1257 results about "Optical storage" patented technology

According to the optical storage direct flexible system scheduling method based on multi-objective optimization and an adaptive scheduling strategy, monitoring devices are installed on a photovoltaic array, an energy storage unit and a load side, a data sensing network covering the whole link of'source-storage-load-network 'is constructed, and key data are collected in real time. A multi-objective optimization model with maximization of economical efficiency, reliability and clean energy consumption rate as objectives is established, and a hybrid optimization mechanism of a genetic algorithm and particle swarm optimization is adopted to generate a day-ahead scheduling reference scheme. And designing an adaptive scheduling algorithm and a dynamic parameter adjustment mechanism based on fuzzy logic, and combining a rolling optimization window to realize real-time optical storage coordination control and power real-time balance. According to the invention, the operation efficiency, stability and flexibility of the optical storage direct-flexible system are effectively improved, the capability of coping with emergencies is enhanced, and the optimization of the overall performance of the system is realized.

The invention discloses a light storage and charging energy allocation system based on data driving and a control method, and relates to the technical field of light storage and charging energy allocation, and the method comprises the following steps: carrying out the real-time collection of the real-time power generation amount of a photovoltaic power generation system, the current power state of an energy storage battery, and the power consumption data of a load; and cleaning, normalization processing and time serialization are carried out on the collected data, so that the accuracy and continuity of the input data are ensured. According to the invention, by monitoring the power consumption data of the load in real time, combining with the long-term energy prediction model and dynamically adjusting the energy storage and discharge strategy, excessive discharge in a non-peak period is avoided, sufficient energy storage in a peak period is ensured, the power grid dependence is reduced, and the power consumption cost is reduced. Through load sudden increase detection and an adaptive scheduling algorithm, the system can quickly cope with sudden load changes, preferentially guarantee power supply of key loads, flexibly adjust a discharge mode, improve endurance time and system stability, and maximize green energy utilization efficiency.

The invention discloses an optical storage direct-flexible system power scheduling method based on market model prediction response, which comprises the following steps: determining the composition of an optical storage direct-flexible system, and collecting operation state data and external environment data; constructing a hybrid prediction model, and predicting the market price and the uncertainty interval of the market price in the scheduling period; establishing a power scheduling optimization model, and solving to obtain an optimal power scheduling strategy; according to the optimal power scheduling strategy, a control instruction is issued to each control unit of the optical storage direct flexible system, and cooperative adjustment is carried out through a bidirectional coupling feedback mechanism of voltage and power; the market price and the system operation state are monitored in real time, and when the market price deviation exceeds a price deviation threshold value, scheduling strategy online correction is triggered. According to the robust optimization architecture, traditional power scheduling is converted into a confrontation game structure between the system and the market, and the resistance of the system to extreme price situations is improved while economic benefits are guaranteed.

The invention provides an optical storage and charging cooperative control method and system based on multi-energy complementation. The method comprises the following sub-steps: respectively establishing a photovoltaic power generation model, an energy storage system model and a charging load model; acquiring historical illumination information, charging information and electricity price information, constructing a prediction model based on a neural network, and predicting and outputting illumination intensity, charging load demand power and electricity price in a future time period; constructing a target optimization function by taking the annual net cost and the power deviation rate as optimization targets; according to the method, the cooperative optimization control of the photovoltaic power generation, energy storage and charging system is realized, the annual net cost is reduced, the power deviation is reduced, the energy storage and charging cooperative control strategy is established, the target optimization function is solved by adopting the improved whale optimization algorithm, and the charging and discharging power sequence is generated according to the optimal solution obtained by solving and is input to the system for execution. And the operation efficiency and reliability of the whole system are improved.

