1083 results about "Battery energy storage system" patented technology

Disclosed a decision-dependent chance-constrained optimal model for enhancing resilience of power distribution system under renewable generation uncertainty through strategically setting-up and activating dispatchable diesel generators, renewable distributed generations, battery energy storage systems, and switchable devices. By incorporating the information of decision variables, a moment-based ambiguity set is employed to depict the uncertainty arising from renewable distributed generators. By leveraging convex approximations to handle the considered joint chance constraints, the disclosed model is transformed into a tractable mixed-integer second-order conic programming problem to be solved.

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 linkage protection method of a battery energy storage system and the battery energy storage system. The linkage protection method of the battery energy storage system comprises the following steps: S1, monitoring multi-dimensional operation parameters of a battery pack in real time; s2, performing parallel feature extraction on the multi-dimensional operation parameters based on a preset dynamic association model; s3, establishing a three-dimensional safety assessment coordinate system, performing vector overlay analysis on each representation value and a corresponding axial threshold boundary, and outputting four-stage dynamic safety level criteria; and S4, activating the hierarchical protection coprocessor according to the dynamic security level criterion. According to the method, through the core design of multi-dimensional dynamic correlation modeling and hierarchical cooperative control, the problems of response delay and protection blind areas of a traditional method under complex working conditions are solved, an innovative three-dimensional safety evaluation system recognizes potential risks in advance, the cooperative efficiency of a hierarchical protection mechanism is improved, and the false triggering rate of disconnection decision is reduced.

To provide a system and an apparatus for implementing a mobile energy system.SOLUTION: In an aspect, a mobile energy system includes a cabinet having an interior space defined by an outer surface of the cabinet, and the interior space can include a battery storage area configured to receive a battery energy storage system having at least 2 kWh of storage capacity. The mobile energy system can also include an item storage area configured to receive and store one or more other items, a connector configured to connect the battery energy storage system located in the battery storage area to an external power source, and a charging cable configured to connect the battery energy storage system to a charging port of an electric vehicle.SELECTED DRAWING: Figure 4

The invention provides a dynamic reconfigurable battery energy storage system balance control method and device based on PWM duty ratio modulation. Belongs to the battery system control field. Voltage information of all single batteries in the energy storage system is collected in real time, total loop current, system operation modes and temperature distribution are monitored synchronously, a controller dynamically calculates charge state values of all the single batteries based on the information, a target object to be balanced is recognized, and meanwhile a global battery consistency evaluation index is established. The method dynamically adjusts the maximum allowable equalization current and generates an equalization topology. The modulation frequency, the duty ratio spectrum amplitude and the phase distribution are adjusted through PWM, and the maximum duty ratio is limited. All the operation instruction sets take effect synchronously at the starting moment of the next equalization period. Besides, the efficiency and working condition mapping table in the historical learning library is synchronously updated to form a closed-loop self-evolution optimization mechanism, so that the balance efficiency optimization of the system in a dynamic scene is realized, and the voltage overshoot is ensured to be within a set threshold value.

The invention discloses a plateau multi-energy complementary agricultural energy management system and a plateau multi-energy complementary agricultural energy management method, and belongs to the technical field of new energy. Wind, light and terrestrial heat multi-energy complementation is cooperated with a battery energy storage system and a phase change heat storage system, and a central intelligent management system is used for carrying out priority scheduling and real-time monitoring and prediction on a load; efficient energy supply of irrigation, processing and greenhouse heating is achieved, the renewable energy utilization rate and the load satisfaction degree are remarkably improved, the operation cost and environmental pollution are reduced, safe and efficient operation of the system is ensured, and good economic and environment-friendly effects are achieved.

