whether the off-line power-on moment of the energy storage system is reached or not is determined according to the size of the arc extinguishing current, and the arc extinguishing current is the current flowing through the filter; and under the condition that the off-grid power-on moment is reached, off-grid power generation is controlled, and the energy storage system is controlled to operate in an off-grid operation mode based on the port voltage and the port current of the load. The method determines whether to start off-grid according to the magnitude of the arc extinguishing current, thereby avoiding impact caused by direct start.