The invention discloses a multi-source data fusion-based optical storage load collaborative optimization scheduling system and method, and relates to the technical field of photovoltaic energy storage optimization, and the method comprises the steps: building a photovoltaic power generation scene tree model and a load prediction model through obtaining historical photovoltaic power generation data, load power consumption data and meteorological data; constructing a first optimization target and a second optimization target by considering the operation income and the energy storage aging cost, considering the photovoltaic uncertainty based on the photovoltaic power generation scene tree model, and establishing an adaptive optimization scheduling model in combination with the load demand predicted by the load prediction model; the photovoltaic power generation scene tree model and the load prediction model are embedded into the adaptive optimization scheduling model, and the optimal energy storage charging and discharging strategy of the current time period is solved, so that the robustness and reliability of energy storage scheduling are improved while the economical efficiency of photovoltaic power generation is ensured.

An optical storage system designed to compensate for the water hammer effect in hydropower turbines and its cooperative frequency modulation method are provided. The method involves detecting the water hammer effect and utilizing a pre-established system model integrating a hydropower unit, photovoltaic system, and hybrid energy storage system. Through model predictive control combined with a whale optimization algorithm, the governor parameters of the hydropower unit are optimized. The system then obtains the photovoltaic active power output and the battery's state of charge (SOC) within the hybrid energy storage system. Based on these parameters, a collaborative control strategy for the photovoltaic and hybrid energy storage systems is determined and executed. This strategy enables effective control of the photovoltaic system and / or hybrid energy storage to compensate for reverse power adjustments in the hydropower unit, addressing the water hammer effect and ensuring stable power grid operation.

The invention discloses an optical storage and charging integrated micro-grid energy management system, relates to the technical field of micro-grid energy management, and is used for solving the problems of low energy scheduling efficiency and insufficient stability in an optical storage and charging system. The system comprises a power generation monitoring module, an energy storage management module, a charging load control module and an energy coordination module. The photovoltaic power generation state and environmental parameters are monitored in real time through a multi-type sensor network, and the running state of the photovoltaic module is judged; based on battery monitoring data and photovoltaic output characteristics, a differential energy storage management strategy is formulated; the charging power is dynamically distributed in combination with the energy state to realize charging and discharging intelligent regulation and control; by converging multi-source information, source storage and load interaction is coordinated to cope with different power states; accurate monitoring, intelligent scheduling and efficient cooperation of the photovoltaic, storage and charging integrated micro-grid are realized, and the energy utilization efficiency and the operation stability are remarkably improved.

The invention provides an intelligent scheduling control method for an optical storage charging and discharging integrated power station, and the method constructs a multi-time-scale prediction-optimization-correction three-stage control architecture, and achieves the real-time scheduling of the optical storage charging and discharging integrated power station through the coordinated operation in the upper-layer 24-hour rolling optimization, the middle-layer real-time scheduling and the lower-layer equipment control. And multi-target and multi-time-scale coordinated control optimization of maximization of the photovoltaic consumption rate, minimization of the power grid electricity purchase cost and prolonging of the service life of the energy storage system is realized. And a model prediction control algorithm is combined to dynamically adjust photovoltaic power generation output, an energy storage charging and discharging plan and a charging pile scheduling strategy. In addition, an adaptive parameter adjustment mechanism is introduced, and MPC parameters are adjusted online by using a reinforcement learning algorithm so as to cope with dynamic changes of environmental parameters and equipment states. The method can effectively improve the operation efficiency and economy of the optical storage charging and discharging integrated power station, prolongs the service life of an energy storage system, and is suitable for intelligent scheduling control of various optical storage charging and discharging integrated power stations.

The invention relates to the technical field of data processing, and discloses a cold and hot data exchange method and system based on optical storage and a storage medium. The method comprises the following steps: performing access feature acquisition and analysis on data in the optomagnetic hybrid storage system, calculating an access life cycle factor, generating a logic interval heat evaluation result, performing temperature grading, formulating a cold and hot data placement strategy, generating a data placement mapping table, executing batch migration according to priority, and updating a data position record. According to the method, the problem of how to realize logic interval hot degree accurate identification, temperature grade dynamic grading, storage mapping optimal matching and batch migration task efficient organization under the optomagnetic hybrid architecture is solved.

