733results about "Energy storage" patented technology

The invention discloses an on-site monitoring system for the performance of an elastic loose type anchorage system suitable for deep-sea buoys, and particularly relates to the field of deep-sea monitoring. The on-site monitoring system auxiliary comprises a central processing module, wherein the output end of the central processing module is separately connected with an information display module,an information storage module, an auxiliary recovery module and a driving module, and the input end of the central processing module is separately connected with a power supply module, a monitoring module, a correction module and a positioning module. According to the on-site monitoring system for the performance of the elastic loose type anchorage system suitable for the deep-sea buoys, the auxiliary recovery module is arranged, air bags are installed at a plurality of node positions on the anchorage system, a booster pump in a pressurization unit is used, outside air is conveyed into a floating ball unit through a pipeline unit, so that the retractable air bags are enabled to bulge upwards to float, the whole anchor system is directly floated in sections, people conveniently recycle theanchorage system greatly, the workload during the recycling process is reduced, and the practicability is high.

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 discloses a hybrid energy storage optimization configuration method based on a multi-time scale regulation and control demand, and the method comprises the steps: collecting the operation data of a power system, and obtaining the power fluctuation and the frequency deviation of the power system under a short time scale through a preset high-proportion renewable energy power system model; on the basis of power fluctuation and frequency deviation, the regulation and control requirements of the power system are divided according to different time scales, different energy storage modules are correspondingly configured, and a multi-level collaborative energy storage regulation and control structure matched with the time scales is formed; based on the power system model and the mathematical model of each energy storage module, constructing a hierarchical nested optimization model oriented to multiple time scales; and selecting a typical scene from the operation data by adopting a time sequence clustering method, and obtaining the optimal capacity and power configuration of each energy storage module based on a hierarchical nested optimization model, and obtaining a cross-time-scale collaborative operation strategy. The global optimal configuration is realized by establishing a multi-time-scale collaborative hierarchical nested optimization architecture.

The invention discloses a multi-energy system closed-loop prediction control method, system, equipment and medium, and the method comprises the steps: carrying out the decomposition, dimension reduction and nonlinear modeling of the time sequence characteristics and environmental influence factors of photovoltaic output through a photovoltaic power prediction model, and outputting a future multi-period photovoltaic power prediction sequence; establishing a state equation and an output equation, integrating equipment operation constraints, and constructing a hydrogen-containing energy storage state space model; inputting local load power and a future multi-period photovoltaic power prediction sequence into the hydrogen-containing energy storage state space model, and solving an objective function through a rolling optimization algorithm to obtain a future multi-period optimal scheduling scheme; and applying a first hour control instruction of the optimal scheduling scheme to an actual system, and proportionally superposing the deviation between an actual measurement value and a historical prediction value to a photovoltaic power prediction sequence of a next period through a feedback correction item to realize closed-loop control. According to the method, the photovoltaic local consumption rate can be improved, and the power grid fluctuation rate is reduced.

The invention relates to the technical field of wind power generation, and particularly discloses a train-mounted ducted airflow coupling wind energy recovery power generation system and method. The train-mounted ducted airflow coupling wind energy recovery power generation system comprises N ducted windmills which are sequentially connected through connecting assemblies; the supporting assemblies are in one-to-one correspondence with the ducted windmills; the supporting assembly is used for supporting the ducted windmill and can achieve rotation and turning of the ducted windmill. The energy storage devices are in one-to-one correspondence with the ducted windmills, and the energy storage devices are connected with generators in the ducted windmills through cables; the connecting assembly comprises a first fixing part, a connecting section and a second fixing part; the first fixing part is connected with the outlet end of the ducted windmill, the second fixing part is connected with the inlet end of the ducted windmill, and the two ends of the connecting section are detachably connected with the first fixing part and the second fixing part respectively. The multiple ducted windmills are connected in series and installed on the train, the ducted windmills can rapidly turn around based on different driving directions, and the ducted windmills can be used for train power generation.

