478 results about "Battery energy storage system" patented technology

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 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 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 an energy storage system and a parallel operation control method thereof. The system comprises a battery cluster, a battery management system and an energy storage converter. The battery management system is respectively connected with the battery clusters and the energy storage converter, and the plurality of battery clusters are connected with the energy storage converter through the coupling circuit. Wherein a pre-charging equalization loop is arranged between the battery cluster and the energy storage converter, and the battery management system is used for controlling connection or disconnection of a circuit. The battery management system is also provided with a threshold module which is integrated with a plurality of parallel operation thresholds and is used for judging the switching-on or switching-off time of the contactor. By constructing a coupling system containing a pre-charging equalization loop, the problems of impact current and device damage caused by large inter-cluster voltage difference in the parallel operation process of a traditional multi-battery energy storage system are solved; and meanwhile, through a strategy of setting multiple parallel operation threshold values, targeted current balancing can be carried out according to different dynamic working conditions and electric energy parameter differences, the impact current is prevented from being too high, components are protected, and the operation stability of the system is improved.

The invention discloses a multi-energy complementary coordination control system and coordination control method based on mixed water and light storage. The system comprises a data acquisition unit, a data storage unit, a coordination control unit, an optimization scheduling unit and a telecontrol communication unit. The data acquisition unit is in data connection with the hydropower station, the photovoltaic power station and the energy storage system; the coordination control unit is in communication connection with the data storage unit; the optimal scheduling unit is in communication connection with the coordination control unit; and the telecontrol communication unit is used for issuing the active power setting instruction generated by the coordination control unit and the optimization scheduling unit to the hybrid hydropower station, the photovoltaic power station and the battery energy storage system. According to the method, active power control with real-time performance, coordination and robustness is realized, the consumption capability of new energy is improved, and the impact of new energy access on power grid operation is relieved.

The invention discloses a battery energy storage system predictive maintenance method and system based on a large language model, and relates to the field of battery energy storage system predictive maintenance, and the method comprises the following steps: collecting multi-modal sensor time sequence data of a battery energy storage system, and carrying out the interception through a sliding window to obtain a multi-modal sensor time sequence data fragment; inputting the time series data fragments of the multi-modal sensor into a large language model for feature extraction to obtain a probabilistic semantic tag set; the probabilistic semantic tag set analyzes a causal relationship between probabilistic semantic tags through a fault mode correlator, and calculates to obtain a dynamic risk score and a recommendation action; and adjusting operation parameters of the battery energy storage system according to the dynamic risk score, and executing the recommended action at the same time to realize predictive maintenance of the battery energy storage system. According to the invention, the problem of lack of real-time dynamic labeling during maintenance of the battery energy storage system in the prior art can be solved.

The invention discloses a power system cascading failure chain modeling and blocking method, device and system considering source-load double-end uncertainty, and a medium. The method comprises the steps of constructing source-load uncertainty input distribution (wind power introduces Weibull distribution based on a wind speed segmented power model, photovoltaic introduces Beta distribution based on an irradiance output model, and a load side introduces a normal distribution fluctuation model); an MSFF method is adopted to construct a unified source-load stochastic power flow model, and a multi-scene power flow state set is obtained; introducing a power flow out-of-limit criterion and a hidden fault probability function, building a cascading fault propagation model fusing wind-solar load uncertainty, and dynamically simulating fault chain evolution; and formulating a staged collaborative blocking strategy (cutting off non-critical load emergency control, quickly responding a battery energy storage system and dynamically adjusting a critical line protection constant value) to realize real-time fault suppression. Simulation shows that the method is suitable for power system security defense in a high-proportion new energy penetration scene, and has good engineering adaptability and dynamic control performance.

A battery management apparatus 102 calculates a state of charge SOC representing the state of charge of a chargeable and dischargeable battery, a charge deterioration degree SOHQ and a resistance deterioration degree SOHR, corrects the calculated SOHR, corrects an mid resistance MidDCR corresponding to a mid voltage MidVoltage according to a correction coefficient in accordance with SOHR for MidDCR (corrected SOHR), calculates MidVoltage (a mid voltage present between a discharge voltage in the current state of charge of the battery, and a voltage value representing a discharge voltage in the minimum state of charge of the battery), calculates the remaining capacity of the battery based on SOC and SOHQ, and calculates the available energy of the battery based on the mid voltage and the remaining capacity.