The invention relates to the technical field of power system engineering, in particular to a power distribution network safety assessment method and system based on an optical storage and charging system, and the method comprises the steps: collecting three types of key data of the optical storage and charging system; based on the three types of key data, establishing a power generation prediction model, constructing an energy storage scheduling strategy, and generating a load characteristic curve; calculating a node voltage deviation value and a branch power loss value of the power distribution network to form a network state evaluation index; performing comparative analysis on the network state evaluation index and a preset safety threshold value, and when the node voltage deviation value or the branch power loss value exceeds the preset safety threshold value, marking an abnormal node position; and for the abnormal nodes, adjusting the charging and discharging power of the energy storage system and the operation mode of the charging facility, and outputting optimized operation parameters of the optical storage and charging system. Through cooperative operation of the photovoltaic power generation system, the energy storage system and the charging facility, accurate evaluation and dynamic regulation and control of the node voltage and the line power loss of the power distribution network are realized, and the operation safety and the energy complementation efficiency of the power distribution network are improved.

The invention relates to the field of optical storage, and particularly discloses an optical storage system cooperative control method and device, a terminal and a medium, and the method comprises the steps: collecting multi-dimensional data in real time, including photovoltaic array data, user side load data, power grid side information data, meteorological data and weather forecast information; generating a photovoltaic power generation power prediction curve, a user load demand prediction curve and a power grid electricity price prediction curve by using the multi-dimensional data through a machine learning model; and taking the current state of the optical storage system and each prediction curve as input parameters, carrying out optimization problem solving based on a multi-objective optimization function and constraint conditions through a model prediction control algorithm, generating an optimal control sequence in a period of time in the future, and controlling corresponding equipment through the optimal control sequence. According to the method, the response speed to uncertainties such as illumination abrupt change and load fluctuation is increased, source-storage-load-network coordination is realized, the sub-optimal problem of independent control of each unit is avoided, the operation cost is reduced, and renewable energy consumption is improved.

The invention discloses an energy storage capacity configuration method for cluster regulation and control of an optical storage and charging station, relates to the technical field of capacity configuration, and effectively solves the problem of balancing economy and robustness of a traditional method through a hierarchical collaborative energy storage capacity configuration mechanism. The established source-load difference uncertainty model accurately quantifies the space-time coupling characteristics of the photovoltaic output and the charging load, and avoids capacity redundancy caused by deterministic planning; independent energy storage is configured on the basis of sub-cluster differentiation requirements, repeated investment of distributed energy storage is reduced through local fluctuation stabilization, and meanwhile, single-point capacity requirements are reduced by using complementary characteristics in clusters; shared energy storage is introduced and a cross-cluster collaborative optimization model is constructed, so that the overall capacity utilization rate is remarkably improved; on the premise that high-proportion photovoltaic consumption and reliable power supply of a charging load are guaranteed, the adaptability to extreme scenes is enhanced through a layered response mechanism, and an extensible solution is provided for a power system.

The invention discloses a system processing method and device, a storage medium and electronic equipment, and relates to the technical field of optical storage. The method comprises the following steps: acquiring historical generating capacity data of a photovoltaic power generation system, historical state information of an energy storage system and historical consumption data of load equipment; inputting the historical generating capacity data, the historical state information and the historical consumption data into a target prediction model, and predicting to obtain generating capacity data of the photovoltaic power generation system in a first preset time period and load demand data of the load equipment in the first preset time period; generating an initial operation plan according to the generating capacity data and the load demand data; and determining a target operation plan based on the initial operation plan, and adjusting the operation states of the photovoltaic power generation system and the energy storage system according to the target operation plan. According to the invention, the problem that the operation efficiency of the photovoltaic power generation system and the energy storage system is low because the operation state of the photovoltaic and energy storage system is adjusted based on a fixed operation strategy in the prior art is solved.

