375 results about "Grid energy storage" patented technology

A distributed photovoltaic consumption-oriented energy storage planning method and system for a flexible distribution network. The method comprises: acquiring grid data, photovoltaic data and load data of a distribution network in a target area, preprocessing the data, screening the preprocessed data, and selecting fault data; on the basis of the selected fault data and a genetic algorithm, establishing a distribution network energy storage system capacity configuration model; and on the basis of the distribution network energy storage system capacity configuration model, performing distributed photovoltaic consumption-oriented flexible distribution network energy storage planning.

The invention discloses a power grid energy storage capacity demand determination method and system based on multiple time scales, relates to the technical field of power grid energy storage capacity demand calculation, and aims to solve the problem of inaccurate energy storage capacity demand calculation. By generating multiple scenes, quantitatively screening key scenes and incorporating various uncertain factors, energy storage capacity calculation focuses on high-influence scenes, the coping capacity of the scheme to actual risks is enhanced, decision scientificity is improved, ultra-short-term to long-term multi-time scales are divided, core contradictions of all the scales are captured in a targeted mode, limitation of a single scale is avoided, and energy storage capacity calculation efficiency is improved. According to the method, capacity requirements and equipment distribution are integrated, operation rules are defined, visual documents are generated, multi-scale energy storage cooperative operation is achieved, the stability of a power grid is guaranteed, meanwhile, cost is reduced, scheme landing performance and operation efficiency are improved, multi-time-scale power grid state prediction is carried out based on a dynamic database, and historical rules and real-time data are combined, so that the power grid state prediction efficiency is improved. And the prediction coordination is ensured through multi-dimensional verification.

The invention relates to the technical field of energy storage configuration, in particular to an energy storage configuration method and system for a photovoltaic off-grid system, and the method comprises the following steps: obtaining illumination intensity and component output change, recognizing a slope abrupt change section, marking the change trend, extracting the difference between the energy storage change and the power generation direction, and grouping a delay response time period; and extracting operation paths, sorting and matching the operation paths to a response section, setting a multiplying power change direction, synchronizing unselected path states, sequentially arranging adjustment instructions, and writing the adjustment instructions into a control channel to obtain a photovoltaic off-grid energy storage configuration scheme entry set. According to the method, a change section is constructed by identifying sudden change of a power slope, response lag adjustment is set by combining energy storage and power generation direction comparison, rate matching is carried out, charge state and discharge fluctuation double indexes are introduced through path sorting, path selection precision is improved, rate setting is adjusted in parallel according to priorities, and an adjustment instruction is generated in cooperation with time mapping. And the energy storage response and control synchronism in the sudden change scene is enhanced.

The invention discloses an electric vehicle V2G micro-grid energy storage capacity optimization method based on dynamic planning, particularly relates to the technical field of micro-grid energy storage optimization, and aims to solve the problem of energy storage capacity optimization defects caused by spatial dynamic characteristics caused by mobility of an existing electric vehicle. Performing geographic grid division on the node position, generating a space-time matrix by combining with a timestamp, and identifying a high-frequency access node; constructing a state transition equation based on the inter-node impedance matrix, and setting a node-level safety boundary by taking a line capacity change rate as a dynamic constraint; a staged reverse dynamic programming algorithm is adopted, spatial dimension optimization is preferentially executed on the high-frequency access nodes, and charging and discharging constraints fusing voltage deviation and capacity overrun penalty terms are generated; carrying out global optimization by taking the minimization of the total operation cost as a target after the constraints are integrated, and outputting an energy storage capacity configuration strategy of each time period; and finally generating an energy storage deployment scheme.