The invention relates to the technical field of power system control, and discloses a photovoltaic energy storage primary frequency modulation cooperative control system based on output prediction and SOC balance, which comprises a photovoltaic array unit, a photovoltaic inverter, a sodium ion super capacitor energy storage unit, a bidirectional DC / DC converter and a cooperative controller. The cooperative controller is configured to identify an output trend by using photovoltaic power prediction data, and dynamically adjust an energy storage SOC reference anchor value; a source storage virtual impedance model considering the real-time efficiency characteristic of the sodium ion super capacitor is constructed, and the primary frequency modulation power demand is dynamically allocated. When the state of the energy storage unit deteriorates, the power compensation amount is calculated through photovoltaic load shedding sliding mode offset control, and the closed-loop target of the photovoltaic inverter is corrected to share the frequency modulation task. And after the frequency modulation is finished, controlling the photovoltaic power to recover by adopting an asymmetric step length. The method solves the problems that the energy storage standby is not matched and the response capability is reduced under the extreme working condition, and improves the frequency modulation stability of the system.

The invention discloses a photovoltaic electric field energy storage optimal configuration method and system considering system flexibility and confidence level, and relates to the technical field of energy storage capacity configuration.The photovoltaic electric field energy storage optimal configuration method comprises the steps that photovoltaic data are collected to construct a photovoltaic generation power output model, and a system flexibility constraint based on a rapid unit combination model is established; establishing a system capacity adequacy constraint based on a confidence level, and calculating the load supply capacity of the optical storage combined system according to the flexibility constraint and the capacity adequacy constraint of the system; and solving an energy storage equipment parameter feasible region meeting the safe operation requirement of the combined system based on the load supply capacity, and calculating the optimal parameter of the energy storage equipment in the feasible region. According to the photovoltaic electric field energy storage optimal configuration method considering the system flexibility and the confidence level, the system capacity adequacy constraint adopting the confidence level is added, the stability and safety of the system are evaluated more comprehensively, and therefore it is ensured that the system can still operate stably under the condition that the maximum peak load is met.

The invention discloses a distributed photovoltaic grid-connected and off-grid coordination control method. The method comprises the following steps: a photovoltaic data acquisition terminal acquires an operation state data set of a photovoltaic array, an inverter and the like through each node sensor and intelligent equipment; the photovoltaic data preprocessing terminal performs denoising, normalization and the like on the original data to form a standardized data set; the data analysis terminal calculates a power balance equal coefficient, inputs the power balance equal coefficient into the decision model and outputs a grid-connected and off-grid coordination index; the coordination control terminal judges a grid-connected operation mode or an off-grid operation mode according to the index; the energy management terminal coordinates the power output of each unit during grid connection, and optimizes an energy storage charging and discharging strategy during off-grid; the state monitoring terminal performs real-time monitoring, discovers abnormal early warning and triggers fault processing; according to the method, the operation stability and the energy utilization efficiency of the photovoltaic system are improved.

The invention provides a power grid dispatching control method based on renewable energy source and energy storage collaborative optimization, which comprises the following steps: S1, acquiring the power of a tie line of a regional power grid and a main power grid, determining the real-time fluctuation ratio of the power of the tie line, and determining a virtual power plant configuration according to the real-time fluctuation ratio; s2, the renewable energy units and the energy storage units used for building a virtual power plant are screened out according to the operation parameters of the renewable energy units and the energy storage units, and the virtual power plant is built according to the virtual power plant configuration; acquiring a real-time operation state of an energy storage unit in the virtual power plant; dividing the energy storage units into different control groups according to the real-time operation states of the energy storage units, and configuring charging and discharging control parameters for each control group; s3, inputting the topological structure of the virtual power plant into the digital twin system, simulating the operation of the virtual power plant in the digital twin system, and operating according to the charge and discharge control parameters configured in the step S2; and S4, constructing a virtual power plant operation comprehensive evaluation model, determining an optimal value of the evaluation model by adopting a genetic algorithm, and taking the charging and discharging control parameters corresponding to the optimal value as power grid dispatching control parameters.

The invention discloses an energy control method and device based on an optical diesel storage micro-grid system and a medium. The invention relates to the field of energy management, and solves the problem of consumption of diesel generator feedback residual electricity and photovoltaic feedback electricity in a factory and the problem of reducing the demand electric charge of the factory. Whether feedback electricity is generated or not is recognized through power grid home-entry load data, once it is judged that the feedback electricity exists and energy storage does not reach the preset upper limit, energy storage charging is immediately controlled, redundant electric energy such as the feedback electricity of the diesel generator test stand and photovoltaic residual electricity is stored, and the problems that the feedback electricity cannot be connected to a grid and consequently waste is caused and photovoltaic light is abandoned are solved; when no feedback electricity exists, whether the energy storage state of charge (SOC) is lower than a preset lower limit or not is judged to avoid over-discharge, then charging is triggered in combination with the conditions that the load power is smaller than or equal to a peak clipping threshold value in a low ebb period, and low-cost energy storage is conducted through the valley electricity; and when the load exceeds a peak clipping threshold value and is in a non-low-ebb period, discharging is triggered, and the load peak demand is matched. In addition, when the load peak or the load exceeds the peak clipping threshold value, power supply is supplemented through energy storage discharge, and the cost is reduced.