The present disclosure provides a coupling network model lithium-ion battery energy storage system fire spread modeling method, which belongs to the technical field of lithium-ion battery model construction and simulation method. The coupling network model lithium-ion battery energy storage system fire spread modeling method includes: obtaining battery electrochemical parameters, material thermophysical parameters and energy storage system geometric characteristic parameters of a battery energy storage system; establishing a three-dimensional geometric model of air domain inside the energy storage system and performing a grid division; calculating the heat generated inside batteries during thermal runaway; solving the heat transfer and the thermal runaway propagation process between batteries, and calculating the battery temperatures; calculating the gas generation inside batteries during thermal runaway; solving jet dynamics parameters of batteries; and, solving the conservation equations of fluid regions in the battery energy storage system, to predict the fire spread behavior inside an energy storage power station.

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.

The invention discloses a vehicle network charging and discharging optimization method and system based on a dynamic electricity price, and relates to the technical field of smart power grids and electric automobiles, and the method comprises the steps: S1, constructing a prediction model of the polarization degree of a battery through an electrochemical model and historical operation data, obtaining a quantification result of the polarization degree of the battery, and obtaining a prediction result of the polarization degree of the battery; s2, according to the quantification result of the battery polarization degree, combining the dynamic electricity price data and the user demand data, adopting a reinforcement learning algorithm, constructing a charging and discharging strategy optimization framework, outputting a preliminary charging and discharging strategy, determining the adaptability of the strategy in different scenes, and obtaining a smooth charging and discharging curve; according to the vehicle network charging and discharging optimization method and system based on the dynamic electricity price, intelligent management of the charging and discharging process of the battery is achieved, the service life of the battery is effectively prolonged, the energy utilization efficiency is improved, economic benefits are maximized, and technical support is provided for efficient operation of a battery energy storage system.

The invention relates to a reconfigurable battery energy storage system grid-connected and off-grid seamless switching control method and device. The method comprises the following steps of: sensing a real-time power grid state, pre-judging a system operation mode, and acquiring a millisecond-level panoramic information flow of the power grid state through a high-speed sampling voltage sensor, a high-speed sampling frequency sensor, a high-speed sampling phase sensor and a high-speed sampling communication interface. And pre-judging the stability and disturbance trend of the power grid through a deep learning algorithm, executing a power distribution and voltage support algorithm in grid-connected and off-grid modes, and calculating an optimal switching opportunity point and a system reconstruction target topology scheme. Meanwhile, the harmonic distortion rate and the voltage sag depth are calculated in real time through discrete Fourier transform, so that a mode pre-judgment mechanism is automatically triggered. After switching, key parameters such as voltage, frequency and power are automatically corrected through real-time sampling and observation, and zero-sensing switching is achieved. The method can effectively improve the response speed and stability of the battery energy storage system when the power grid fails, and guarantees the safe operation of the power grid.

The invention provides a method for realizing in-phase online equalization of a modular battery energy storage system based on an NLM, and the method comprises the steps: S1, regularly obtaining SOCj, x and (1-SOC) j, x, rechargeable energy SOEj, x and dischargeable energy SODEj, x of a module DC side battery through a battery management system BMS according to an equalization control period Tequ; s2, acquiring an equalization index of each module according to engineering requirements, determining an input priority sequence during charging and discharging, and generating a battery voltage queue of all modules; and S3, obtaining the size of a modulation wave in each power control period, and determining the first k modules which should be input currently and the total number k of the input modules. In-phase equalization is realized by fully utilizing an alternating-current reactive energy exchange process and a reactive state of the system, a blind area of a traditional method is eliminated, an application range of the in-phase equalization is expanded, in-phase module equalization is realized in each power frequency period, an operation boundary of the system is not influenced at all, charging of some modules in one power frequency period is realized, and charging efficiency is improved. Some modules discharge, and the equalization speed is higher.