The invention discloses a multi-source information fusion-based dynamic cooperative regulation and control method for a transmitting-end power grid energy storage station, and relates to the field of power grid energy storage regulation and control. The method comprises the following steps: compressing global heterogeneous data, and extracting a low-dimensional critical feature flow; constructing a dynamic coupling potential energy field, and quantifying gradient intensity to capture recessive instability; generating a layered fractal regulation strategy, resolving conflicts and outputting an instruction and a residual error; constructing a topological phase change trigger network, and triggering regulation and control through spectrum gap jump; causal tracing and model evolution are carried out, and parameters are optimized to form a closed loop. According to the invention, through fractal cooperation, topological response and evolution closed loop, regulation and control collaboration, instability response speed and system adaptability are improved, and safe and stable operation of a power grid is guaranteed.

The invention provides a grid-connected and off-grid seamless switching method and system for a network-constructed energy storage micro-grid, belongs to the technical field of grid-connected and off-grid switching, and realizes rapidity and stability of micro-grid mode switching through multi-stage cooperative control. The method comprises the following steps: a power grid state real-time monitoring stage: acquiring power grid short-circuit capacity, impedance angle, voltage amplitude, frequency and phase parameters through impedance spectrum analysis and phase-locked loop cooperative detection; a pre-synchronization-hybrid control-dynamic damping three-stage switching stage; a steady state maintaining stage: maintaining a system damping ratio gt through a multi-target cooperative controller; and in the whole switching process, the bus voltage fluctuation is less than or equal to 2%, and the frequency deviation is less than or equal to 0.1 Hz. According to the method, MPC pre-synchronization, hybrid control of dynamic weight, virtual impedance adaptive compensation and multi-target collaborative optimization are controlled through model prediction, so that the problems are solved, seamless switching is realized, and the quality of electric energy is improved.

The invention relates to the technical field of intelligent power grids, in particular to a micro-grid energy storage optimization method and system based on big data analysis, and the method comprises the steps: obtaining the comprehensive prediction power generation through the prediction segmentation time, a wind power generator set and a solar power generator set, and obtaining the analysis power based on the prediction segmentation time and the comprehensive prediction power generation, an energy storage battery parameter set is obtained, if the analysis electric quantity is larger than or equal to a storage electric quantity threshold value, a target storage battery pack is retrieved from the energy storage battery packs through the energy storage battery parameter set, active equalizing charging is conducted on the target storage battery pack, and an updated storage battery pack is obtained; and after it is confirmed that a preset target energy supply battery pack is retrieved in the energy storage battery packs by using the analysis electric quantity and the energy storage battery parameter set, power is supplied by using the target energy supply battery pack, and an updated power supply battery pack is obtained. According to the method, the energy storage of the micro-grid can be accurately and intelligently optimized.

The invention relates to the technical field of power grid energy storage, in particular to a voltage fluctuation rapid suppression method based on a composite energy storage system, which realizes targeted response to voltage fluctuation of different frequencies by setting a dual-time scale power distribution strategy, improves the improvement efficiency of the energy storage system, and improves the suppression efficiency of the composite energy storage system. Through a composite control structure of an adaptive PI controller and a feedforward compensation link, the voltage control precision and the harmonic suppression rate are improved, and according to peak-valley electricity price characteristics and load fluctuation rules of different scenes, the power grid line voltage fluctuation type is monitored in real time, and a dynamic parameter library and an online identification algorithm are combined. The system can automatically adapt to factors such as hardware aging and environment change, a long-term control effect is maintained, and the charging and discharging frequency of the lithium iron battery is reduced by setting the high-frequency power buffer effect of the super capacitor, so that the cycle life of the lithium iron battery is prolonged; meanwhile, the overall energy conversion efficiency of the system is improved through cooperative control of the modular multilevel converter topology and the double energy storage elements.