The invention discloses a power cooperative regulation and control method and device based on a heterogeneous energy storage cluster, and the method comprises the steps: carrying out the determination and optimization processing according to a user demand, the output power of a renewable energy subsystem, and a variational mode algorithm, and obtaining a target high-frequency signal and a target low-frequency signal; determining the charging and discharging power of each single super capacitor according to the target high-frequency signal and the health state and the charge state of the single super capacitor; determining the charging and discharging power of each single battery according to the target low-frequency signal and the health state and the charge state of the single battery; judging whether the charging and discharging power of each single super capacitor and the charging and discharging power of each single battery meet a preset charging and discharging constraint condition, an electric power balance constraint condition and a cost constraint condition or not; and if all constraint conditions are met, taking the scheme as a final charging and discharging scheme. According to the application, the systematized and refined response to the power grid total dispatching instruction is realized by optimizing the distribution of the power among different stations and heterogeneous energy storage units.

The invention relates to the technical field of energy management, calculation and prediction, in particular to an energy storage micro-grid dynamic collaborative scheduling system based on photovoltaic prediction, a photovoltaic prediction system comprises a data acquisition module and a prediction model, and a micro-grid scheduling system comprises a load management module, a grid interaction module and a real-time response control module. The energy storage system comprises an energy storage battery pack, a charging and discharging control module and an SOC monitoring module. The photovoltaic prediction system is in communication connection with the micro-grid scheduling system, the micro-grid scheduling system is in communication connection with the energy storage system, photovoltaic and load prediction is fused, a multi-target optimization algorithm and a closed-loop feedback mechanism are introduced, and regulation and control perspectiveness, multi-target collaborative scheduling and whole-process system linkage are achieved. And the requirements of various types of micro-grid systems on controllability and stability of photovoltaic power generation are met.

The invention relates to a water-light-storage integrated micro-grid system and a control method thereof. The system comprises a distributed hydroelectric power supply, a distributed photovoltaic power supply, an energy storage system, a medium-voltage AC-DC flexible interconnection device, a micro-grid energy management system and a load. The medium-voltage AC / DC flexible interconnection device is connected in series between a grid-connected point of the micro-grid and a superior power distribution network, an AC port of the medium-voltage AC / DC flexible interconnection device is used for realizing flexible power flow mutual aid between the micro-grid and the superior power distribution network, and a DC port of the medium-voltage AC / DC flexible interconnection device is used for being connected with an energy storage system; and the micro-grid energy management system is in communication connection with the distributed hydroelectric power supply, the distributed photovoltaic power supply, the energy storage system and the medium-voltage AC / DC flexible interconnection device, and is used for collecting system operation data, executing an optimization control strategy and realizing autonomous operation of the micro-grid and cooperative control of the micro-grid and a superior power distribution network. The system can effectively cope with seasonal load peaks, greatly improve the local consumption rate of distributed water and light resources, and enhance the power supply reliability and operation flexibility of a local power grid.

Systems and methods are described for powering a load, such as a data center, with renewable energy from a renewable energy source. When the renewable energy is greater than a demand of the load, excess renewable energy is used to power a hydrogen production device or charge a battery depending on whether or not the charge level of the battery satisfies an upper threshold charge level, respectively. When the renewable energy is less than the demand of the load and the charge level of the battery satisfies a lower threshold charge level, the load is powered with energy from the battery. When the renewable energy is less than the demand of the load and the charge level of the battery does not satisfy the lower threshold charge level, the load is powered and the battery is charged with energy generated by the hydrogen-based energy generator.