The invention relates to the technical field of battery energy storage, and discloses a battery energy storage health state assessment method and system, and the method comprises the steps: analyzing the constant-power charging and discharging process of a lithium battery, and obtaining health factors highly related to the battery energy storage health state through Pearson correlation analysis; constructing a bidirectional long short-term memory network model, taking the health factor highly related to the battery energy storage health state as model input, and outputting an energy storage battery health state estimation value; and optimizing the bidirectional long-short-term memory network model by improving a Kepler optimization algorithm and introducing a differential evolution strategy. According to the invention, the improved Kepler optimization algorithm is combined with the bidirectional long short-term memory network (BiLSTM) and the attention mechanism (Attention), so that the accurate estimation of the health state of the battery energy storage system is realized, the safety and reliability of the battery management system are improved, the high-precision evaluation of the health state of the lithium battery is realized, and the reliability of the battery management system is improved. And the robustness and generalization ability of the model under complex working conditions are improved.

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 discloses a waste heat-demand two-stage optimization design method for a multi-energy combined supply Carnot battery system, and belongs to the field of energy storage and comprehensive energy utilization, and the method comprises the steps: determining the energy demand and waste heat source condition of a target energy supply object; constructing a multi-energy combined supply Carnot battery energy storage system model composed of a multi-energy conversion subsystem and a Carnot battery subsystem; the method comprises the following steps: performing parameter optimization on performance expressions of an energy storage loop and an energy release loop of a Carnot battery subsystem through first-layer optimization, and determining Carnot battery system performance and state parameters of each point under unit cold and heat source flow; and through second-layer optimization, multi-objective optimization is carried out on the efficiency of the first law of thermodynamics, the efficiency of the second law of thermodynamics and the economical efficiency of the system, and the optimal heat source flow input into the energy storage loop, the optimal heat storage water flow input into the multi-energy conversion subsystem, the optimal heat storage water flow input into the energy release loop and the corresponding overall performance of the Carnot battery system are determined.

The invention relates to a sodium electric energy storage system dynamic partition power control method based on string type cluster level management, which comprises the following steps of: firstly, realizing physical isolation of battery clusters through a string type framework, configuring an independent power conversion module and a cluster level controller for each cluster, acquiring voltage, current, SOC (state of charge) and SOH (state of health) of each cluster in real time, and on the basis of the data, in a discharging or discharging process, determining the state of charge of each cluster; a dynamic partition strategy and automatic adjustment of power distribution are realized according to inter-cluster SOC, SOH, voltage range, temperature range, power limit and other differences, and an energy storage system is dynamically divided into a high-energy high-health area, a high-energy medium-health area, a medium-energy high-health area, a medium-energy medium-health area, a low-energy or sub-health area and a fault early warning area in a discharging and charging mode; and rapid balance of electric quantity among clusters is realized through the converter module, so that power distribution is ensured to meet power grid requirements, overcharge and overdischarge of batteries are avoided, and the service life of a battery system is prolonged.

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.

The embodiment of the invention provides a digital simulation modeling method and device of a tandem type hybrid electric propulsion system, computer equipment and a medium, and relates to the technical field of simulation modeling, and the method comprises the following steps: constructing a turboshaft prime mover model, constructing a generator model, connecting the turboshaft prime mover model and the generator model in series to generate a generator set, the power generation groups are connected in parallel to construct a turbine power generation system; constructing a propulsion system; constructing a battery energy storage system; constructing a power transmission and distribution system, and respectively connecting the power transmission and distribution system with a turbine power generation system, a propulsion system and a battery energy storage system; and constructing a comprehensive control and energy management system, and outputting a digital simulation modeling result through a turbine power generation system, a power transmission and distribution system and a battery energy storage system. According to the scheme, a simulation modeling method based on multi-physics field coupling double-power-source dynamic response and energy flow regulation and control provides reliable modeling technical support for engineering application of a tandem type hybrid electric propulsion system.