The invention relates to an optical storage and charging alternating current and direct current hybrid micro-grid construction control method and device and a medium. According to the method, level-to-level management is carried out on an energy storage converter according to an SOC value of an energy storage device. And the converter with the high priority is switched to a VSG mode, and whether the voltage and frequency fluctuation of the micro-grid exceeds an adjustment dead zone or not is detected. When the frequency fluctuation is exceeded, active power output is adjusted through a VSG mode; when the voltage fluctuation is exceeded, the reactive power output is adjusted. And the energy storage equipment is switched to the VSG mode step by step, and when the requirements cannot be met, the photovoltaic equipment and the electric automobile support power grid are put into use in sequence. Before the photovoltaic equipment is connected, the voltage of the photovoltaic equipment is synchronized to be consistent with that of the connected energy storage equipment, and the VSG mode is converted. And if further support is still needed, the electric vehicle is used for feeding by adjusting a charging pile control algorithm. And the voltage and the phase need to be synchronized before the electric vehicle is connected so as to cooperatively support the micro-grid. According to the method, the voltage and frequency stability of the micro-grid system is remarkably improved.

The invention relates to the technical field of power grid dispatching, and discloses an optical storage direct-current flexible micro-grid multi-target optimization dispatching system, which comprises a photovoltaic power generation module, an energy storage module, a direct-current power supply module, a flexible power supply module and a multi-target optimization dispatching module, and is characterized in that the multi-target optimization dispatching module comprises a monitoring unit used for monitoring each load unit in real time, acquiring basic power utilization information; the prediction unit is used for carrying out load prediction on the load unit at each moment every day according to the power utilization basic information; and the optimal scheduling unit is used for establishing a multi-target model by adopting a multi-target optimization algorithm and by taking the lowest daily operation cost and the maximum photovoltaic consumption rate of the optical storage direct-flexible micro-grid as targets, and solving the multi-target model based on a load prediction result to obtain an energy scheduling scheme of the optical storage direct-flexible micro-grid. According to the invention, the operation state of the micro-grid can be predicted and scheduled more accurately, so that an energy scheduling scheme with a better effect is obtained, and the energy utilization efficiency and the system operation stability are improved.

The invention provides an optical storage parallel network control method, which comprises the following steps: calculating the current load rate percentage of each residual unit according to the connection relation and electrical path information of the residual units after isolation; evaluating the available margin capacity and the frequency regulation bearing capacity of the remaining units, matching the available margin capacity and the frequency regulation bearing capacity with a specific power value and a frequency regulation requirement which need to be compensated, and determining a feasible unit combination scheme for fault recovery; generating a power redistribution list and a frequency adjustment responsibility distribution table according to the direct current bus connection mode of the optimal unit recombination, and obtaining an output power set value and a frequency adjustment parameter of each unit after adjustment; and extracting the continuous power supply time value of the optical storage parallel network, updating the total power supply capacity value of the optical storage parallel network, and maintaining the continuous power output and frequency stability after the fault of the optical storage parallel network.

The invention relates to a reliability evaluation method and system for a flexible AC / DC power distribution network containing an optical storage system in the field of flexible AC / DC power distribution networks. The method comprises the following steps: collecting photovoltaic data, energy storage data, AC / DC bus data and the like in real time; constructing a multi-time scale dynamic topology model, and establishing a failure probability distribution function; load flow calculation based on an improved forward-backward substitution method; adopting an N-1 + N-1-1 composite fault screening strategy to simulate a typical disturbance scene; establishing a vulnerability evaluation matrix to calculate power failure probability and other indexes; designing an optimal scheduling strategy based on model predictive control; multi-time-scale reliability evaluation is carried out; and outputting an evaluation report and a topology reconstruction suggestion. The system comprises a data acquisition unit, a dynamic modeling unit and the like, and an evaluation and analysis unit is internally provided with an algorithm module and is configured with an FPGA acceleration card. The method breaks through the limitation of traditional steady state evaluation in the technology level, improves the load flow calculation speed in the calculation efficiency level, reduces the operation cost in the application value level, improves the energy storage efficiency, and provides support for reliability evaluation of a novel power system.

