1126 results about "Battery energy storage" patented technology

The invention relates to the technical field of battery management systems, in particular to a distributed battery state estimation and compensation method based on voltage and current sampling, which comprises the following steps: constructing an original characteristic matrix by synchronously acquiring voltage and current waveforms and extracting ripple characteristics and slope abrupt change points, and generating a characteristic tensor with environment correction through a coupling compensator; then constructing a state parameter space based on adaptive particle injection and an electrochemical-thermodynamic coupling model; adopting a multi-source data fusion engine to realize distributed collaborative estimation of a health state index and a charge state confidence interval, and completing SOC, SOH and temperature trend prediction and residual compensation correction through a multi-state dynamic prediction model; and based on the prediction result and the uncertainty boundary, constructing an energy compensation optimization model, and searching a Pareto optimal compensation strategy. The method can be widely applied to intelligent management and control in the fields of battery energy storage systems and electric power equipment.

The invention discloses a DC bus voltage fluctuation suppression method of a renewable energy hydrogen production system, and relates to the technical field of renewable energy electrolysis hydrogen production. The method comprises the following steps: collecting system operation parameters in real time; bus voltage disturbance power is estimated based on a disturbance observer, and frequency decomposition is carried out; fusing the ARIMA model and the LSTM model to predict the load power, and calculating a prediction deviation; dynamically setting upper and lower limits of a bus voltage control interval according to the predicted deviation and the operation state; a multi-objective optimization function is constructed, bus voltage disturbance power, prediction deviation and a control limit value are comprehensively considered, and power regulation instructions of battery energy storage, a fuel cell and an electrolytic cell are solved; and executing power regulation control to realize bus voltage stabilization. The method can improve the grading response capability of voltage disturbance, the prediction accuracy of load power change, the adaptability of the control boundary and the overall operation stability of the system, and is suitable for the electric energy quality control of the hydrogen production system in a multi-source fluctuation scene.

The invention discloses a battery prefabricated cabin intelligent refrigeration control method and system based on data driving, and relates to the technical field of battery energy storage system thermal management, and the method comprises the steps: collecting the operation multi-source data of a battery prefabricated cabin, and constructing the current thermal environment state expression; constructing a battery cabin short-term internal heat change trend prediction model based on the operation multi-source data of the battery prefabricated cabin; and according to the current thermal environment state expression and the thermal trend prediction result of the battery compartment short-term internal thermal change trend prediction model, an optimal control strategy for an air cooling, liquid cooling or composite refrigeration mode is formulated. According to the method, a closed-loop thermal management system driven by data is formed by constructing a thermal state expression module, a thermal trend prediction module and an intelligent refrigeration decision module, accurate recognition and active regulation and control of the thermal risk of the battery prefabrication cabin are achieved, the temperature control precision and the response efficiency are improved, energy consumption and over-control risks are effectively reduced, and the method is suitable for popularization and application. And the system has the advantages of remarkable engineering practical value and system intellectualization.

In an approach to a state of health for grid applications, a system includes one or more battery energy storage systems having a plurality of batteries; energy sources; power distribution systems; and computing devices. The computing devices are configured to: for each of the battery energy storage systems: receive battery parameters for each of the batteries from the battery energy storage systems; determine a lithium plating state, a solid electrolyte interface (SEI) thickness, and a dendrite length for each of the plurality of batteries; determine a battery state of health (SOH) for each of the batteries based on at least one of the lithium plating state, the SEI thickness, and the dendrite length; determine a battery charge profile to mitigate aging for each of batteries based on the SOH; and send updated battery parameters and control thresholds for each of batteries to each of the battery energy storage systems.

