1157 results about "Grid system" patented technology

The invention provides a micro-grid cooperative scheduling method and device, and relates to the technical field of smart grids, and the method comprises the steps: obtaining historical operation data and real-time operation data of a micro-grid system, and data of an external information system; generating load demand and energy equipment output prediction information based on the historical operation data and the data of the external information system; constructing a layered multi-time-scale decision architecture, and performing decision optimization on each layer of agents by adopting a reinforcement learning algorithm; constructing a plurality of heterogeneous agents, and carrying out cooperative scheduling on the plurality of heterogeneous agents by adopting a centralized training and distributed execution multi-agent reinforcement learning algorithm; inputting the prediction information and the real-time operation data into a decision framework, and outputting a real-time control instruction; and setting a security constraint condition, and realizing optimization of the security constraint in combination with a Lyapunov function, a Lagrange multiplier method, a security layer mechanism and a reinforcement learning algorithm. According to the method provided by the invention, the safe, efficient and reliable operation of the micro-grid in the grid-connected / off-grid mode can be realized.

An energy storage control method and apparatus for a micro-grid system and a micro-grid system are provided. The method includes: for a target period within a first operation period, based on first predicted operation parameters of the micro-grid system in the target period, obtaining, via a first control model, a first control parameter of the energy storage unit in the target period; and for a target period within a second operation period, based on first historical state parameters of the micro-grid system before the target period, obtaining, via a second control model, a second control parameter of the energy storage unit in the target period. In this way, the energy storage regulation of the entire life cycle of the micro-grid system can be realized, effectively reducing the user electricity cost.

The invention relates to the technical field of power electronics, in particular to a photovoltaic off-grid inverter control method and system, and the method comprises the following steps: applying a test signal to identify an output interaction characteristic parameter, predicting the power generation power through combining with weather and attenuation, calculating the power fluctuation, and adjusting a current control parameter set. And calculating voltage and reactive power compensation parameters to generate an inverter control instruction, and combining a temperature load prediction trend to adjust a power allowable value to obtain a predictive power calibration coefficient. According to the invention, by analyzing the output interaction characteristics, enhancing the perception capability of the inverter to the actual operation environment, combining with the prediction of the photovoltaic power generation amount, realizing the prediction and influence evaluation of the power fluctuation, improving the adaptive adjustment capability of the current control parameters, improving the output voltage and reactive power control precision by utilizing the interaction characteristics, and optimizing the electric energy quality; and through thermal management of multi-point temperature and load prediction, the operation safety is improved, the service life of equipment is prolonged, and the operation performance of the photovoltaic off-grid system in a complex environment is improved.

The invention discloses a rotor craft flow field numerical simulation method and device, a medium and a product, and relates to the technical field of aircraft flow field data processing, and the method comprises the steps: building a rotor craft model based on a rotor craft under a given flight condition; generating a hybrid grid system based on the rotorcraft model; according to the hybrid grid system, performing flow field CFD numerical simulation on the rotorcraft to obtain conservation variable information of a blade area; according to the conservation variable information of the blade area, an AASM method is adopted to calculate and obtain an unsteady momentum source item of the blade area; and according to the unsteady momentum source item of the blade area, rotor aerodynamic characteristic data and flow field data under the given flight working condition are determined. By coupling the AASM method and the CFD simulation, the precision and efficiency of calculating the aerodynamic characteristic data and the flow field data of the rotor wing can be improved, and the requirements of carrying out complex full-aircraft interference with great resource consumption and maneuvering flight state research are met.

The invention provides a micro-grid dispatching method based on a hybrid genetic particle swarm optimization algorithm. The method comprises the following steps: constructing a micro-grid system comprising a photovoltaic cell PV, a fan WT, a diesel generator DE and a micro gas turbine MT; based on the micro-grid system, a multi-objective optimized micro-grid optimization scheduling model is constructed, an objective function of the optimization scheduling model is set to be cost for minimizing the micro-grid in a grid-connected mode, and the cost comprises operation cost and environment cost; and solving the optimal scheduling model of the micro-grid by adopting a hybrid genetic particle swarm optimization algorithm MOPSO, and outputting an optimization result meeting a scheduling strategy. According to the method, the operation cost is optimized, the microgrid dispatching strategy with the optimal economical efficiency can be formulated by accurately predicting the future load and the new energy output and fully utilizing adjustable and controllable means such as energy storage and the hybrid genetic particle swarm optimization algorithm, and the operation cost is reduced.

