31 results about "Grid operator" patented technology

Provided is a method of operating a hybrid power plant, including energy generating units including a wind park and at least one unit of another type of renewable energy source and including an energy storage system, the method including: creating a power production schedule based on an actual forecast of power production, an actual forecast of energy price and actual hybrid power plant status, the power production schedule including at least scheduled power for points in time in the future; and controlling, during the points in time in the future the energy generating units and the energy storage system based on the power production schedule, the hybrid power plant status at the points in time in the future, in particular energy storage system status, such as to dispatch power according to the power production schedule, but complying with any grid operator reference at the points in time in the future.

According to the intelligent compatible and efficient charging control system and the application method thereof, a management system combined with a cloud platform is provided, and a more intelligent, convenient and reliable charging control system is provided for a user by integrating the latest information technology, automation technology and artificial intelligence technology. Charging strategies suitable for various vehicle types are dynamically generated through the cloud strategy management platform, the edge computing node executes a lightweight charging control model, the multi-mode sensing module collects battery state data in real time, and the federal learning framework is connected with vehicle enterprises, power grid operators and charging facility data. The system solves the problems of poor compatibility and insufficient data collaboration of a traditional charging system, improves the charging efficiency, guarantees the safety of a battery, achieves the personalized adjustment of a charging strategy, and will show huge market potential and social value in the future along with the rapid growth of the intelligent equipment and electric vehicle market.

The invention relates to a port micro-grid energy control strategy considering incomplete information, and the strategy is technically characterized in that the time-of-use electricity price of a power grid, the parameters of a micro-grid operator and the like are set, and a data source is determined; scene sampling is carried out, and uncertain information in micro-grid operation is converted into a computable deterministic scene; establishing a Bayesian-Stackelberg game model under incomplete information by taking a power transaction agent as a main body and a micro-grid operator as a slave body; a follower model constraint is established by considering port berth distribution, and a KKT condition is established for a follower model so that the double-layer game model can be converted into a single-layer optimization model; and solving the model by using a CPLEX solver to obtain an optimal electricity price and an energy control strategy of each scene. According to the method, the uncertainty of port micro-grid information is considered, port operation constraints, berth distribution strategies and the like are comprehensively considered, the economy of micro-grid operation is considered while the port logistics transportation efficiency is ensured, and a port micro-grid energy control strategy considering incomplete information is provided.

The application discloses a multi-time scale hierarchical scheduling method for a combined heat and power system containing electric vehicles, and the system comprises a micro gas turbine unit, an absorption refrigeration unit, a ground source heat pump unit, a wind turbine unit, photovoltaic, a battery, a super capacitor and a heat storage device. The optimization method contains two time scales. In the day-ahead stage, economic scheduling is carried out according to the day-ahead predicted power value of wind power and photovoltaic and the day-ahead predicted value of load power in the system, and a target function and optimization constraint condition are established, and the result is used as a reference for the day-ahead optimization. In the day-ahead stage, a two-layer rolling optimization model is considered, a target function and a constraint are established, and a model predictive control (MPC) rolling optimization layer corrects the result of the upper layer according to real-time predicted power information and non-planned behavior of the electric vehicle (EV). The application adopts a multi-time scale hierarchical optimization strategy, real-time tracks the optimal scheduling strategy of the combined heat and power system containing electric vehicles, and realizes a win-win situation between the electric vehicle owner and the micro-grid operator.

Computer implemented systems and methods for providing an uncertainty platform for an energy grid controller that (1) receives risk inputs including (a) one or more load forecasts, (b) one or more wind forecasts, (c) one or more solar forecasts, (d) one or more generator availability risk forecasts, (e) one or more generator fail-to-start or fail-to-run predictions, (f) one or more net scheduled interchange forecasts, and / or (g) one or more transmission congestion forecasts; (2) determines net uncertainty for a predetermined time period based on the risk inputs; and (3) provides dynamic risk outputs including forecast scenarios, reserve requirements and / or reserve margin thresholds based on the determination of net uncertainty.

Systems, methods and apparatus for power management in an electric power grid are disclosed. A power flow to a plurality of power consuming devices in the electric power grid is enabled and disabled by a plurality of controllable devices under the control of one or more client devices. An apparatus receives a power control command and select at least one client device to which to issue a power reduction message. The power reduction message comprises an amount of electric power to be reduced to at least one of the plurality of power consuming devices for a predetermined time. A database stores information relating to power consumed by the plurality of power consuming devices based on measurement and verification.

The invention relates to the technical field of photovoltaic voltage regulation, in particular to a photovoltaic energy storage cluster collaborative voltage regulation method and device based on adaptive gaming, and the device comprises a voltage out-of-limit judgment unit which judges whether the node voltage of a power distribution network is out-of-limit or not; the voltage response unit responds and judges whether the energy storage SOC of the power distribution network is sufficient or not; the voltage regulation unit responds to the adaptive game voltage regulation strategy and outputs the regulated node voltage of the power distribution network; the voltage recovery judgment unit is used for judging whether the adjusted node voltage of the power distribution network is recovered or not; a result output unit; according to the method, a'master-slave + evolution + cooperation 'three-layer fusion game framework is constructed, a power grid operator sets excitation signals, photovoltaic energy storage units serve as a group, dynamic response excitation is achieved through evolutionary game, respective output is optimized in a collaborative mode, and finally the equilibrium state of voltage qualification and the lowest cost is taken into consideration. The adaptive game optimization can adjust the strategy in real time in different operation scenes, and has good robustness and adaptability.