The invention discloses a power distribution network multi-terminal optimization collaborative voltage regulation method fused with power interval prediction, and belongs to the technical field of power system operation and control, and the method comprises the steps: building a convolutional neural network model to predict the photovoltaic output and load power of a power distribution network in a future time period; carrying out load flow calculation based on power prediction, identifying a key bus according to the estimated maximum value of each bus voltage in the interval, calculating the required voltage regulation quantity of the key bus, and determining a voltage regulation target; based on dynamic voltage sensitivity analysis, with minimization of power compensation as a target, reactive compensation of a photovoltaic inverter and active compensation of a battery energy storage system are coordinated in sequence according to an optimal proportion, and finally interval adjustment of all bus voltages is achieved. According to the invention, voltage out-of-limit can be effectively suppressed in the high photovoltaic permeability power distribution network, the requirements of reactive and active compensation are significantly reduced, the safety of system operation is enhanced, and the service life of equipment is prolonged.

The invention relates to the technical field of batteries, and discloses a state-of-health correction method and device for a battery energy storage system and storage equipment, and the method comprises the steps: enabling the battery energy storage system to start charging and discharging, calculating the accumulated discharge capacity, and obtaining the remaining capacity; calculating a theoretical health state based on the accumulated discharge capacity and the remaining capacity; storing the theoretical health state in a memory; under the condition that the battery energy storage system is restarted, recalculating the accumulated discharge capacity, and calculating the actual health state; determining a target health state based on the theoretical health state and the actual health state in the memory; and correcting the theoretical health state in the memory based on the target health state. According to the method, the theoretical health state in the memory is corrected based on the better and more reliable target health state, the health state abnormal data in the memory is thoroughly eliminated, automatic recovery of the health state storage abnormity is realized, and the correctness and reliability of the health state stored in the memory are guaranteed.

The invention discloses an island micro-grid frequency coordination control method based on flywheel and battery hybrid energy storage, and provides a hybrid energy storage coordination control method for solving the problem that a diesel generator in an island micro-grid is low in inherent response speed and difficult to deal with rapid load disturbance in time. The method combines the advantages of a flywheel energy storage system (FESS) and a battery energy storage system (BESS) to construct a multi-time-scale frequency regulation mechanism: the FESS is responsible for absorbing or releasing a high-frequency power component and quickly responding to instantaneous fluctuation; the BESS bears an intermediate-frequency power component and realizes medium-term energy regulation; and the diesel generator compensates the low-frequency power component and maintains long-term steady-state operation. Through the multi-unit collaborative hierarchical control, the frequency stability and the operation reliability of the island micro-grid are remarkably improved, the dynamic regulation pressure of the diesel engine is reduced, and the frequent charge-discharge cycle of the battery is reduced, so that the service life of the energy storage system is prolonged.

Systems and method to minimize conditions that cause sub-synchronous oscillation (SSOs) associated with series compensated transmission grids. The implementations ensures the correct development of methods and systems that can mitigate sub-synchronous oscillation (SSOs) associated with a series compensated transmission grid and enhance the series compensation efficiency. An example implementation is a network-based SSO mitigation technology, and another example implementation is a generator-based SSO mitigation technology. The discovery and example implementations are applicable to series compensated transmission networks with synchronous generators, induction generators, wind turbines, solar photovoltaic generators, charging stations, battery storage systems, high-voltage DC transmission systems, STATCOMs, inverter-based data centers, and other inverter-based resources.

According to a method to aid installation of large-scale BESS in a power network, a hyperparameter optimization engine generates a feasible configuration of BESS defined by location and sizing parameters subject to an installation constraint. A power system simulation engine conducts an energy market simulation for the power network with the generated configuration over a defined simulation horizon to determine a configuration value. The power system simulation engine comprises one or more subroutines characterizing the impact of the BESS on the market clearing mechanism, to compute an expected generation cost associated with the BESS. The configuration value is determined based on the expected generation cost and a total installation cost of the BESS. The hyperparameter optimization engine is iteratively executed to generate an updated configuration based on the configuration values of previous configurations, to determine a final configuration of BESS defined by a set of optimal location and sizing parameters.