The invention provides a day-ahead optimization scheduling method and system for a wind-light-hydrogen storage off-grid operation system. The method comprises the following steps: establishing an off-grid planning outer-layer capacity optimization configuration model by taking the total cost of the wind-light-hydrogen storage off-grid system as a first objective function; in the off-grid operation state of the wind-solar-hydrogen storage coupled system, taking the off-grid operation cost of the wind-solar-hydrogen storage coupled system as a second objective function to establish an off-grid operation inner-layer optimization scheduling model; solving the off-network planning outer-layer capacity optimal configuration model through improved particle swarm optimization iterative optimization to obtain economically optimal hybrid energy storage capacity configuration; and determining the optimal load scheduling amount through the off-grid operation inner-layer optimization scheduling model and the off-grid planning outer-layer capacity optimization configuration model. The unreasonable charging and discharging time sequence of the hybrid energy storage system can be optimized, the cost influence on optimal configuration and operation of the wind-light-hydrogen storage off-grid system can be avoided, and the economical efficiency of the wind-light-hydrogen storage off-grid system is improved.

A generalized approach and methodology for addressing surface traversal and coverage of a 3 Dimensional (3-D) object receives a 3-D wireframe or similar Cartesian based representation, converts the 3-D representation to a u,v system or mapping. Often employed for texture mapping, u.v grid systems define a two dimensional form of an object, often referred to as “unfolding” of an object. Configurations herein define a u.v grid system directly on the 3-D object for computing a coverage path, typically an aggregation of raster passes to traverse an entire 3-D surface. From a robotic manipulator, a 3D freeform surface, and task constraints, the approach determines whether there exists a feasible continuous motion plan to cover the surface, and if so, produces a uniform coverage path that best satisfies task constraints resulting from the physical object and robot kinematics.

The embodiment of the invention provides a low-altitude digital management method and device based on an urban space-time grid, and the method and device achieve the precise division of an airspace through a plurality of layers of grid units by creatively building a unified urban space-time reference grid system. And designing a space-time grid data assignment model, processing multi-source heterogeneous data by using a deep neural network and a space-time convolutional layer, and realizing intelligent mapping of grid features through an attention mechanism. And constructing an airspace situation awareness model based on a graph neural network, and capturing a space-time dependency relationship among grid units in combination with a message passing mechanism to realize accurate prediction and hierarchical management and control of an airspace state. According to the method, the defects of the traditional technology in the aspects of airspace division, data processing, situation awareness and the like are effectively overcome, and the accuracy and practicability of urban low-altitude digital management are remarkably improved.

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 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 discloses a micro-grid system planning and design method and device based on double-layer optimization, and relates to the field of micro-grid system planning and design, and the method comprises the following steps: S1, collecting the operation data of wind power, photovoltaic, hydropower, an energy storage power station, an electrolytic cell and a hydrogen storage tank in a micro-grid system, and the load data of the micro-grid system; s2, constructing a micro-grid system double-layer optimization model based on a double-layer optimization method; the upper-layer model is a capacity optimization layer, and the maximum total income within the operating age limit is used as a target function; the lower-layer model is a scheduling optimization layer, the maximum operation net income in a scheduling period is taken as an objective function, and system power balance, equipment operation and capacity are taken as constraint conditions; and S3, solving the double-layer optimization model by using an improved grey wolf algorithm and a solver. The microgrid system is planned and designed through a double-layer optimization method, a clean energy power generation and energy storage device capacity configuration scheme is reasonably configured, and an energy scheduling strategy is optimized.