The invention provides a network construction type energy storage wide short circuit ratio adaptive stability control method and system, and the method comprises the steps: carrying out the calculation based on a power grid energy storage parameter, power grid impedance and energy storage impedance, and obtaining a dynamic short circuit ratio; according to the dynamic short-circuit ratio, switching the power grid operation condition mode to a power grid operation condition mode corresponding to the dynamic short-circuit ratio; in a power grid operation working condition mode, obtaining optimized virtual inductance resistance parameters or frequency-variable admittance regulator parameters; a corresponding control instruction is generated according to the virtual inductance resistance parameters or the frequency-variable admittance regulator parameters, and self-adaptive stability control is completed; real-time identification and dynamic adjustment of the power grid impedance and the energy storage impedance are achieved, traditional fixed parameter control limitation is broken through, the dynamic short-circuit ratio is obtained through calculation, the problem of power angle instability under the wide short-circuit ratio is solved, corresponding switching of power grid operation working condition modes can be conducted based on the dynamic short-circuit ratio, differential control requirements of a weak power grid and a strong power grid are considered, and the method is suitable for large-scale popularization and application. And the full-working-condition adaptive capacity is improved.

The invention discloses a networking type energy storage semi-physical simulation test platform and method, and particularly relates to the field of simulation testing, and the platform comprises a digital twin collaborative modeling module, an impedance adaptive hardware coupling module, a networking control depth verification module, a multi-dimensional performance evaluation module, and an iterative optimization module. According to the method, a dynamic impedance network model and a virtual energy storage unit are integrated by constructing a power grid-energy storage digital twin; the dynamic impedance network is generated by adopting a frequency-dependent parameter transmission line equation and combining actual measurement impedance scanning data in a fitting manner; in the loop test, a full-band disturbance injection method is adopted to monitor impedance characteristics, and virtual inertia and physical droop control parameters are coordinated under a preset weak power grid working condition; the multi-dimensional performance evaluation system quantifies the system performance from three dimensions of dynamic response, stability margin and transient energy function, and when the phase margin deviation is greater than 15 degrees, triggers an iterative optimization mechanism, reconstructs a virtual inertia coefficient and repeatedly verifies the virtual inertia coefficient until a stability threshold is met.

The invention provides a micro-grid energy storage optimal configuration method and system, and relates to the technical field of energy storage system optimization. According to the method provided by the invention, a micro-grid energy storage configuration and optimization scheduling model taking the energy storage network construction capability of the micro-grid as an evaluation standard is established; establishing a target function by taking the overall operation benefit optimization of the micro-grid as a target; determining a plurality of constraint conditions based on the micro-grid energy storage configuration and the optimal scheduling model; according to the actual parameters of the micro-grid, the objective function and the multiple constraint conditions are solved, the optimal configuration and scheduling result of the micro-grid is obtained, the method provided by the invention can determine the optimal configuration and scheduling result according to the actual scene of the micro-grid, and then scheduling strategies corresponding to different time periods are obtained. The energy storage investment and construction cost can be reduced, the micro-grid operation cost can be reduced, the new energy utilization rate can be improved, meanwhile, it is guaranteed that the system has the enough inertia level and frequency adjusting capacity under the disturbance condition, and the use requirements of users in different use scenes are met.

The invention discloses a regional distributed energy storage optimization scheduling method, which comprises the following steps: S1, model construction: constructing a mixed integer nonlinear programming model containing a multi-objective optimization function according to physical characteristics, operation constraints and economic objectives of a regional power distribution network, a micro-grid, an energy storage system and renewable energy; s2, scene generation and processing: adopting a Latin hypercube sampling method to generate a multi-scene data set of renewable energy output, load demand and electricity price fluctuation, performing clustering analysis on scene data, and screening out representative typical scenes so as to reduce calculation complexity; and S3, carrying out optimization solution. In the application, multi-dimensional constraints such as energy storage life attenuation, network loss, carbon emission and the like are added in constraint conditions, the practicability of the model is improved, and the limitation of traditional single-target scheduling is broken through through multi-target optimization and multi-constraint coordination.