The invention discloses a dynamic thermal management and risk pre-judgment system for a lithium battery energy storage system, and relates to the technical field of lithium battery energy storage, and the system comprises a thermal field monitoring module which generates a real-time three-dimensional thermal field distribution map of a battery pack; the dynamic regulation and control module is used for self-adaptively regulating the heat dissipation power and the refrigerant flow in combination with the charging and discharging states of the battery and the environmental parameters; the risk assessment module is used for constructing a thermal runaway risk grade assessment model and generating a risk probability value; the early warning response module triggers a multi-stage early warning mechanism according to the risk probability value, and is linked with the dynamic regulation and control module to execute an emergency heat dissipation strategy to generate a risk disposal scheme; and the data archiving module is used for storing data. According to the invention, the whole-process intelligent design of monitoring, regulation and control, evaluation, early warning and archiving is provided, the thermal management precision, the risk prevention and control capability and the operation economy of the lithium battery energy storage system are comprehensively improved, and a key technical guarantee is provided for large-scale energy storage application.

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.

Systems and methods for detecting intermittent connections in a battery energy storage system (BESS) subsystem are disclosed. For each battery rack in the BESS subsystem, current time series data is received. A current rolling average is determined for each data point of the time series data by averaging current values of timestamps over a specified time interval. A current delta is determined for each data point, where the current delta is a difference between the current rolling average associated with the battery rack under analysis and a mean of the current rolling averages associated with the other battery racks in the BESS subsystem. A distribution profile of the current deltas is analyzed to detect a current anomaly at the respective battery rack. In response to detecting the current anomaly at the battery rack under analysis, an alert indicative of a faulty connection is displayed on a user interface.

When supporting ancillary services for a target power system, existing solutions consider a fixed capacity of the battery energy storage system. In contrast, disclosed embodiments leverage a forecast of ancillary events, in combination with an optimization model, to produce an optimal determination for ancillary services. In particular, required capacity may be calculated from the forecast of ancillary events, and a capacity constraint may be generated from the required capacity and incorporated into the optimization model. Then, the optimization model may be solved to produce an optimal determination for ancillary services.

The invention discloses a short-process preparation method and application of a vanadyl sulfate electrolyte based on vanadium slag valence regulation and control, and belongs to the technical field of vanadium electrolytes. The method comprises the following steps: leaching the vanadium slag by using sulfuric acid to obtain a leaching solution containing low-valence vanadium; extracting vanadium and chromium in the leachate by adopting an amine organic extraction agent; carrying out reverse extraction by using sulfuric acid; the method comprises the following steps of: firstly, extracting and separating vanadium by using a phosphoric acid extracting agent, and finally, carrying out reverse extraction by using sulfuric acid to obtain the vanadium electrolyte which can be used for constructing a VFB-5kW / 10kWh vanadium battery energy storage system. The traditional established thinking that pentavalent vanadium is extracted through vanadium slag oxidation to serve as a vanadium source to prepare the vanadium electrolyte is broken through, the novel technology for extracting the low-valence vanadium solution from the vanadium slag to directly prepare the vanadium electrolyte is provided, the short-process and green novel technology for preparing the vanadium electrolyte from the vanadium slag is constructed, the efficiency of the vanadium electrolyte preparation technology is improved, and the preparation cost is reduced.

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 relates to the technical field of battery energy storage system management, and relates to a battery energy storage system management method based on multiple energy optimization, and the method comprises the steps: obtaining the actual value of each evaluation index corresponding to each to-be-used phase change material, and selecting the phase change material most suitable for each battery unit in a battery energy storage system; packaging a phase change material in a material with good thermal conductivity, and tightly attaching the phase change material to the surface of each battery unit; a plurality of temperature sensors are installed in a battery energy storage system, the temperature of each battery unit corresponding to each monitoring time point is monitored in real time, and the phase change state of a phase change material in each battery unit at each monitoring time point is analyzed; according to the method, the thermal management efficiency of the battery energy storage system can be remarkably improved, and the safety and reliability of the system are enhanced. Through accurate thermal management, the performance of the battery is optimized, the service life is prolonged, and the overall efficiency of the system is improved.