The invention relates to a self-adaptive cooperative control system and method for a sodium-ion battery energy storage system, and relates to the technical field of energy storage system control. An EMS-BMS-PCS cooperative control module is customized, a three-level architecture dynamically adjusts a voltage threshold value, and the SOC is corrected; the multi-stage active safety protection module comprises battery cell monitoring, fault battery cell ejection, modular battery replacement and three-stage fusing protection; the power grid response module PCS performs high-frequency sampling and supports grid-connected and off-grid switching and AGC / AVC service; the intelligent collaborative optimization engine integrates data to generate a charging and discharging strategy, and early warning is performed 14 days in advance for predictive maintenance; the layered distributed control module is used for realizing battery cell-to-system level management; and the double-ring network communication redundancy module ensures real-time transmission of instructions. According to the invention, the DoD and capacity utilization rate of the sodium-ion battery is improved, and the system economy is enhanced; heat spreading is blocked through multi-stage protection, the maintenance time is shortened, and the safety is improved; millisecond-level response meets the high-order demand of a power grid, predictive maintenance reduces the operation and maintenance cost, and the method is suitable for multiple energy storage scenes.

Disclosed is a BMS-based battery energy storage safety management system. The system comprises a BMS module, a control center module, an evaluation analysis module, a coupling analysis module, a prediction module, and a data storage module. The BMS module collects monitoring data of a battery under different operation states and then, according to the monitoring data, performs initial monitoring of a real-time health state of the battery. The evaluation analysis module, according to a change in data indicators in the monitoring data, evaluates and analyzes all fault analysis models in the BMS module to obtain an evaluation analysis result. Then the coupling analysis module combines the evaluation analysis result with the data indicators of the monitoring data to retrieve multidimensional spatio-temporal data, and constructs a coupling field model to perform coupling analysis on battery operation state. The prediction module then constructs a fault prediction model by using a coupling data set as training data, accurately locates coupling faults of different coupling surfaces, and implements comprehensive analysis and location of coupling faults.

The invention discloses a Fourier transform and S transform combined battery impedance spectroscopy measurement method and device, and aims to improve the precision, speed and reliability of impedance measurement of a battery energy storage system. According to the method, a multi-frequency component excitation signal is generated through a controllable current source, and current and voltage response signals of a battery are synchronously acquired and are respectively input into a Fourier transform module and an S transform module for frequency domain analysis. The Fourier transform module extracts impedance spectrums of low and medium frequency bands, and the S transform module extracts impedance spectrums of medium and high frequency bands through Gaussian window time-frequency analysis. And a data fusion algorithm is adopted to perform composite processing on results of the two modules, including a direct selection method, an arithmetic average method, an amplitude and phase calibration method and a weighted average method, so that smooth transition and optimization between frequency bands are realized, and finally the electrochemical impedance spectrum is generated. Through collaborative analysis of Fourier transform and S transform, parameter optimization and a fusion algorithm, the efficiency and accuracy of impedance spectroscopy measurement are remarkably improved, and the method is suitable for rapid monitoring and diagnosis of the battery state.

The invention discloses a container type battery environment monitoring system based on edge calculation, which relates to the technical field of battery environment monitoring, and is characterized in that sensors and edge nodes are arranged in cabins of a battery energy storage device to acquire internal operation environment data of the container type battery energy storage device; a pneumatic environment data set and a water vapor critical data set are formed after data processing, cross-cabin air exchange efficiency Eex is constructed for air exchange qualification evaluation, a condensation nucleation potential index Cnp is constructed when air exchange is abnormal, and a comprehensive condensation risk index Rall is generated in combination with the cross-cabin air exchange efficiency Eex for condensation risk evaluation. Instructions such as fan power adjustment, dehumidification device start and stop and power limitation are issued according to the risk level, and information labels are added to the evaluation data set and uploaded to the cloud in real time. According to the invention, the real-time monitoring of the container type battery environment, the dynamic prediction of the condensation risk and the automatic control are realized, and the safety and reliability of the operation of the energy storage system are improved.

The present invention provides a battery energy storage parallel equalization converter topology and a control method therefor. The battery energy storage parallel equalization converter topology comprises a series-connected battery energy storage parallel equalization converter, a main converter, and a plurality of groups of filter inductors; in the main converter, the input side of a DC / DC or DC / AC converter is connected in parallel to a parallel voltage-stabilizing capacitor, and the output side of the DC / AC or DC / AC converter is correspondingly connected to an AC or DC source load; the series-connected battery energy storage parallel equalization converter comprises a plurality of groups of small-capacity DC / DC converters and a common DC bus capacitor; the output sides of all the small-capacity DC / DC converters are connected in parallel by means of the common DC bus capacitor to form a common DC bus; the input side of one group of small-capacity DC / DC converters is connected in series to the input side of the main converter, and the input sides of other groups of small-capacity DC / DC converters are connected in series to a battery pack by means of the filter inductors, respectively. According to the present invention, in a battery charging and discharging process, only a small amount of power flows through the converter, reducing the capacity requirements of the converter, and reducing the transmission efficiency.