The invention relates to the technical field of micro-grid energy optimization, in particular to a distributed federal reinforcement learning-based hydrogen-containing micro-grid energy scheduling method, which comprises the steps of constructing a multi-region hydrogen-containing micro-grid system model, designing a state space, an action space and a reward function of an intelligent agent, constructing an Actor-Critic network and an experience pool, and completing environment initialization. The intelligent agent inputs the operation state of the equipment into the Actor network, updates the state of the equipment according to the output action, verifies the constraint and outputs a reward value; tuples are extracted from the experience pool to update local network parameters, and the exploration rate is updated regularly; when a federation interaction period is reached, exchanging Critic network parameters and updating federation parameters; and when the training round arrives, outputting an equipment operation plan, deploying the model to the local hydrogen-containing micro-grid in the island mode, and outputting an equipment output value. According to the scheme, strategy sharing and learning collaboration are realized through neighborhood collaboration and local communication among the regional intelligent agents, so that dependence on a central node is avoided.

The invention relates to the field of clean energy, and provides a distributed secondary control method for an island micro-grid system based on event triggering, which comprises the following steps: S1, connecting adjacent distributed units in an island micro-grid through a local communication link, and constructing a distributed control architecture to eliminate dependence on a central controller; s2, triggering communication of the local communication link based on a preset threshold value, and transmitting a secondary control signal when the system state deviation exceeds the threshold value; s3, performing cooperative calculation on the secondary control signal by using the distributed control architecture, adjusting frequency and voltage deviation, and shielding original power data; and S4, connecting a newly added distributed unit to the distributed control architecture through the local communication link, thereby reducing high communication burden and single-point fault of centralized control of the island microgrid.

The invention relates to the technical field of micro-grid capacity configuration, in particular to a micro-grid capacity configuration optimization method and system. According to the method, a total cost objective function is constructed by taking the minimization of the total cost of all main bodies in the wind-solar storage micro-grid as a target, a wind-abandoning and light-abandoning objective function is constructed by taking the minimization of the penalty cost of wind-abandoning and light-abandoning as a target, and an ACG wind-solar frequency modulation objective function is constructed by taking the maximization of ACG wind-solar frequency modulation benefits as a target. Setting a power balance constraint and a wind curtailment and light curtailment constraint as constraint conditions, and establishing a micro-grid capacity non-cooperative game model; and based on the micro-grid capacity non-cooperative game model and the constraint conditions thereof, solving the micro-grid capacity non-cooperative game model by adopting an improved particle swarm algorithm to obtain a capacity target configuration result. According to the method, the power output of each main body is optimized by considering the wind curtailment and light curtailment factors, the Nash equilibrium of the system is achieved, the system income is maximized, and the overall performance and economical efficiency of the micro-grid system are effectively improved.

The invention discloses a multi-microgrid system distributed optimization scheduling method based on an electric power-carbon market, and the method comprises the steps: constructing an energy consumption equipment model and a carbon quota transaction model based on the energy flow and carbon quota transaction process in a microgrid; a dynamic collaborative pricing model is constructed based on the power and carbon quota market supply-demand relationship; constructing an operation cost optimization model of a single micro-grid system based on the above models, and constructing a multi-micro-grid collaborative optimization scheduling problem with the goal of minimizing the total operation cost of all micro-grids based on a Nash bargaining game framework; and solving by adopting an accelerated prediction-correction alternating direction multiplier method algorithm to obtain an optimal scheduling scheme based on power-carbon market coupling, thereby realizing energy operation scheduling of the multi-microgrid. Through power-carbon market coupling, dynamic pricing, game theory optimization and an efficient distributed algorithm, the operation cost of the micro-grid system is reduced, and the reduction of the operation cost assists in improving the operation income of the micro-grid system.

The invention provides a resource decoupling-oriented service grid test oracle method and device, and the method comprises the steps: determining first communication paths from an input port to an output port in a target service grid system, generating first test service requests corresponding to the first communication paths, and enabling the first test service requests to be connected with the output port of the target service grid system; inputting the target service grid system from the input ports corresponding to the first test service requests to obtain first test service results output by the target service grid system, and sending the first test service results to the target service grid system under the condition that the first test service results are matched with service reference results corresponding to the first communication paths. According to the method, the target service grid system is determined to pass the test, a more comprehensive test process can be executed on the target service grid system, the problem that the test process is not comprehensive due to the difference of the service grid system is avoided, and the accuracy of the test result of the service grid system is improved to a certain extent.