The invention discloses a network construction type energy storage optimization method and system based on power grid strength constraint, and belongs to the technical field of power grid energy storage optimization. Obtaining a reduced frequency domain admittance matrix based on power synchronization control and a node admittance matrix of the power system; constructing an optimization target model of the power system according to the multi-dimensional stability evaluation index and the reduced frequency domain admittance matrix; constructing a double-layer reinforcement learning model which comprises a first TD3 model and a second TD3 model, and repeating alternate iteration of the first TD3 model and the second TD3 model until an optimization target model of the power system is met; and obtaining a selection node and a capacity of the network construction type energy storage unit output by the first TD3 model when the optimization target model of the power system is satisfied, and taking the selection node and the capacity as a network construction type energy storage optimization configuration result of the power system. According to the invention, efficient site selection and constant volume of the network-forming type energy storage system can be realized, and the stability and the new energy accepting capability of a power system are improved.

The invention discloses a power grid operation safety margin improvement method and system. The method comprises the steps of obtaining power grid data and performing preprocessing; constructing a power grid simulation model based on the preprocessed data to perform power grid fault simulation; identifying key nodes of the power grid based on a power grid fault simulation result; based on the power grid key nodes, constructing a power grid load prediction model and predicting load conditions of the power grid key nodes; obtaining a power grid safety margin through a current load and a load demand value predicted by the load prediction model, and deploying an energy storage regulation and control strategy at a key node in combination with the power grid safety margin; and network security encryption is carried out. According to the invention, the load prediction result is combined with the power grid energy storage system, and under the guidance of the load prediction result, the dynamic distribution and adjustment of power are realized, the change of the power grid load is coped with in time, the optimal configuration of power resources is realized, the power grid pressure during the peak load period is reduced, and the stable operation of the power grid is ensured. And the safety margin and the operation efficiency of the power grid are improved.

The invention relates to the technical field of lithium ion battery negative electrode materials, and discloses a preparation method and application of a high-efficiency silicon-carbon composite graphite material, and the preparation method comprises the following steps: S1, carrying out porosity and size regulation and control on silicon particles: carrying out ball milling on industrial-grade silicon powder to obtain nano silicon particles, and carrying out acid etching to form a porous structure; s2, functional surface treatment and interface optimization: introducing functional molecules to the surfaces of the silicon particles and coating a layer of ultrathin SiO2 protective film; and S3, carbon coating and flexible protection layer construction: performing pyrolysis on the porous silicon particles by using a carbon source to form a uniform carbon coating layer which is applied to a lithium ion battery negative electrode material, and the lithium ion battery is used for an electric vehicle, a power grid energy storage system and portable electronic equipment. Through the collaborative design of the flexible protection layer, the double-layer carbon coating and the gradient coating, the technical bottlenecks of the silicon-based negative electrode material in the aspects of long cycle stability, high rate performance and interface chemical stability are systematically solved.

The invention discloses a distributed power grid dispatching management and optimization method, and relates to the technical field of power grid automation, and the method comprises the steps: collecting multi-dimensional power grid data in a system, carrying out the data preprocessing of the multi-dimensional power grid data, carrying out the electrical load prediction of the initial multi-dimensional power grid data through an LSTM neural network, and carrying out the optimization of the electrical load. Performing energy storage SOC state real-time evaluation on the electrical load data based on a DTW dynamic time warping load identification model, performing state judgment on power grid equipment according to an evaluation result, constructing a multi-target optimization model by using mixed integer second-order cone programming, performing power grid constraint adjustment by using the multi-target optimization model, and performing power grid constraint adjustment on the basis of a power grid constraint result. And performing real-time power generation plan adjustment by using an improved particle swarm algorithm to obtain target electric power output of the power grid, and performing power grid energy storage control optimization according to the target electric power output. And the prediction accuracy of the new energy output and the load demand is obviously improved.

The invention provides a control method of an off-grid energy storage device and the off-grid energy storage device. The control method comprises the following steps: collecting power grid voltage state data of a power grid; when it is judged that the power grid voltage state data meet the pre-configured mode switching condition, the amplitude and phase of the power grid voltage in the power grid voltage state data are obtained; the mode switching conditions comprise an energy storage-power grid switching condition for switching from battery pack power supply to power grid power supply and a power grid-energy storage switching condition for switching from power grid power supply to battery pack power supply; and the control module is used for controlling the mode change-over switch circuit to perform corresponding switching on the basis of a mode switching condition conforming to the state data of the power grid voltage, and controlling the amplitude and the phase of the inverter voltage output by the bidirectional AC / DC conversion module on the basis of the amplitude and the phase of the power grid voltage. The amplitude and the phase of the load voltage received by the load before and after mode switching are in a continuous state, so that the switching time is shortened, and the power failure risk of a user is reduced.