The present invention relates to a wind turbine park (100), comprising at least a first wind turbine (110) and a second wind turbine (120) for generating a power product, and a main line (101) connecting the first wind turbine (110) and the second wind turbine (120) for transporting the power product. The wind turbine park (100) further comprises an auxiliary power line (102) being connected to the first wind turbine (110) and the second wind turbine (120), wherein the auxiliary power line (102) is configured for transporting auxiliary power for a wind turbine maintenance or standby operation to at least one of the first wind turbine (110) and the second wind turbine (120). Furthermore, the wind turbine park (100) comprises an auxiliary power unit (103) for generating the auxiliary power, wherein the auxiliary power unit (103) is connected to the auxiliary power line (102).

The invention provides an energy storage adjustment method and system based on photovoltaic power ultra-short-term prediction. The method comprises the steps of periodically obtaining an ultra-short-term power prediction sequence of a photovoltaic power station; the fluctuation characteristic quantity is analyzed, a control parameter set is dynamically selected based on the characteristic quantity, and a self-adaptive stabilizing target power curve is generated; constructing a multi-target optimization problem taking a tracking target curve as a core, and carrying out online solving to obtain an optimal charging and discharging power instruction of the energy storage system; the system comprises an ultra-short-term power prediction module, a self-adaptive strategy generator module, a rolling optimization controller module, an energy storage control execution module and a data acquisition and feedback module, relates to the technical field of new energy power generation and intelligent power grid operation control, and aims to deeply couple prediction information with self-adaptive decision, rolling optimization and closed-loop learning so as to realize intelligent power generation. The energy storage system can deal with photovoltaic power fluctuation in a prospective manner, control modes are intelligently switched according to fluctuation intensity, and collaborative optimization of stabilizing effect and equipment economy is realized.

The invention discloses an operation control method and device of an energy storage system based on demand defense. The method comprises the following steps: predicting and obtaining a load change curve, a photovoltaic output change curve, an electricity price change curve and a charge state change curve in a future preset time period based on a collected multi-source data set of a user side; predicting the electricity purchase cost of the user based on the electricity price change curve, the load change curve, the photovoltaic output change curve and the charge state change curve; predicting demand penalty cost based on the load change curve and the photovoltaic output change curve; constructing a target function at least based on the user electricity purchase cost and the demand penalty cost; and determining a day-ahead charging and discharging strategy based on the target function and a predetermined constraint condition, and controlling the operation of the target energy storage system based on the day-ahead charging and discharging strategy. According to the invention, the operation of the energy storage system can be reasonably and accurately controlled.

The integrated hybrid system for managing the production, flow, consumption and storage of energy is characterised in that it comprises a cryogenic liquefied air energy storage (7), to which, either upstream and / or downstream of the compressor, an system for transporting oxygen (D) obtained from the electrolyzer (11) is connected, while an system supplying heat (B) obtained during combustion of gas in the trigeneration unit (9) is incorporated in the liquid air and / or oxygen expansion station of the cryogenic liquid air energy storage (LAES) (7), wherein all energy processing and storage units are incorporated in the control and supervision system, collecting data in real time, monitoring the production, consumption and demand for electrical energy, and intelligently controlling energy flow between generation sources, powered devices and energy storage units.

A stackable power supply device, container or unit is provided. The power supply device includes an energy conversion module, such as a solar panel. The power supply device includes several power outlets, such as an interface to recharge rechargeable batteries for power tools, an electrical outlet, and a battery to store energy generated by the solar panel. The power supply device is stackable within a modular storage system.

The invention discloses a multi-target collaborative energy management method and system for a light storage integrated power station. The method comprises the following steps: acquiring real-time operation data of the light storage integrated power station in a current detection period; based on the real-time operation data, calculating an operation efficiency evaluation value, an energy storage device life attenuation evaluation value and a power grid supporting capability evaluation value of the light storage integrated power station; based on the real-time calculation result, generating a multi-target collaborative optimization instruction by adopting a dynamic priority strategy; and decomposing the multi-target collaborative optimization instruction to obtain a photovoltaic inverter output instruction, an energy storage device charging and discharging power instruction and a grid-connected power instruction, and controlling the operation of the light storage integrated power station according to the photovoltaic inverter output instruction, the energy storage device charging and discharging power instruction and the grid-connected power instruction. Self-adaptive switching of multi-target weights is realized by constructing a dynamic priority strategy, and the problems of aggravation of equipment loss, lagging of power grid support and the like caused by single-target optimization are effectively solved.