The invention relates to an artificial precipitation enhancement operation area identification method and system based on multi-source data, and relates to the technical field of meteorological intervention operation, and the method comprises the steps: building a multi-resolution dynamic data grid system, and enabling a coarse-grained grid layer to cover the whole operation area, and to be used for bearing the macro data of a satellite cloud picture and a conventional radar; the fineness grid layer is used for receiving and mapping real-time data provided by the high-resolution radar; receiving real-time data of all cloud blocks, mapping the real-time data to corresponding grid layers, and projecting the data collected at different time points to a unified time reference frame to obtain a cloud system state view; predictive interpolation is carried out by using the latest data of the conventional radar and the macroscopic trend of the satellite cloud picture in combination with the motion vector and confidence weighting so as to obtain cloud system information; and forming a visual cloud system three-dimensional view, identifying and tracking a target cloud block with an artificial precipitation enhancement potential, and generating an operation instruction. The method has the effect that the target cloud block with the operation value can be identified and tracked to generate the accurate operation instruction.

The invention discloses an island micro-grid reliability evaluation method and device considering a hybrid energy storage system, and the method comprises the steps: obtaining the operation parameters of an island micro-grid energy storage system, considering the uncertainty of load output, and the charge and discharge and capacity constraints of the energy storage system, building a load output model and an energy storage charge and discharge model, state parameters of the hybrid energy storage system are obtained, a multi-state model of the hybrid energy storage system is established, the state probability is solved, and a reliability index of the hybrid energy storage system is obtained; establishing a minimum load reduction strategy model on the basis of considering the load importance; and according to the hybrid energy storage system multi-state model, the energy storage charging and discharging model, the load output model and the minimum load reduction strategy model, constructing an island photovoltaic micro-grid reliability evaluation program containing the hybrid energy storage system, and outputting a reliability index of the hybrid energy storage system. And reliability evaluation can be carried out on the island photovoltaic micro-grid system containing the wind and light storage.

The invention discloses an independent micro-grid energy storage optimization method considering lithium ore load regulation potential improvement, and the method comprises the steps: S1, considering the lithium ore load regulation potential and a micro-grid operation scene, and constructing a lithium ore load and energy storage coordination optimization model; s2, outputting a result of the lithium ore load and energy storage coordinated optimization model by taking the optimal operation cost benefit of the micro-grid as a target function; and S3, according to an output result of the lithium ore load and energy storage coordinated optimization model, completing independent micro-grid energy storage optimization, the lithium ore load regulation potential is excavated, the bidirectional flexible interaction capability with the micro-grid is improved, the micro-grid system operation cost is reduced, and the new energy consumption capability and the lithium ore load power supply reliability are improved in the technical aspect.

In a cooperative autonomous distributed grid interconnection system, each of the cooperative autonomous distributed devices receives frequency information and phase information transmitted from the grid interconnection controller based on a standard time signal, or a combined signal of the frequency information and the phase information. When the synchronization checking circuit breaker is open, each or the cooperative autonomous distributed devices controls a voltage phase of the cell grid system so that the voltage phase of the cell grid system is synchronized with that of the main grid. When the synchronization checking circuit breaker is closed, each of the cooperative autonomous distributed devices controls a power flow between the main grid and the cell grid system.

The invention relates to the technical field of electric energy storage, in particular to an electric energy conversion device of a photovoltaic energy storage micro-grid system, which comprises a protection bin, one side of the protection bin is provided with an openable front cover, the middle part of the protection bin is recessed inwards to form a placement cavity, and a plurality of batteries are arranged in the placement cavity. A liquid storage tank is further arranged in the containing cavity, a water pump for sucking cooling liquid is arranged below the liquid storage tank, a heat conduction pipe is arranged at the output end of the water pump, a plurality of cooling devices are arranged outside the batteries, and a moving device for driving the batteries to move is arranged between the batteries and the containing cavity. Through cooperation of structures such as a first cooling plate, a second cooling plate, a first surrounding pipe, a second surrounding pipe and a conveying pipe, cooling liquid is conveyed into the cooling box through the conveying pipe, the cooling liquid is contained and cooled in the cooling box, the cooling liquid is rapidly cooled, the water cooling effect is improved, and the continuous cooling effect on a battery is improved.