The invention discloses a network construction type battery energy storage system and a control method thereof, and relates to the technical field of battery energy storage. Electrical parameters and operation state parameters are preprocessed, and feature vectors are generated; analyzing offset features based on the feature vectors, and performing feature drift marking; analyzing the spacing characteristics of each battery energy storage device, and performing clustering analysis according to the spacing characteristics; analyzing the equivalent capacity of each cluster in the clustering result; obtaining a historical regulation and control record set, and analyzing the association degree between any two moments; the composite energy fluctuation value at the current moment is analyzed, and a dynamic regulation and control threshold value is analyzed in combination with the correlation degree of the real-time moment and the historical moment; matching degree indexes of all clusters are analyzed in combination with the equivalent capacity and the total regulation and control instruction, an ordered cluster index sequence is generated after sorting, and hierarchical regulation and control instruction analysis is conducted on the ordered cluster index sequence; the allocation proportion is dynamically adjusted, resource allocation is optimized, and the regulation and control risk is reduced.

The invention belongs to the technical field of battery energy storage systems. The invention provides a power distribution method and system for a battery energy storage system, a medium and computer equipment, when the target power of the energy storage system is not zero and the target power is greater than or equal to the sum of the maximum charging and discharging power of all energy storage units, all the energy storage units operate at the maximum charging and discharging power; when the target power of the energy storage system is not zero and the target power is smaller than the sum of the maximum charging and discharging power of all the energy storage units, determining the number of required energy storage units according to the target power and the maximum charging and discharging power of each energy storage unit, and selecting the energy storage units to be used according to an energy storage unit priority rule; performing global optimization on the target power distribution to obtain an optimal or approximately optimal power distribution value of each energy storage unit to be used; according to the invention, the SOC balance degree of the battery energy storage system is improved, and the risk of over-charging and over-discharging is reduced.

The invention discloses an intelligent control method and system for a solar street lamp, and particularly relates to the technical field of intelligent control. The method comprises the following steps: collecting photovoltaic power generation data and battery charging and discharging data of a solar street lamp node, analyzing difference characteristics of photovoltaic power generation capacity of the solar street lamp node in space and fluctuation characteristics of a battery energy storage state in time, and outputting space difference characteristic data and time fluctuation characteristic data; power generation space imbalance evaluation data and energy storage time abrupt change evaluation data are output by evaluating power generation imbalance distribution characteristics and energy storage state abrupt change characteristics caused by dynamic shielding; a local energy link imbalance prediction model is constructed, energy link imbalance prediction data of solar street lamp nodes are output, power distribution and brightness control strategies of solar street lamps are dynamically adjusted, and intelligent sensing and regulation of energy link instability under local shielding are achieved. And the operation stability and the energy-saving performance of the whole illumination system of the solar street lamp group are ensured.

The invention discloses a fire prevention and control method and system for battery energy storage equipment. The method comprises the following steps: collecting real-time fire characteristic parameters of the battery energy storage equipment; based on the real-time fire characteristic parameters and a preset fire control strategy, making a fire control decision and generating a fire control instruction; obtaining effect feedback after the fire-fighting instruction is executed; based on the real-time fire characteristic parameters and effect feedback, optimizing and updating a fire-fighting strategy; and applying the optimized and updated fire-fighting strategy to a subsequent fire-fighting decision of the battery energy storage equipment. According to the method, through real-time monitoring, digital twinborn simulation and a closed-loop optimization mechanism, the accuracy and adaptive capacity of fire prevention and control of the battery energy storage equipment are remarkably improved, dynamic adjustment and low-risk verification of a fire-fighting strategy are achieved, and safety and reliability are effectively enhanced.