The invention discloses a power system operation strategy generation method and device, equipment, a medium and a product, and belongs to the technical field of power system automation control. The method comprises the following steps: establishing a cooperative operation model of a wind turbine generator and a battery energy storage system participating in power grid primary frequency modulation; deriving an analytic expression of frequency stability constraints of the power system based on the collaborative operation model, wherein the frequency stability constraints comprise a maximum frequency change rate constraint, an overshoot constraint and a static frequency deviation constraint; constructing a wind power uncertainty model based on the uncertainty budget; constructing a mixed integer linear programming scheduling model taking the minimum total operation cost as a target; and solving the mixed integer linear programming scheduling model to obtain a power system operation strategy. According to the embodiment of the invention, the frequency safety level of the power system can be remarkably improved under the wind power uncertainty.

The invention discloses a dynamic reconfigurable battery energy storage system active equalization method and device based on open-circuit voltage detection, and belongs to the technical field of battery energy storage systems. Open-circuit voltage data of all single batteries are collected in real time in a high-precision mode, battery states are dynamically grouped through an improved K-means clustering algorithm, circuit topology is flexibly adjusted through a reconfigurable switch array, and energy priority transfer between groups is achieved. Multi-step shortest path control is adopted in the equalization process, and high-efficiency charge adjustment is achieved; the system is provided with a self-adaptive monitoring mechanism, balancing is automatically stopped when the single voltage difference converges to a set threshold value, and key data are filed. The method can also automatically detect and isolate abnormal single batteries, improves the safety and reliability of the system, is suitable for a multi-scale energy storage scene, and has the advantages of high equalization speed, high precision, strong adaptability and the like.

Generally disclosed herein is a mechanism to mitigate power fluctuations of a data center by dynamically charging and discharging a battery energy storage system (BESS). According to some examples, a BESS control system can be configured to monitor power demand fluctuations and initiate charging of the BESS during periods of low power demand. One example of a period of low power demand includes active idle, wherein the workloads of the server machines frequently decrease by a small magnitude. Another example of a period of low power demand includes deep idle, wherein the workloads of the server machines decrease by a larger magnitude than the active idle for a longer duration. The system may discharge the power from the BESS during the peak power demand. The BESS control system may stabilize the data center power system through fast-acting voltage and frequency control at a system level.

The invention belongs to the technical field of electricity-hydrogen coupling system control, and provides a voltage-air pressure stability control method and system for an electricity-hydrogen coupling system. The voltage-air pressure stability control method for the electricity-hydrogen coupling system comprises the steps that a battery energy storage system serves as an execution unit, and a voltage regulation model is constructed based on the dynamic relation between voltage and current; a solid hydrogen storage system is used as an object, and an air pressure adjusting model is constructed based on the relation between flow and pressure; constructing a hydrogen production / hydrogen consumption model based on hydrogen production / hydrogen consumption behaviors of the electrolytic cell and the fuel cell; on the basis of real-time sharing of state variables of an electricity-hydrogen coupling system, charging and discharging of a battery energy storage system in a millisecond period are adjusted according to a voltage adjusting model, so that rapid and stable control over the voltage of a direct-current bus is achieved. And regulating and controlling the hydrogen charging and discharging flow of the solid hydrogen storage system in a second-level time scale according to the air pressure regulation model to ensure the stable pressure of the buffer tank and continuous hydrogen supply, regulating the electrolysis and fuel cell power according to the hydrogen production / consumption model to ensure the balance of energy supply and demand, and finally realizing the voltage-air pressure stability coordinated regulation and control between the electric domain and the hydrogen domain.

The invention relates to the technical field of hybrid energy system optimization control, in particular to a hybrid energy system optimization method and system based on multi-agent reinforcement learning, and the method comprises the steps: constructing an equipment mathematical model of a hybrid energy system comprising a solar photovoltaic system, a battery energy storage system and a hydrogen energy storage system; a multi-agent reinforcement learning control framework for energy scheduling optimization is designed, and the framework takes solar photovoltaic real-time available power, a battery charge state and a hydrogen storage tank state as state variables, and takes battery charge and discharge power, electrolytic cell charge power and fuel cell discharge power as action spaces; minimization of system operation cost and optimization of battery usage are taken as targets; a multi-agent near-end strategy optimization MAPPO algorithm is adopted to train agents, and an energy scheduling strategy is optimized online through interactive learning of the agents and a system environment so as to maximize a preset cumulative reward target and realize dynamic and adaptive control of system operation.