The invention provides a photovoltaic output prediction method and a distributed optical storage transformer area active / reactive support capability optimization method, and belongs to the technical field of power system automation. Comprising the following steps: constructing a prediction model based on meteorological information, extracting multi-scale features of meteorological data, reducing dimensions through kernel principal component analysis, predicting photovoltaic power through a long-short-term memory network, quantifying the uncertainty of the photovoltaic power, and forming a prediction interval. Based on a photovoltaic power prediction result, a robust nonlinear programming model is established, the sum of absolute values of active / reactive power transmitted to a main power grid by a light storage area is maximized as a target, and linear and nonlinear constraints such as energy storage operation, power balance, equipment capacity and power factors are considered at the same time. The robustness under the photovoltaic output uncertainty is ensured through a budget uncertainty set; the model is solved by adopting a sequential quadratic programming algorithm. According to the method, the photovoltaic power prediction precision is effectively improved, and organic combination of high-precision prediction and robust nonlinear optimization is realized.

The invention provides an optical storage system intelligent scheduling and fault prediction method and device, equipment and a medium, and belongs to the technical field of intelligent optical storage, transportation and maintenance, and the method comprises the steps: collecting the data of an optical storage system in real time, and carrying out the preprocessing; inputting the preprocessed data into a multi-modal fusion model, and performing unified feature representation through a cross attention mechanism to obtain fusion features; inputting the fusion features into a prediction model for fault prediction and residual service life prediction; generating a state space formed by a fault type, a fault probability and a real-time electricity price according to a prediction result through a reinforcement learning algorithm, and setting a scheduling strategy which takes the charging and discharging power of the energy storage battery pack as an action space, and setting a reward function; and constructing an experience playback pool according to the actual operation data of the optical storage system, and regularly updating the strategy network of the reinforcement learning algorithm. According to the invention, the data is collected through the multi-mode sensor, the deep learning and reinforcement learning are combined, the intelligent fault prediction and dynamic scheduling of the optical storage system are realized, and the operation efficiency and reliability are improved.

The invention discloses a wind and light storage coordination control method and system for a virtual synchronous machine, and the method comprises the steps: building a wind power plant-energy storage power station double-layer response mechanism at a first stage, and employing a multi-time scale coordination control strategy for a second-stage energy storage system; and in combination with the virtual synchronous control characteristics of the optical storage power station, establishing a multi-scene optimization model of a wind and light storage multi-source collaborative double-layer coupling mechanism, and realizing dynamic optimization of output of each unit among inertia support, frequency modulation capacity and energy storage health state. According to the method, wind power plant rotor kinetic energy release combined overspeed load shedding control, a fuzzy control means based on an energy storage charge state and a VSG control means based on a virtual inertia and damping coefficient self-adaption photovoltaic system are considered, then wind and light energy storage frequency modulation coordination is optimized, and the system inertia safety is effectively improved on various working conditions and different time scales.

The invention discloses an optical storage layered collaborative optimization control method coupling photovoltaic priority absorption and time-of-use electricity price, and relates to the technical field of new energy power system optimization control. The method comprises the following steps: taking a photovoltaic generating capacity prediction value, a load electricity consumption prediction value and peak and valley electricity price information as input data; carrying out rolling optimization by utilizing a model prediction control framework, and generating a light storage plan table; and calculating a photovoltaic output regulation value and energy storage charging and discharging power based on the generated light storage plan table in combination with the photovoltaic power generation power and the load power consumption power which are acquired in real time, executing corresponding energy storage charging and discharging and photovoltaic output processing by applying a decision tree control mechanism, and optimizing light storage control according to a processing result. According to the method, the photovoltaic preferential consumption strategy is executed, the light abandoning amount is reduced, the photovoltaic consumption rate is improved, the time-of-use electricity price dynamic response mechanism and the energy storage efficiency compensation and light abandoning punishment mechanism are combined, peak-valley arbitrage is maximized, meanwhile, the comprehensive electricity utilization cost is reduced, and the power purchase demand of a power grid is reduced.