The invention provides an indoor navigation and path planning method, device and equipment. Comprising the steps that path planning request parameters are acquired, and the request parameters at least comprise a starting point, an ending point, a time context, a user portrait and a scene template of path planning; generating a runtime snapshot reflecting the traffic state at the current moment in combination with a pre-constructed static grid system, a knowledge graph and a dynamic grid system generated in real time; according to an indoor structure mask and guide identification information in the static grid system, generating a search domain limit of path planning on the runtime snapshot; judging whether the starting point and the ending point are on the same floor; performing path search by adopting a same-layer search strategy or a cross-layer search strategy; and dynamically injecting constraints to the result of the path search and calculating the path cost to generate a path plan. According to the embodiment of the invention, the indoor space can be uniformly expressed, the multi-source dynamic information can be fused in real time, and the path planning scheme can be quickly generated, so that the navigation requirement in a modern complex indoor scene can be met.

The invention discloses a micro-grid system based on a direct current bus and a control method, the micro-grid system comprises the direct current bus, an energy management unit and a plurality of power conversion modules, when the micro-grid system is in an independent adjusting mode, each power conversion module controls the direct current bus to operate according to bus operation parameters of the direct current bus; and when the micro-grid system is in a centralized regulation mode, the energy management unit issues a control instruction to coordinate the output power and / or the input power of each power conversion module. According to the technical scheme, a unified direct current bus framework is constructed, the photovoltaic energy unit, the energy storage energy unit, the commercial power energy unit, the direct current load and other loads are directly connected to the direct current bus, direct current direct supply and direct current direct charging are achieved, the energy link structure is simplified, the power conversion link is reduced, the overall energy efficiency of the system is improved, and the system cost is reduced. And the phenomena of multiple energy conversion and energy loss caused by dependence on an alternating current bus in the prior art are avoided.

The invention discloses a high-order direct-current micro-grid system multi-loss synchronous convergence modeling method based on an improved physical information neural network. The method comprises the steps that S1, a physical information neural network model is initialized; s2, calculating physical loss and updating parameters of the physical information neural network model; s3, reflecting parameters of the physical information neural network model around physical optimization result points; s4, calculating data loss by using the reflected parameters and updating parameters of the physical information neural network model; s5, using the parameters obtained in S2 and S4 to update the parameters of the physical information neural network model through the iterative operation of Douglas-Rachford splitting; and S6, iterating the parameter updating process to solve the physical information neural network model. Different from a traditional physical information neural network which is difficult to converge for high-order system training, the method can realize synchronous convergence of physical loss and data loss in high-order direct-current micro-grid system fitting, and has important significance for mastering an internal operation rule of a direct-current micro-grid system in real time and establishing a physically interpretable data driving model.

The invention relates to the technical field of data transmission, in particular to a high-reliability intelligent micro-grid system data transmission method, which comprises the following steps: acquiring load data of a target node for an intelligent micro-grid system in a current time period and a historical time period; carrying out clustering division on the load data in the current time period, and carrying out adaptive combination on all current load clusters; determining a data change frequency degree corresponding to each current load sub-segment; screening a similar load sub-segment corresponding to each current load sub-segment; determining a state influence factor corresponding to each current load sub-segment; screening out a historical load sequence which is the same as the corresponding stage of each current load sub-segment, and obtaining a state influence factor corresponding to the historical load sequence; and transmitting the working condition information collected in the current time period according to the determined target transmission level. Data transmission is carried out based on the quantized transmission level, and the reasonability of data transmission is improved.