A method for harvesting energy from one or more internal energy sources of a wind turbine of a wind farm during an off-grid state includes collecting energy from the one or more internal energy sources locally at the wind turbine during the off-grid state. The off-grid state is characterized in that the wind turbine is mechanically and electrically installed at the wind farm but not yet connected to a grid. The method further includes storing at least a portion of the energy in one or more energy storage devices locally at the wind turbine or the wind farm during the off-grid state. Moreover, the method includes using the energy to periodically power one or more electrical power systems used for idle operation or maintenance tasks of the wind turbine during the off-grid state.

The invention discloses a wind storage combined frequency modulation method and device based on a wind power participation coefficient and energy storage charge-discharge balance. The method comprises the following steps: firstly, calculating a kinetic energy margin and a power margin of a wind turbine generator in real time, generating a wind power participation coefficient by adopting LOGISTIC mapping, calculating a normalized SOC of an energy storage unit according to a grouping mode to obtain a balance degree, dynamically adjusting an energy storage droop coefficient based on the balance degree, and triggering charge and discharge role interchange when a single SOC approaches an upper limit and a lower limit. And then a combined state space model including wind power, energy storage, thermal power and controllable load is further constructed, model prediction control MPC or quadratic programming is adopted in a prediction time domain, constraint optimization distribution is performed on active power output of various resources, and finally a control instruction is issued in a rolling time domain mode to realize real-time closed-loop adjustment. According to the method, the fan operation safety and the energy storage service life are both considered, the maximum frequency deviation of the system is remarkably reduced by coordinating dynamic participation of wind power and energy storage, frequency oscillation is restrained, energy storage deep circulation is reduced, and good engineering implementation and remarkable economic benefits are achieved.

The invention belongs to the technical field of VSG network construction active support, and particularly discloses a transient support power coordination control method and system for a network construction type optical storage system, and the method comprises the steps: building an equivalent mathematical model of the network construction type optical storage system, and obtaining key control parameters of a virtual synchronous generator control link of the optical storage system based on the equivalent mathematical model; constructing an internal energy flow characteristic analysis model of the network construction type optical storage system based on key control parameters of a control link of the virtual synchronous generator, and further obtaining a core defect of passive participation of energy storage in transient response; and based on the core defects, designing an energy storage driving control strategy based on VSG transient response power decomposition to control an energy storage subsystem to charge and discharge, and completing transient support power coordination control of the network construction type optical storage system. The problems that in the prior art, due to the fact that energy storage passively participates in frequency modulation, response timeliness and accuracy are insufficient, and due to the fact that VSG transient control complexity is high, large-scale engineering application adaptability is poor are solved.

The invention discloses a wind and light energy storage adaptive event triggering reinforcement learning control method and system, and relates to the technical field of new energy power generation and energy storage system intelligent control. The trigger frequency can be automatically adjusted according to the operation state by utilizing a dynamic threshold mechanism, and response delay or frequent updating caused by a traditional fixed threshold is avoided. The algorithm only performs strategy updating at a necessary moment, so that the calculation burden and the communication pressure are effectively reduced. Aging cost and time discount factors are introduced into the reward function, and unified optimization of short-term smoothness and long-term service life is achieved. The optimal control strategy can be obtained through experience learning without an accurate model, and the adaptability of the system under complex working conditions is enhanced.

The invention discloses an off-grid photovoltaic hydrogen production system double-layer optimization method, device and equipment and a storage medium, and the method comprises the steps: constructing an off-grid photovoltaic hydrogen production system based on a battery energy storage unit, a photovoltaic power generation unit and a hydrogen energy conversion unit, and constructing a double-layer optimization model comprising an upper-layer constant volume optimization model and a lower-layer operation optimization model; the upper-layer constant volume optimization model takes the maximization of the total yield of green hydrogen in the whole life cycle of the system as a target and takes the system capacity configuration as a decision variable; the lower-layer operation optimization model takes green hydrogen yield maximization in the current scheduling time period of the system as a target and takes a system operation strategy as a decision variable; and an optimal capacity configuration scheme and an optimal operation strategy are obtained by solving the double-layer optimization model, so that the utilization efficiency of the system on renewable energy sources is improved, the overall low-carbon benefit is enhanced, and the potential of the electrolytic cell is fully played.