A device, method, and non-transitory computer readable medium for controlling a power distribution system includes an islanded microgrid and a control system. The islanded microgrid includes battery energy storage systems (BESSs) that operate as a primary energy source, and a decentralized consensus-based virtual synchronous generator (VSG). The control system simultaneously, emulates inertial response of a synchronous generator by the virtual synchronous generator during grid disruptions to regulate and stabilizes frequency of the islanded microgrid, and maintain consensus among the plurality of battery energy storage systems (BESSs).

The invention discloses a battery energy storage health state detection and evaluation method and system, and relates to the technical field of battery energy storage state monitoring and evaluation, and the method comprises the steps: employing an SOC estimation method, combining an unscented Kalman filter and a Thevenin model to calculate the state of charge of a battery in real time, integrating the multi-dimensional feature data of the battery, inputting the data into an isolation forest algorithm, and carrying out the detection and evaluation of the energy storage health state of the battery. And carrying out deep anomaly detection on the battery sample with the abnormal frequency, and carrying out battery health state evaluation through a multi-stage anomaly detection result. SOC estimation is combined with an unscented Kalman filter, a Thevenin circuit model and an isolation forest algorithm to construct a self-adaptive and high-robustness multi-stage health assessment and anomaly detection system, the unscented Kalman filter performs high-precision prediction on nonlinear state transition, and the robustness of the health assessment and anomaly detection system is improved. The method effectively improves the estimation precision of the SOC under dynamic charging and discharging conditions and the accuracy of anomaly detection, and is suitable for monitoring and safety management of a battery system under complex environments and working conditions.

The invention relates to the technical field of battery energy storage station heat management, and discloses a battery energy storage station heat management optimization method based on multi-target control, which comprises the following steps: constructing a mathematical model of an energy storage station heat management system, and defining a state variable and a control variable of the model; the mathematical model comprises a battery heat production model, a battery heat exchange model, an SOC dynamic model and an energy storage station power balance model; based on the mathematical model of the thermal management system of the energy storage station, establishing a multi-target comprehensive evaluation function and setting constraint conditions; according to the defined state variables and control variables, the multi-objective comprehensive evaluation function and set constraint conditions, learning iteration is carried out based on a Q learning algorithm, a Q value is obtained when a preset convergence condition is reached, and an optimal control variable distribution strategy is output; and performing thermal management optimization on the energy storage station based on the optimal control variable distribution strategy. According to the invention, the balance among the targets is realized based on the combination of the multi-target control strategy and the optimization algorithm, and guarantee is provided for the performance and safety of the battery energy storage station.

The invention discloses a multi-terminal collaborative modular power operation and maintenance method and system based on digital twinning, and the method comprises the following steps: constructing a global power topological graph of a power energy site, mapping power equipment, sensors and connecting lines into graph nodes and graph edges, and binding the static attributes of the equipment with the topological structure; and acquiring real-time operation data of the power equipment, and distributing a unified time label for the multi-source heterogeneous data. According to the method, a unified twinborn model of cross-voltage class, cross-region and cross-equipment type is established in a digital twinborn platform, and operation data of different equipment such as photovoltaic equipment, battery energy storage equipment, an inverter, a protection device, an electric energy meter and temperature control equipment are expressed in a unified data semantic mode; according to the invention, the system can still automatically establish a consistent device portrait under the conditions of a large number of multi-terminal devices and diversified communication protocols, and the multi-terminal cooperative computing capability is significantly improved.

The invention belongs to the technical field of energy storage fire fighting, and particularly discloses an emergency fire fighting system and method for an immersed battery energy storage power station, and the system comprises a battery pack, an immersion liquid storage tank, a fire fighting liquid storage tank, a pumping system and a control system. The battery pack is composed of a plurality of stacked battery packaging units, and a temperature and smoke sensor array and a scattering nozzle are installed above a battery module in each battery packaging unit and used for monitoring fire behavior in real time and spraying fire fighting liquid. The immersion liquid storage tank is connected with the battery packaging unit through a pipeline and is used for battery heat dissipation and insulation protection; the fire-fighting liquid storage tank is connected to the scattering nozzle through a pipeline to provide emergency fire extinguishing support; the pumping system comprises an immersion liquid pump and a fire-fighting liquid pump; the control system is in linkage with the sensor and the pumping system, electrical isolation, immersion liquid emptying and fire-fighting liquid injection operation of a fault module are automatically triggered according to monitoring data, accurate positioning fire extinguishing is achieved, the influence on adjacent normal modules is reduced to the maximum extent, and safety and operation and maintenance efficiency are improved.