The invention discloses a multistage early warning linkage control method and system for an energy storage system, and relates to the technical field of safety of battery energy storage systems, and the method comprises the steps: obtaining multi-modal real-time data streams, including voltage, current, temperature, specific gas concentration and internal pressure of a box body, of a single battery / battery box layer in the energy storage system; performing time sequence alignment and feature level fusion on the multi-modal real-time data stream to generate a fusion feature vector; inputting the fusion feature vector into a pre-trained dynamic risk assessment model, and outputting a comprehensive risk score and a corresponding early warning level of the battery; and according to the early warning grade, executing a matched linkage control strategy by following a grading progressive principle. According to the method, the basic statistical characteristics, the related characteristics and the model driving characteristics are fused, the coupling rule among the parameters is comprehensively identified, the pre-trained dynamic risk assessment model is matched, the comprehensive risk score and the early warning level are output, and the safety protection requirements of different risk levels are accurately matched.

The invention relates to the technical field of battery fault diagnosis, in particular to a battery monomer safety early warning positioning method, which comprises the following steps of: establishing a voltage and temperature consistency model of a battery module, setting a comprehensive consistency evaluation score for evaluating the battery module, and then calculating a weight coefficient of each index of the battery module, and carrying out clustering analysis on the voltage and / or temperature data set of the battery monomers so as to determine the battery monomers meeting a preset abnormal condition, and carrying out statistics on a fault probability change condition of each battery monomer of the battery module in a period of time to obtain a battery monomer safety early warning positioning result. Therefore, the problems that abnormal battery monomers cannot be accurately detected and positioned, battery monomer faults are difficult to count and classify, an effective safety early warning mechanism of the battery monomers cannot be established and the like due to the fact that a system structure in a battery energy storage system is complex and data mining and mathematical statistics methods are not adopted to analyze operation data are solved.

Embodiments of the present application provide a method, device, system, computer-readable storage medium and computer program product for diagnosing BESS fault. The method includes: obtaining detection values from multiple different information sources configured for the BESS; inputting the detection values to a BESS fault diagnosis model constructed based on multi-information source data input, the types of the detection values are a subset of the types of the multi-information source data; and receiving a fault diagnosis result outputted by the BESS fault diagnosis model. The technical solutions of the present application can achieve early diagnosis of BESS fault.

This invention provides a method, apparatus, and equipment for capacity optimization configuration of a wind-gas-storage virtual power plant, belonging to the technical field of virtual power plants. The method includes: filtering the load power deviation curve to obtain a first frequency signal and a second frequency signal; calculating the minimum rated capacity of the gas turbine generator set based on the first frequency signal; calculating the minimum rated capacity of the battery energy storage system based on the second frequency signal; calculating the operating cost of the wind-gas-storage virtual power plant based on the power of the gas turbine generator set and the power of the battery energy storage system; constructing an objective function based on the operating cost and the environmental cost of the wind-gas-storage virtual power plant; and solving the objective function using a particle swarm optimization algorithm to obtain the optimized power of the gas turbine generator set and the optimized power of the battery energy storage system. This invention addresses the deficiency in current virtual power plant capacity planning configurations that do not consider the output characteristics of wind power, gas turbines, and energy storage batteries, potentially leading to power instability during peak load periods.

The invention relates to the technical field of safety control of an electric power energy storage system, and discloses a battery energy storage system for fast frequency modulation and a control method thereof, and the system comprises a distributed power buffer module array which is used for absorbing or releasing a high-frequency fluctuation component in a power instruction from a power grid dispatching end; a subarea countercurrent liquid cooling subsystem, wherein a cooling loop of each liquid cooling subarea adopts a countercurrent arrangement mode; and the global energy router is used for selecting part of the battery clusters to execute the power instruction according to the power instruction and the state of each power buffer module, and synchronously adjusting the cooling intensity of the corresponding liquid cooling partition. According to the method, external millisecond-level power impact is converted into gentle thermal load and periodic stress relaxation in the battery through triple defense lines, so that the problem of local thermal runaway of the electric energy storage system in a rapid frequency modulation scene is solved, and the safety and durability of the electric energy storage system in long-term and high-strength rapid frequency modulation service are ensured.