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.

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 an intelligent scheduling method and system for a battery energy storage system, and the method comprises the steps: generating a multi-dimensional operation state matrix through obtaining the charge state, charge-discharge rate and temperature data of a battery unit, and combining the power grid load and power market price information; according to the multi-dimensional operation state matrix, calculating an electric energy distribution proportion of each battery unit by adopting a preset state-of-charge threshold and charge-discharge rate constraint, and generating an initial electric energy distribution scheme; if a battery unit whose charge-discharge rate exceeds a safety range exists in the initial electric energy distribution scheme, predicting a performance attenuation trend based on historical operation data, and adjusting a distribution proportion to generate a corrected electric energy distribution scheme; according to the corrected electric energy distribution scheme, real-time temperature data are obtained, the local overheating risk is judged, and a temperature adjustment instruction set containing heat dissipation power adjustment parameters is generated. The operation efficiency and the economic benefit of the battery energy storage system can be effectively improved, and meanwhile the safety and the stability of the system are guaranteed.

The invention discloses a distributed energy storage system operation scheduling method and device based on a block chain. The method comprises the following steps: collecting and obtaining household power consumption data through a household energy management system; calculating the minimum operation cost to obtain a family quotation or a family preference selection sequence, and sending the family quotation or the family preference selection sequence to the smart contract; the method comprises the following steps: collecting and obtaining set market data through an energy storage operator energy management system, obtaining an energy storage operator quotation or an energy storage operator preference selection sequence through maximum profit calculation, and sending the energy storage operator quotation or the energy storage operator preference selection sequence to an intelligent contract; the intelligent contract determines an energy storage charging and discharging set value at a time point according to a pre-agreed rule between the household user and an energy storage operator and sends the energy storage charging and discharging set value to a controller of the household battery energy storage system; and the controller of the household battery energy storage system controls the operation of the household battery energy storage system according to the energy storage charging and discharging set value. According to the method, the problem of interest conflict between stakeholders is solved while the facilities of the battery energy storage system are effectively managed.

Provided are a control method and apparatus, an electronic device, and a storage medium. The method comprises: issuing alternating-current active power to corresponding bidirectional energy storage converters so as to adjust current distributed by each bidirectional energy storage converter; and controlling each direct-current power converter on the basis of a target current distribution ratio so as to adjust current distributed to each battery cluster. By controlling alternating-current active power issued to the bidirectional energy storage converters to be a given value, the current of each direct-current bus is controlled, so that battery stacks are simultaneously fully charged or fully discharged; in addition, the current is distributed on the basis of the current ratio of battery clusters in a same stack to reduce system differences, thereby greatly improving the consistency, service life, working efficiency and depth of charge and discharge of a whole battery energy storage system.

The invention discloses a fault early warning determination method and device, a storage medium and an electronic device. The method comprises the following steps: acquiring temperature data corresponding to a plurality of battery cells in a battery cluster; the cluster characteristic temperature of the battery cluster and the intra-cluster temperature difference in the battery cluster are calculated according to the temperature data, and the temperature difference is used for indicating the temperature difference value between the highest battery cell temperature and the lowest battery cell temperature in the battery cluster; comparing the cluster characteristic temperature with an absolute temperature threshold to obtain a first comparison result; and / or comparing the intra-cluster temperature difference with a temperature difference threshold value to obtain a second comparison result; and determining the message alarm content of the energy storage fault based on the first comparison result and the second comparison result. The problems of inaccurate temperature control and untimely fault early warning in the battery energy storage system are solved. The temperature data of the battery cells in the battery cluster are monitored and analyzed in real time, the characteristic temperature and the temperature difference are calculated and compared with the threshold value, the fault state is determined, corresponding alarm is triggered, and timely early warning of temperature abnormity of the battery energy storage power station is achieved.