The invention relates to the technical field of energy storage system grid-connected control, and particularly discloses a two-stage coupling type battery energy storage grid-connected converter model prediction control method and device, and the method comprises the following steps: S1, constructing a two-stage coupling type battery energy storage grid-connected converter single-machine two-order composite model; s2, according to the single-machine dual-order composite model, constructing a prediction equation of the output current and the capacitor voltage of the inverter; s3, constructing a unified cost function of the output current and the capacitor voltage of the inverter; s4, predicting the switch state combination of all the switch tubes, and calculating the value of a corresponding unified cost function; and S5, selecting the switch state combination with the minimum uniform cost function value as the optimal switch state of all the switch tubes, and carrying out on-off control on the switch tubes. According to the invention, through unified modeling and control optimization, the dynamic response capability and the voltage stabilization performance of the energy storage grid-connected converter are improved.

The invention relates to the technical field of electric power control, in particular to a fire storage cross-regional collaborative frequency modulation control method and system, and the method comprises the steps: generating a cross-regional power distribution instruction of a thermal power generating unit and battery energy storage through an upper-layer optimization model, and carrying out the multi-regional power instruction tracking through a lower-layer distributed control model; selecting a current frequency modulation strategy from a local frequency modulation mode and a cross-regional support mode based on the charge state of the battery energy storage in the disturbance region; in the power distribution instruction generation process, dynamic nonlinear correction is carried out on the energy storage output weight according to the charge state; and calculating local fire storage output by each region based on the current frequency modulation strategy and the power distribution instruction, generating a frequency modulation control instruction meeting the frequency safety constraint and the tie line transmission constraint, and completing cross-region collaborative frequency modulation. According to the invention, the problems of insufficient frequency modulation economy caused by lack of centralized and distributed coordination and rigid responsibility distribution caused by energy storage life static management are effectively solved, and economy-life balanced regulation and control are realized.

The invention belongs to the technical field of battery energy storage, and discloses a method, system, equipment and medium for evaluating the internal temperature of an energy storage lithium ion battery, and the method comprises the steps: obtaining the AC impedance data of the battery at a characteristic frequency, including a real part, an imaginary part, a module value and a phase angle; inputting the real part, the imaginary part, the module value and the phase angle into a battery internal temperature estimation model to obtain the internal temperature of the battery in the current state; the characteristic frequency is the frequency that the Pearson correlation coefficients of the real part, the imaginary part, the module value and the phase angle and the temperature meet correlation, and the frequency that the Pearson correlation coefficients of the real part, the imaginary part, the module value and the phase angle and the state of charge meet ircorrelation. According to the method, the real thermal state in the battery is reflected through the impedance data, and high-precision estimation of the internal temperature of the battery is achieved. Only the characteristic frequency is measured, so that the test time can be greatly shortened; the temperature data can be quickly estimated, the evaluation response speed is obviously improved, and the method has high engineering application value.

The invention relates to the technical field of sodium battery energy storage safety, and discloses a thermal runaway early warning method and device for a sodium battery energy storage system. Multi-modal data such as acoustic emission, gas dielectric characteristics and electrical parameters are collected in real time through multiple sensors, pre-processing and feature extraction are performed through an edge calculation unit, and the data are transmitted to a central decision-making unit for multi-source information fusion and risk assessment; the thermal runaway risk probability is dynamically calculated by adopting a deep learning algorithm based on an attention mechanism, a grading early warning instruction is generated according to the risk grade, and accurate response is realized through multi-system linkage execution. According to the invention, early-stage monitoring of internal microscopic damage and gas environment abnormity of the sodium battery is realized, timeliness and accuracy of thermal runaway early warning are improved, and safe and stable operation of a sodium battery energy storage system is guaranteed.