This invention discloses an insulation monitoring method and system for cascaded battery energy storage systems. The monitoring method includes the following steps: constructing a signal acquisition module, with a switch and bias resistor connected in series between the positive and negative busbars and ground; acquiring the voltages of the positive busbar to ground and the negative busbar to ground of the battery clusters when the first and second switches are in different on / off states; calculating the insulation resistance values ​​of the positive and negative busbars to ground based on the voltages of the positive and negative busbars to ground, and sending them to a fault diagnosis module; judging the insulation performance of each battery cluster based on the insulation resistance values, and sending the data to a control and protection module; and controlling the corresponding battery cluster to take control and protection actions based on the insulation performance data. The monitoring method proposed in this invention has a simple structure and can detect double-point grounding faults, unaffected by the equal or similar decrease in the insulation resistance of the positive and negative busbars to ground.

The present application relates to the technical field of power energy storage, and particularly relates to a multi-battery energy storage system SOC equalization control method based on event triggering, aiming at the phenomenon of large calculation and periodic communication overhead in the prior art, and solving the problem of limited SOC equalization control accuracy in a large-scale system. The core of the method is to combine a distributed dynamic equalization control protocol and an event triggering mechanism to realize on-demand communication and power distribution among multiple batteries in the system, and to reduce the communication frequency and calculation complexity of the system. The method is suitable for multi-battery energy storage systems with high efficiency and reliability requirements.

The invention relates to the technical field of high-voltage energy storage system control, and discloses a fault quit method of a high-voltage cascade direct-hanging energy storage system, which comprises the following steps of: 1, continuously monitoring the working state of a battery energy storage system by a battery management system in the energy storage system so as to capture a fault signal, and analyzing the captured fault signal according to a preset rule base. A scheme of combining fault grading response and time-limited self-healing is adopted, faults are graded, temporary and reversible electronic bypass fault-tolerant processing is introduced for recoverable general faults, and a self-healing mechanism with a time window is set, so that power links with instantaneous recoverable faults are automatically recovered and run again after the faults are eliminated; and the online capacity and the charge-discharge capacity of the energy storage system are maintained. And for a serious fault, executing a redundancy strategy, mechanically bypassing a faulty chain link, removing the faulty chain link, and maintaining the overall operation of the system. And carrying out system shutdown operation aiming at an emergency fault.

The present application relates to the technical field of energy storage battery, in particular to a forward-looking energy storage frequency modulation power distribution method and system; the method has a double-time scale structure of minute-level strategy adjustment + second-level real-time control. On the minute-level time scale, an AGC signal statistical feature extraction and prediction framework is constructed to predict the AGC signal characteristics and dynamically adjust and optimize the weight; on the second-level time scale, multi-objective optimization is performed every 2 seconds to distribute the charging and discharging power among the battery units, minimizing the AGC tracking error, battery degradation and SOC deviation. The scheme can significantly reduce the battery degradation cost while maintaining good frequency modulation performance and SOC consistency; by capturing the time statistical characteristics of the AGC signal, the potential impact of the AGC signal on the battery degradation is quantified, that is, the influence of the change trend of the AGC signal on the battery energy storage system is considered, providing forward-looking support for the control strategy of power distribution.

The invention provides an abnormity identification method of an energy storage system and a related device, and the method comprises the steps: determining the operation state data of the energy storage system, and the operation state data comprises voltage data and temperature data; then, carrying out distribution similarity evaluation on the voltage data and the temperature data so as to determine the distribution similarity of the voltage data and the temperature data; and if the distribution similarity is smaller than a preset similarity threshold, determining that an area corresponding to the operation state data is an abnormal area which comprises an abnormal battery cluster. And the potential abnormal part is identified through the distribution similarity of the temperature and the voltage, so that the accuracy of abnormal identification of the energy storage system is greatly improved. Abnormity can be identified from the angle of distribution consistency, and the early warning capability is higher; only voltage and temperature data of conventional operation of the system are needed, extra detection is not needed, cost is low, and implementation is easy; algorithm automation degree is high, and results are objective and reliable; and the method has low requirements on data quality and is suitable for various battery energy storage systems.

The present invention relates to an arrangement for a cooling system in a battery storage device, comprising: at least two connection ports for coolant lines; a connecting hose with at least two hose ends comprising at least one radially inwardly projecting gas-tight sealing lip and at least one support lip adjacent to the sealing lip in the axial direction, wherein the connecting hose is designed to fluidically connect the connection ports to each other, wherein the support lip has at least one axially through opening.