The invention relates to the technical field of power distribution network planning management, in particular to a power distribution network energy storage planning optimization aid decision-making system and method, and the system comprises a data collection module, a prediction analysis module, a permeability analysis module, a bearing capacity evaluation module, an adaptability analysis module and a planning optimization module. Wherein the data acquisition module is used for acquiring related operation data of a new energy automobile and a charging facility; the prediction analysis module is used for predicting the near, medium and long-term scales of the new energy vehicle and the charging facility; the permeability analysis module is used for analyzing the influence of disordered charging and ordered charging on the power distribution network; the bearing capacity evaluation module is used for establishing a bearing capacity evaluation model; and the adaptability analysis module is used for identifying potential overload points and bottlenecks. By integrating new energy automobile charging load prediction, permeability analysis and power distribution network bearing capacity evaluation, power distribution network planning and operation are optimized, the efficiency and stability of a power grid are improved, and meanwhile wide application of new energy automobiles is supported.

The invention relates to the technical field of power grid energy storage control, and particularly discloses a network construction type energy storage system and a control method thereof, and the system comprises a parameter collection module which obtains the voltage, frequency, short-circuit capacity ratio, phase angle and other power grid operation parameters of a grid-connected point in real time; the scene recognition module judges the power grid scene of the energy storage system according to the acquired parameters, wherein the power grid scene comprises a weak power grid scene, a fault scene, an oscillation scene, a phase angle jump scene and a power loss scene; the strategy library module stores control strategies for each scene, including active / reactive control, active / reactive decoupling, overload support, low-frequency oscillation suppression, phase angle stabilization and black start strategies; and the adaptive control module retrieves and calls a corresponding strategy from a strategy library according to an identification result, performs adaptive control on the energy storage system, and realizes intelligent response and stable support for a complex power grid environment. According to the invention, intelligent response and stable support of the energy storage system to a complex power grid environment are effectively realized.

Systems and methods for supplying power (both active and reactive) at a medium voltage from a DCSTATCOM to an IT load without using a transformer are disclosed. The DCSTATCOM includes an energy storage device, a two-stage DC-DC converter, and a multi-level inverter, each of which are electrically coupled to a common negative bus. The DC-DC converter may include two stages in a bidirectional configuration. One stage of the DC-DC converter uses a flying capacitor topology. The voltages across the capacitors of the flying capacitor topology are balanced and switching losses are minimized by fixed duty cycle operation. The DC-DC converter generates a high DC voltage from a low or high voltage energy storage device such as batteries and / or ultra-capacitors. The multi-level, neutral point, diode-clamped inverter converts the high DC voltage into a medium AC voltage using a space vector pulse width modulation (SVPWM) technique.

The invention discloses a microgrid storage load coordination control optimization method and system, and relates to the technical field of power grid control, and the method comprises the steps: analyzing a target historical generating capacity record of a target microgrid, and obtaining a predicted generating capacity; analyzing the target historical electricity utilization record to obtain a target electricity utilization type set; performing correlation analysis on the power consumption time and the power consumption types to obtain a correlation result, and establishing a schedulable power consumption type set; calling a load prediction plan to obtain a predicted electrical load; and comparing the predicted generating capacity with the predicted electrical load to obtain a predicted comparison result, and generating a coordination control plan. According to the method, the technical problems of low energy utilization efficiency and operation stability of the micro-grid caused by inaccurate power generation capacity and load prediction and insufficient energy storage and load scheduling optimization in the prior art are solved, and coordinated optimization control of energy storage and load of the micro-grid is realized; and the energy utilization efficiency and the operation stability of the micro-grid are improved.