The invention is suitable for the technical field of battery safety monitoring, and provides a sodium ion battery energy storage system health state dynamic prediction method based on simulation digital twinning, and the method comprises the steps: constructing a digital twinning body comprising a physical layer, a virtual layer and a data interaction layer; performing health state estimation based on the physical layer and the virtual layer, and outputting a health state estimation value; comparing the health state estimated value with the measured value, calculating a residual error, and updating key aging parameters in the simulation model; inputting the updated key aging parameters into a pre-trained time sequence neural network model, carrying out sequence learning, and outputting a capacity attenuation trend and a residual life prediction result of the battery; generating a full life cycle optimization strategy based on the prediction result, and generating an optimal charge-discharge power table by simulating the influence of different charge-discharge strategies on the life; the problems of life attenuation and high operation and maintenance cost caused by insufficient prediction precision in the prior art are effectively solved.

The invention discloses a diesel-storage intelligent micro-grid system. A diesel generator charges an energy storage unit or cooperatively supplies power when power supply is insufficient; the battery energy storage unit stores electric energy and supplies power to a load; the micro-grid energy management system dynamically coordinates the output proportion, and a harmonic suppression module suppresses harmonic interference; the load prediction module predicts load power change; the transient response control module deals with transient power impact; the power distribution system is connected to a main power supply and is switched to a diesel generator power supply mode when power supply of the main power supply does not meet requirements; when the diesel generator supplies power, the bidirectional converter converts electric energy into charging current of the energy storage unit and inhibits harmonic interference; when the energy storage unit supplies power, the direct current is converted into the alternating current required by the load. According to the invention, seamless switching of multiple energy sources, active stabilization of power fluctuation, flexible conversion of electric energy forms, optimization of energy distribution efficiency and comprehensive improvement of the survivability of the micro-grid can be realized.

The invention discloses an energy storage cabinet, and relates to the technical field of battery energy storage. The cabinet comprises a cabinet body and a solar cell module, wherein the solar cell module is fixed at the top of the cabinet body; the cabinet body comprises a battery bin, a control bin and a rear backboard. A plurality of bracket slide rails are arranged in the battery compartment side by side, and a cooling plate is fixed on each row of bracket slide rails; an integrated water cooling machine is arranged in the control bin; the cooling plate is connected to the integrated water cooling machine through a water cooling pipeline; a plurality of semiconductor coolers are fixed on the back plate; and the solar cell module is electrically connected with the semiconductor cooler. The circulating water cooling plate is adopted to carry out cooling control on the battery of the energy storage cabinet, the solar battery assembly is arranged at the top of the energy storage cabinet, extra electric energy independent of the energy storage cabinet can be provided, meanwhile, the semiconductor refrigerator is installed on the energy storage cabinet, the solar battery is used for direct refrigeration, and the use energy consumption of the energy storage cabinet is effectively reduced.

The invention discloses a photovoltaic-electrolytic cell cooperative power control method and a medium, and the method comprises the steps: constructing a photovoltaic electrolytic hydrogen production system which comprises a photovoltaic module, a battery energy storage module, an electrolytic cell module and a hydrogen storage tank; calculating the planned operation number of electrolytic baths based on the photovoltaic electrolytic hydrogen production system; dividing electrolytic bath operation scenes based on the photovoltaic output, the photovoltaic electrolytic hydrogen production system and the planned operation number of the electrolytic bath, wherein the electrolytic bath operation scenes comprise an electrolytic bath full-load operation scene, an electrolytic bath and battery load mixed operation scene and a self-adaptive adjustment load operation scene; executing a corresponding power scheduling and operation control strategy on the photovoltaic electrolytic hydrogen production system based on the electrolytic cell operation scene and the planned operation number of the electrolytic cells; and based on the objective function under the constraint condition, carrying out optimization solution on the power scheduling and operation control strategy to obtain the reference power of the electrolytic cell. The method can adapt to different photovoltaic wide power fluctuations by dividing different electrolytic cell operation scenes.