The invention provides a distributed robust optimization scheduling method for an optical storage charging and discharging integrated power station, and aims to solve the influence of multiple uncertain factors in an optical storage charging and discharging system on a power station scheduling decision and improve the robustness and real-time response capability of the system. According to the method, a distributed robust optimization framework is constructed, each node autonomously decides on the basis of boundary variables exchanged by local information and neighbor nodes, operation state changes are quickly responded through information interaction and cooperation, global cooperative scheduling is realized based on a distributed solving technology of a consistency algorithm, the calculation complexity is reduced, and the communication overhead is reduced. A multi-time scale model is introduced, the uncertainty of day-ahead scheduling is predicted based on a scene tree method, and a rolling optimization strategy is adopted for real-time scheduling. A charging pile intelligent scheduling strategy is formulated, bidirectional interaction with a power grid is realized, and the power grid stability and the resource utilization rate are improved. According to the invention, efficient, stable and economical operation of the optical storage charging and discharging integrated power station is realized, and the real-time scheduling requirement of a large-scale optical storage charging and discharging station is met.

The invention, which relates to the technical field of optical storage and charging, discloses an optical storage and charging cooperative control method for a transformer area, and the method comprises the steps: carrying out the intelligent and multivariate collection and prediction through intelligent equipment, constructing a function through collected data, solving an optimal solution, selecting an optimal optical storage and charging cooperative control strategy from the optimal solution, generating a corresponding control instruction, and carrying out the transmission of the corresponding control instruction. Cooperative regulation and control of a photovoltaic power generation system, an energy storage system and a charging pile system are achieved, a feedback and correction mechanism is further established, and it is ensured that the photovoltaic storage and charging system stably operates according to a preset strategy. According to the transformer area light storage and charging cooperative control method, a light storage and charging cooperative control mechanism is established by comprehensively considering photovoltaic power generation, an energy storage system and a charging pile system, power resource distribution in a transformer area is optimized, maximum consumption of photovoltaic power generation is achieved, the light abandoning phenomenon is reduced, meanwhile, unnecessary charging and discharging loss of the energy storage system is reduced, and the power utilization rate of the transformer area is improved. And the impact of disordered charging of the charging piles on a power grid system is relieved, so that the overall operation performance of a transformer area power system is improved.

The invention provides a light storage coordinated feed-in new energy microgrid power quality improving device and method, and relates to the technical field of microgrid distributed control. The light storage coordinated feed-in new energy microgrid power quality improving device comprises a series converter, a parallel converter, a battery energy management system and a direct current power supply unit. According to the optical storage coordinated feed-in new energy microgrid power quality improvement method, a prediction equation is established for a series converter to decouple a control target, and power grid current can be accurately compensated. An adaptive compensation control technique based on a VLLMS algorithm is employed for the parallel converter to generate a control signal for the parallel converter. A virtual inertia control strategy is provided for a battery energy management system, and inertia support is provided for a series converter and a parallel converter. And aiming at a non-ideal voltage condition, constructing a PB-SM compensation strategy of the new energy micro-grid power quality improving device based on optical storage coordinated feed-in.

The invention relates to an optical storage power station visual management method based on multi-energy data fusion, and the method is characterized in that the method comprises the following steps: S1, collecting multi-energy heterogeneous data of a multi-energy system; s2, the collected multi-energy heterogeneous data is preprocessed; s3, modeling by using a decomposition-based multi-objective evolutionary algorithm to generate a multi-objective dynamic optimization result; s4, dynamically adjusting and optimizing the target weight for switching of different scenes; s5, generating an action strategy of energy storage charging and discharging, power generation power output and power grid power interaction according to an optimization result; and S6, carrying out visualization processing on the multi-dimensional data and the optimization result. According to the invention, the operation intelligence level and the energy management efficiency of the optical storage power station are effectively improved.

The invention relates to the technical field of control, in particular to a method and a device for determining hyper-parameters of a convolutional neural network by using a Pedal algorithm and optimizing an optical storage net type inverter by using the convolutional neural network. Establishing an inverter parameter control model based on the convolutional neural network, optimizing hyper-parameters of the convolutional neural network through a Pedal algorithm, improving the feature learning capability of the model, obtaining inverter control parameters, taking the power grid impedance measured in real time as the input of the convolutional neural network model, taking the inverter control parameters as the output, and carrying out feature mapping on an input-output relation, thereby achieving the control of the inverter. And the control parameters of the inverter are adaptively updated according to the impedance change of the power grid, so that the optical storage grid type inverter always keeps stable output.