A hybrid load-energy storage system applicable to a microgrid of a hydrometallurgical plant, includes: a plurality of first electrical equipment, a plurality of second electrical equipment, first energy storage equipment, and second energy storage equipment. An electric usage priority of the first electrical equipment is lower than that of the second electrical equipment. The first energy storage equipment is on-grid and off-grid energy storage equipment, and the second energy storage equipment is grid-forming energy storage equipment. The first electrical equipment is connected to the first energy storage equipment via branches provided with first circuit breakers, and the second electrical equipment is connected to the second energy storage equipment via branches provided with second circuit breakers. The first second energy storage equipment are respectively connected to an AC bus via branches provided with a third and a fourth circuit breakers, and the AC bus is connected to an external power grid.

The invention discloses a power grid intelligent planning and load prediction integration method. The method comprises the following steps: S1, acquiring load data of a power system; s2, acquiring historical load data, and predicting load data by adopting an LSTM neural network according to the historical load data and the acquired load data; s3, acquiring renewable resource generating capacity, historical meteorological data and meteorological data predicted by weather forecast, and predicting the renewable resource generating capacity by adopting a random forest according to the renewable resource generating capacity, the historical meteorological data and the meteorological data predicted by the weather forecast; s4, evaluating demand data of the power system for the energy storage system according to the predicted renewable energy power generation amount and load data; and S5, according to the demand data, generating a power grid energy storage system planning strategy including charging and discharging time and power distribution. By optimizing the operation strategy of the energy storage system, the power grid can more flexibly cope with load change and fluctuation of renewable energy sources, and the operation risk of the power grid is reduced.

The present application relates to the field of power grid energy storage, and discloses a power grid energy storage method considering wind and light uncertainty and timing characteristics, comprising: obtaining wind and light load typical seasonal scenes by SOM clustering method for scene reduction, establishing a multi-time scale energy storage model considering long-term energy storage, and constructing a power grid wind and light storage stochastic programming model considering the economy and low carbon of power grid investment; the present application solves the power balance during the day by constructing a long-short-term multi-time scale hybrid energy storage model suitable for real conditions; and at the same time, the wind and light output uncertainty and the calculation efficiency are considered, typical scenes are generated by using the SOM clustering method, and wind and light load typical seasonal data sets are obtained, so as to ensure the calculation accuracy and improve the calculation efficiency.

The invention relates to the technical field of power system energy storage optimization, and discloses a terminal micro-grid energy storage optimization configuration method and system and a computer readable storage medium. Comprising the steps of generating load demand probability distribution and a new energy output confidence interval through deep learning and Bayesian probability modeling based on historical load and new energy monitoring data, extracting boundary parameters and mapping the boundary parameters into a quantum state initial solution set, and generating a quantum coding instruction set; a quantum algorithm population is initialized, a non-dominated solution set sequence is generated through quantum gate evolution operation, and a Pareto leading edge output optimization configuration scheme is screened; verifying feasibility in combination with local voltage data, and generating an executable control instruction set after fine tuning of capacity-position weight; and driving the energy storage unit to execute charging and discharging operation, collecting operation data, updating model parameters, finally separating probability weights and quantum deviations, adjusting a Bayesian model and resetting quantum gate parameters to generate a calibration instruction set. According to the invention, the energy storage configuration efficiency and precision can be obviously improved.

The invention relates to the technical field of micro-grid operation strategy scheduling, and discloses a micro-grid energy storage operation scheduling strategy determination method and device. The method comprises the following steps: predicting multi-source data of a current time period of a microgrid according to an improved GRU neural network to obtain predicted multi-source data in a preset future time period; optimizing the operation scheduling strategies of the microgrid in various operation states by adopting a decision module combining a Markov decision and a Q learning algorithm, and determining an optimal operation scheduling strategy in various operation states; determining an operation state corresponding to the predicted multi-source data, and taking the optimal operation scheduling strategy in the operation state as a predicted optimal operation scheduling strategy in a future preset time period; the operation of the microgrid in the preset future time period is realized based on the predicted optimal operation scheduling strategy, and the energy utilization efficiency and the operation stability of the microgrid are improved.