The invention discloses a building light storage energy economic scheduling and power compensation management system and method, and relates to the technical field of building energy management, and the method comprises the following steps: obtaining scheduling data in a future preset scheduling period, carrying out the prediction analysis based on the scheduling data, and generating a macroscopic charging and discharging scheduling strategy; the method comprises the following steps: acquiring a sky image sequence by using a visual sensor, analyzing the movement of a cloud cluster based on the sky image sequence to predict the descending trend of photovoltaic power, and sending a pre-compensation instruction to an energy storage converter and controlling the energy storage converter to charge and discharge before the actual descending of the photovoltaic power. According to the method, the descending trend of the photovoltaic power can be accurately predicted in advance, the pre-compensation instruction is sent to the energy storage converter before the actual falling of the power, the peak-valley electricity price arbitrage income is maximized through the combination of high-precision prediction and accurate pre-compensation, and the optimization and improvement of the overall performance of the building optical storage system are further realized.

The invention discloses a frequency modulation and peak regulation cooperative control method for a wind storage combined power station, and belongs to the technical field of new energy power station operation control. The method aims to solve the problem that control targets are not matched due to the fact that frequency modulation and peak regulation demand characteristics cannot be effectively distinguished when an existing wind storage combined power station responds to a power grid dispatching instruction. According to the method, a received power station level total active power instruction is decomposed into a high-frequency component which changes rapidly and a low-frequency component which changes gently, and the power adjusting ranges of the high-frequency component and the low-frequency component are determined based on wind power plant output prediction data and the real-time charge state of an energy storage system. The high-frequency component is mainly distributed to the energy storage system to serve as a core part of a charging and discharging instruction, meanwhile, the low-frequency component is combined with a wind power plant basic power generation plan to form a target power generation instruction, and finally the instruction is issued to a corresponding subsystem to be executed. The method is used for improving the cooperative response capability of the wind storage combined power station to the power grid frequency modulation and peak regulation composite demand, and resource optimization configuration and system stable operation are achieved.

A heat generating device includes: a sealed container; a tubular body provided in a hollow portion of the sealed container; a heat generating element provided on an outer surface of the tubular body and configured to generate heat by occluding and discharging hydrogen supplied to the hollow portion; and a flow path formed by an inner surface of the tubular body and through which configured to allow a fluid that exchanges heat with the heat generating element to flow. The heat generating element includes a base made of a hydrogen storage metal, and a multilayer film provided on the base. The multilayer film has a first layer made of a hydrogen storage metal and having a thickness of less than 1000 nm, and a second layer made of a hydrogen storage metal, which is different from that of the first layer, and having a thickness of less than 1000 nm.

The invention discloses a black-start method for an energy storage system of a new energy power station. The method comprises a normal black-start mode and a low-electric-quantity black-start mode. Before black start, all converters of the energy storage system are traversed; when a state of charge (SOC) value of a battery connected with at least one converter in the energy storage system is greater than a threshold value, executing a normal black-start mode; and when the SOCs of all the converters in the energy storage system are smaller than a threshold value, executing a low-electric-quantity black-start mode. According to the method, the starting sequence of the converters is preferentially selected, and the photovoltaic inverter is automatically started and the power of the photovoltaic inverter is limited in the black-start process to assist the energy storage system to establish stable voltage and frequency, so that the black-start success rate of the energy storage system is improved.

The invention relates to the technical field of energy storage systems, in particular to an energy storage system power smoothing method and system based on model predictive control. By introducing the adaptive prediction model and combining with the dynamic frequency decomposition module, the power signal can automatically adjust the frequency decomposition threshold according to the dynamic change of the signal, so that the flexibility and precision of frequency decomposition are remarkably improved, and the accuracy of frequency decomposition is improved by automatically adjusting the frequency decomposition threshold on the basis of the dynamic change information. Therefore, the power difference value sequence is decomposed into a plurality of dynamic frequency components, the change trend of each frequency component is predicted, the future power requirement can be estimated more accurately, the charging and discharging strategy of the energy storage equipment is adjusted in real time, it is guaranteed that the energy storage system can provide efficient and accurate power compensation in practical application, and the energy storage efficiency is improved. According to the invention, the parameters of the adaptive prediction model can be corrected in real time, and the continuous smoothing of the power of the energy storage system is realized by continuously optimizing the frequency decomposition precision and the power prediction accuracy.