The invention discloses an optical storage charging station robust optimization method considering the travel behavior deviation of a charging user, and the method comprises the steps: depicting the path selection and charging behaviors of an electric vehicle user under different perception deviations through collecting the multi-dimensional data of a power network and a traffic network in real time, and employing a random user balanced mixed traffic flow distribution model; coupling the traffic and the power network through a traffic-power coupling network time-space correlation constraint; and establishing a two-stage robust optimization model of the optical storage charging station by integrating the photovoltaic output of the charging station and the behavior perception deviation multi-dimensional uncertainty of the travel user of the traffic network. An efficient solving algorithm is designed for a specific model, an optimal operation strategy of the power distribution network and photovoltaic charging station equipment in a worst scene is finally generated, dynamic optimal balance of operation economy and robustness of the power distribution network is achieved, the operation cost is reduced while the safety margin of the system is guaranteed, and the system reliability is improved. And the cooperative regulation and control capability of the complex coupling system is obviously improved.

The invention discloses an intelligent optical storage integrated AC / DC control method based on an energy management and control algorithm. The method comprises the following steps: acquiring and monitoring first data in real time; the working state of the photovoltaic module is dynamically adjusted through a maximum power point tracking algorithm, so that the photovoltaic module can output maximum power under various environmental conditions; according to the first data monitored in real time, the electric energy of photovoltaic power generation is dynamically distributed; acquiring a power grid fault state, switching an operation mode according to the power grid fault state, and controlling electric energy balance in the system; deploying an intelligent sensing system, collecting system operation state parameters in real time, and adjusting an energy management and power control strategy based on real-time data to enable the energy management and power control strategy to adapt to environment and load changes; monitoring faults and abnormal states, identifying fault types and positions, and intervening to recover normal operation of the system. The technical method for realizing optimal management and seamless operation switching of energy has the advantages of high system stability, high energy utilization efficiency and timely fault processing.

The invention provides a coordinated control method and device for flexible interaction of an optical storage and charging micro-grid and a power distribution network, and belongs to the technical field of intelligent power grids and distributed energy management. According to the method, through a day-ahead, intra-day and real-time three-layer coordination control architecture, the system operation cost is optimized, and the power grid stability is improved. The day-ahead layer generates a 24-hour scheduling plan based on photovoltaic output prediction, electric vehicle charging requirements and time-of-use electricity price; the intra-day layer performs rolling optimization in combination with real-time photovoltaic / load fluctuation, and dynamically allocates V2G and energy storage adjustment tasks; the real-time layer adopts adaptive droop control, monitors power grid abnormity and triggers cross-layer cooperation, and also sets photovoltaic fluctuation compensation and island mode switching conditions. Collaborative optimization is realized among the layers through bidirectional data channels. According to the method, the defect of interactive control of the optical storage and charging micro-grid and the power distribution network in the prior art is overcome, the adaptability of the system to distributed energy fluctuation is enhanced, the V2G resource potential is fully played, and the coping capacity under the abnormal condition of the power grid is improved.

The invention relates to the technical field of optical storage direct-flexible scheduling, and discloses a method for establishing an energy storage scheduling model of a multi-node optical storage direct-flexible system. The method comprises the following steps: acquiring real-time operation data of each node of a system, including a photovoltaic output fluctuation curve, an energy storage charge state, a load demand time sequence, a power grid interaction power limit value and an environmental irradiance change characteristic, and performing multi-dimensional alignment processing on the real-time operation data to form a multi-dimensional operation data set; performing operation state mapping topology construction processing on the data set, and separating out target operation data and state indication data; based on the target operation data, in combination with scheduling priority configuration information of each node, generating a multi-node collaborative energy storage scheduling initial model containing an energy storage charging and discharging time sequence strategy and a power distribution scheme; and identifying node operation abnormal characteristics based on the state indication data, dynamically reconstructing the initial model according to the node operation abnormal characteristics, and outputting the updated energy storage scheduling model to guarantee stable and efficient operation of the system.