The invention relates to the technical field of power grid energy storage regulation and control, in particular to a power grid energy storage regulation and control method and system considering source-storage-load collaborative interaction. The power transmission node information of the power grid system and the power utilization information of each terminal user are acquired, the power grid system is divided into a plurality of virtual energy storage clusters according to the power transmission node information, and load fluctuation characteristic analysis is performed on the power utilization data of all the terminal users of each virtual energy storage cluster; determining a first importance degree of each load area to the electric energy demand; obtaining a second importance degree of each load area in an abnormal state according to the load power change before and after the power generation fault; and according to the first importance degree and the second importance degree of each load area, correspondingly configuring the electric energy guarantee priority of each load area and supplying power until the power generation fault is repaired. According to the technical scheme, after the power grid system has a power generation fault, cooperative adjustment of the energy storage station, the power supply station and the load end is realized, and the accuracy of electric energy distribution is effectively improved.

The invention belongs to the field of power grid energy storage configuration, and discloses a power grid energy storage optimal configuration method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring peak-valley period data of a power grid; constructing an effective arbitrage time length calculation formula based on the power grid peak and valley time period data; acquiring related data of an extreme risk event in the power grid; constructing a multi-dimensional risk influence factor based on risk event related data in the power grid; constructing an internal yield implicit equation by integrating an effective arbitrage duration calculation formula and the multi-dimensional risk influence factors; converting the internal yield implicit equation into a linear equation to obtain an internal yield probability function; converting the internal yield probability function into a constraint condition, solving a pre-constructed optimal configuration model which comprehensively considers economy and power grid stability, and obtaining a power grid energy storage optimal configuration scale; the economical efficiency and the power grid stability are comprehensively considered, and the energy storage configuration scale meeting the requirements of the economical efficiency and the power grid stability can be obtained.

The present invention discloses a semi-physical simulation test platform and method for grid-type energy storage, which specifically relates to the field of simulation testing, including a digital twin collaborative modeling module, an impedance adaptive hardware coupling module, a grid control depth verification module, a multi-dimensional performance evaluation module, and an iterative optimization module. The present invention integrates a dynamic impedance network model and a virtual energy storage unit by constructing a grid-energy storage digital twin. The dynamic impedance network adopts a frequency-varying parameter transmission line equation and is generated by fitting measured impedance scan data. In the in-loop test, a full-band disturbance injection method is used to monitor the impedance characteristics. Under a preset weak grid operating condition, the virtual inertia and physical droop control parameters are coordinated. The multi-dimensional performance evaluation system quantifies system performance from three dimensions: dynamic response, stability margin, and transient energy function. When the phase margin deviation is greater than 15°, an iterative optimization mechanism is triggered, the virtual inertia coefficient is reconstructed, and verification is repeated until the stability threshold is met.

The invention relates to a battery fault detection method based on index normalization, and belongs to the technical field of battery fault detection, and the method comprises the following steps: S1, collecting real-time voltage data and corresponding time sequences of all cells of a power battery pack in a power grid energy storage system; s2, on the basis of the real-time voltage data and the corresponding time sequence, calculating the average value and the standard deviation of the voltage of each battery cell of the battery pack at each moment, and performing Z-score standardization processing; s3, subtracting 1 from the standardized result, taking an absolute value, and performing index mapping to obtain an exp (Z-1) value of each battery cell; s4, setting a fixed threshold value T, and comparing exp (Z-1) values of the battery cells at each moment; and when exp (Z-1) of a certain battery cell exceeds a threshold value T, judging that the corresponding battery cell is a fault battery cell. According to the invention, real-time detection of faults of the power battery of the electric vehicle and the energy storage system can be effectively realized, and the faulted single body can be accurately positioned.