The invention belongs to the technical field of battery energy storage devices, and particularly relates to a battery energy storage device with circular flow heat dissipation, which comprises a bottom plate, the upper end of the bottom plate is fixedly connected with a placement table through a first support rod, and the upper end of the placement table is fixedly connected with a circular flow channel and an annular flow channel; a plurality of linear runners which are distributed in a circumferential array manner are fixedly communicated between the circular runner and the annular runner; the circular flow channel, the linear flow channel and the annular flow channel jointly form a cooling channel, the cooling channel is filled with cooling liquid, and the position, located above the cooling channel, of the containing table is fixedly connected with a containing frame. By arranging the placing frames corresponding to the cooling channels, a differentiated conduction path of'central concentrated heat absorption-peripheral distributed heat dissipation 'is formed, the problems of insufficient central heat dissipation and energy waste of peripheral over-cooling caused by a traditional uniform flow channel are effectively solved, and differentiated precise heat dissipation of modules at the center and the peripheral side of the battery pack is realized.

The invention discloses a power grid frequency modulation method based on flywheel energy storage and electrochemical energy storage. The method comprises the following steps: S1, receiving an AGC instruction issued by an AGC dispatching center; s2, preferentially responding to the frequency modulation demand through flywheel energy storage, and adjusting the rotating speed of the flywheel in real time based on the instantaneous power output capability and the residual electric quantity of the flywheel so as to compensate for the high-frequency small-amplitude power deviation; s3, when the flywheel energy storage power or energy is insufficient, battery energy storage supplements response, the charge and discharge depth of the battery is limited according to the charge state of the battery, and the service life is prolonged; and S4, combining the actual ramp rate of the thermal power generating unit, dynamically distributing the output of the energy storage system, and forming a thermal power-hybrid energy storage combined frequency modulation model. The frequency modulation performance index is improved; through instantaneous response of flywheel energy storage and continuous support of a battery, the Kp value is improved from 3.7 to more than 4.2 by combining a frequency modulation system; and the service life of the battery is prolonged, and the replacement cost and the comprehensive cost are reduced by limiting the charge-discharge depth (the SOC range is 20%-90%) of the lithium battery and reducing the high-frequency charge-discharge times of the lithium battery.

The utility model discloses a rail type gravity energy storage power station, the power station is arranged on a rail, two sides of the bottom of a train are provided with driving plates, the power station comprises a supporting seat, a friction wheel, a transmission piece, a permanent magnet synchronous motor, a PLC control cabinet and a storage battery energy storage control cabinet, when the train passes through the power station, the friction wheel is in friction connection with the train driving plates, and the transmission piece is connected with the storage battery energy storage control cabinet. The permanent magnet synchronous motor is electrically connected with the storage battery energy storage control cabinet through a first on-off switch, the permanent magnet synchronous motor is connected with a power grid power source through a second on-off switch, a plurality of position sensors are arranged on the slope section of the track, and the total controller feeds back the position sensors to the storage battery energy storage control cabinet when the train is in downhill transportation according to the position sensors. Otherwise, the permanent magnet synchronous motor is controlled to operate as a motor. When the power station is applied to a slope section track, a driving mode and a power generation mode can be automatically switched according to ascending or descending of a train, so that one-station compatibility of power generation and driving is realized.

The invention relates to the technical field of prediction models, in particular to a battery energy storage life prediction method and system based on multiple time scales, and the method comprises the following steps: deploying three groups of short-term, medium-term and long-term parallel data windows, obtaining battery capacity and internal resistance parameters, sliding window initialization parameters, synchronous baseline calibration, and Kalman filtering correction parameters, and extracting a variation amplitude and rate, an output capacity mean value and an internal resistance variance, calculating a residual sequence, performing three-time linkage on the capacity residual exceeding a threshold to trigger an abnormity, performing weighted fusion after the abnormity, and outputting the residual life. According to the invention, through multi-time scale parallel data window dynamic monitoring, sliding window synchronous calibration base line, Kalman filtering dynamic correction parameters, capacity and internal resistance residual error linkage determination mechanism establishment, dual-attenuation coupling model fusion multi-dimensional attenuation characteristics and multi-scale collaborative analysis of battery aging, the limitation of a linear model is broken through; the anomaly detection sensitivity and robustness are enhanced, the life prediction accuracy and timeliness are improved, and the misjudgment risk is reduced.