Systems, apparatuses, and methods for a modular resistor grid system include a mount and a plurality of modular resistor grid assemblies that interchangeably couple to the mount. At least two modular resistor grid assemblies are in the plurality. Each has a housing and a plurality of resistor plates. Each housing has input and output terminals. Each plurality of resistor plates is connected between the input and the output terminal of a housing. Each resistor plate has a thickness, and each plurality of resistor plates provides a target electrical resistance for a modular resistor grid assembly. A first modular resistor grid assembly has a first number of resistor plates with a first thickness. A second modular resistor grid assembly has a second number of resistor plates with a second thickness. The first number of resistor plates is greater than the second number. The first thickness is greater than the second thickness.

The invention discloses a multi-objective optimization scheduling method and system for an electricity-hydrogen collaborative micro-grid, and the equipment unit in the electricity-hydrogen collaborative micro-grid comprises a photovoltaic output unit, a fan output unit, a battery energy storage unit, a diesel generator unit, a hydrogen energy storage unit, and a flexible load demand side management unit. The method comprises the following steps: constructing a multi-target optimization scheduling model of the power-hydrogen collaborative micro-grid based on an operation model of an equipment unit in the power-hydrogen collaborative micro-grid; and solving the established multi-target optimization scheduling model of the electricity-hydrogen collaborative micro-grid to obtain an optimization scheduling scheme. According to the method, an emerging hydrogen energy technology is incorporated into a micro-grid system, a hydrogen energy storage unit in the micro-grid is incorporated into an optimal scheduling scheme, a hydrogen power generation and electric hydrogen production system is integrated with traditional battery energy storage and renewable energy sources, and the diversity and flexibility of micro-grid scheduling are improved.

The invention discloses a diesel-storage intelligent micro-grid system. A diesel generator charges an energy storage unit or cooperatively supplies power when power supply is insufficient; the battery energy storage unit stores electric energy and supplies power to a load; the micro-grid energy management system dynamically coordinates the output proportion, and a harmonic suppression module suppresses harmonic interference; the load prediction module predicts load power change; the transient response control module deals with transient power impact; the power distribution system is connected to a main power supply and is switched to a diesel generator power supply mode when power supply of the main power supply does not meet requirements; when the diesel generator supplies power, the bidirectional converter converts electric energy into charging current of the energy storage unit and inhibits harmonic interference; when the energy storage unit supplies power, the direct current is converted into the alternating current required by the load. According to the invention, seamless switching of multiple energy sources, active stabilization of power fluctuation, flexible conversion of electric energy forms, optimization of energy distribution efficiency and comprehensive improvement of the survivability of the micro-grid can be realized.

The invention discloses a heterogeneous graph neural network-based microgrid cooperative scheduling prediction and security check method. The method comprises the steps of constructing a heterogeneous graph model; different micro-grid operation scene graphs are generated through analogue simulation; solving an optimal collaborative scheduling strategy vector for each scene graph to serve as an optimal scheduling label, generating a training data set of a'scene graph-optimal scheduling label 'data pair, and completing offline training of the graph neural network model; dynamically generating an instantiated heterogeneous graph; taking the instantiated heterogeneous graph as the input of the trained graph neural network model, carrying out first forward reasoning, and outputting a predicted collaborative scheduling strategy vector; and injecting a virtual fault, generating a virtual fault heterogeneous graph, inputting the virtual fault heterogeneous graph and the predicted cooperative scheduling strategy vector into the trained graph neural network model, carrying out second forward reasoning, predicting the state of the faulty micro-grid system, obtaining the predicted fault node voltage, and carrying out safety check on the predicted cooperative scheduling strategy vector.

The invention provides a micro-grid peak clipping and energy storage optimization method and optimization system, and belongs to the technical field of micro-grids, and the method comprises the steps: analyzing the project general situation, predicting the energy consumption data of a charging field, building a photovoltaic system peak clipping model, calculating the peak operation power of each time period, determining the total energy storage reduction power, and carrying out the peak clipping according to the peak clipping demand, the charging and discharging depth, the battery efficiency and the PCS efficiency. Calculating the required capacity of an energy storage battery, selecting a proper energy storage device, carrying out peak clipping, releasing energy in a residual electricity peak electricity price period, formulating an operation strategy, and realizing dynamic peak clipping; power supply and power utilization loads in the micro-grid system are always in a balanced state, and the problem that the service life of a transformer is affected due to voltage fluctuation, current overload and the like is avoided.