The invention relates to the technical field of smart power grids and information security, in particular to a PUF (Physical Unclonable Function)-based certificateless proxy signature smart power grid distributed energy transaction method, which comprises the following steps of: constructing a PUF-based certificateless proxy signature smart power grid distributed energy transaction system, transaction is carried out based on the certificateless proxy signature smart power grid distributed energy transaction system; the system comprises a power grid operator, an energy manufacturer, an agent, PUF equipment and a block chain, the transaction process comprises an initialization stage, an identity authentication stage and a transaction stage; according to the method, the unique key of the equipment is generated through the PUF, the problems of complex certificate management and key escrow are avoided by adopting a certificateless mechanism, decentralized evidence storage and non-tampering of transaction data are ensured based on the block chain, the problems of insufficient security, low efficiency and weak anti-attack ability of a traditional scheme can be effectively solved, and the method is adaptive to the resource-limited Internet of Things equipment and has the advantages of high security and high reliability. And efficient and credible safety guarantee is provided for distributed energy transaction of the smart power grid.

This application provides an integrated planning method and related equipment for smart distribution network infrastructure. The method includes: constructing a co-construction and sharing actor network by treating network operators, grid operators, decision-makers, and power infrastructure as actors; constructing a co-construction and sharing initiative model based on the decision-makers' decisions, and implementing the co-construction and sharing initiative model based on the co-construction and sharing actor network; dividing the smart distribution network and implementing coordinated planning strategies for the power supply layer and power supply zones respectively; and constructing an optimization configuration strategy based on the analysis of resources and information in the smart distribution network to optimize the infrastructure in the smart distribution network. It is evident that this method, based on the co-construction and sharing initiative model of power infrastructure, solves the initiative problem under co-construction and sharing tasks in different scenarios, avoids ignoring the initiative of actors, and reflects the interactive relationship between the communication network and the smart distribution network infrastructure. It is applicable to complex smart distribution network business scenarios.

A system for automating matching of energy load with energy generation for energy consumers, utilities, and gird operators, comprising a processor and a memory containing instructions configuring the processor to collect, from a grid network connecting load centers and generation sources, energy datasets including energy attribute records and energy load data, match each load center to the generation sources based on the energy datasets, matching further comprises generating actionable energy models, each one of the actionable energy models representing a configurable allocation of the energy attribute records, based on the energy datasets, and matching the load centers and generation sources as a function of at least one actionable energy model, populate an allocation report for each load center, and transmit the allocation report to an external device in communication with the processor.

The embodiment of the invention discloses a layered and distributed optimal scheduling method for a micro-grid system considering psychological factors of a user. On the basis of considering benefit demands of a micro-grid operator and users participating in demand response, a micro-grid double-layer scheduling model based on a master-slave game is constructed, a user side load model serving as a follower model depicts the influence of psychological factors of the users on the demand response, and a user side load model serving as a follower model depicts the influence of the psychological factors of the users on the demand response. The micro-grid operator model as the leader model optimizes the operation of each device and formulates the excitation price of the demand response, so as to achieve the balance of supply and demand and pursue the maximization of benefits. And layered and distributed optimization solution is performed on the microgrid double-layer scheduling model by adopting an alternating direction multiplier method, so that user side participation demand response can be effectively mined, and resources such as wind power, light and the like in the microgrid system can be fully absorbed. Therefore, on the basis of pursuing optimal operation economy of the micro-grid system and giving consideration to the benefits of the user side, multi-party benefit balance in the micro-grid system is realized.

The invention relates to a computer-implemented method and system for optimizing a baseline when electrical power is drawn by devices of a subscriber connected to a grid connection point on a power supply network operated by a network operator, comprising the steps of: receiving an announcement message from the network operator by an energy management system of the subscriber regarding an upcoming load management event, which indicates the extent to which an electrical load by devices of the subscriber is to be reduced or increased during the load management event in a load adjustment;Determining an optimal baseline for the electrical power consumption of a subscriber's devices in a time interval prior to the announced load management event, such that the load adjustment requested in the notification is optimally balanced in advance with respect to a predefined optimization criterion, taking into account specified constraints; controlling the subscriber's devices by the subscriber's energy management system to achieve the determined optimal baseline during the time interval prior to the announced load management event; and adjusting the electrical load at the subscriber's grid connection point by the subscriber's energy management system according to the information in the notification received from the grid operator regarding the required load adjustment by controlling the subscriber's devices.

A communication system (10) according to the invention for improving the grid stability of electricity grid operators (12) comprises at least one electricity grid operator (12), at least one motor vehicle charging point operator (14) and at least one motor vehicle user (18) of a motor vehicle (16) with an electrical energy storage device, which are functionally connected to each other via a communication medium.In the event of an impending or already active critical power grid condition, an active communication option is enabled for the power grid operator (12) to contact the at least one motor vehicle user (18) regarding the active provision of electrical energy, and the at least one motor vehicle charging point operator (14) enables the at least one motor vehicle user (18) to provide electrical energy from the electrical energy storage of his motor vehicle (16) to the power grid operator (12).

The invention relates to a method for determining a flexibility capability for a power grid (2) within a time range by means of an energy system (1) having a plurality of installations (11) which can be operated flexibly with respect to the generation and / or consumption processes carried out by the installations, wherein the energy system (1) comprises a central control device (12), with respect to the installations (11), for controlling the operation of the installations (11). The method is characterized in that current capability values of the installations (11) are detected and transmitted to the control device (12), the flexibility capability that can be provided being determined by the control device (12) by comparing the detected current capability values with reference data relating to a reference operation of the installations (11). The invention also relates to a method for operating an electrical grid by means of a grid operator (3).

Operation of an electric vehicle (EV) is monitored and controlled to enable operation in a vehicle to grid (V2G) configuration. During bidirectional power transfer, energy stored in batteries onboard the electric vehicle can be transferred to the grid. During a period of high energy input into the grid, e.g., energy sourced from wind turbines / solar, the energy can be stored in the onboard batteries. During low energy input, the energy stored in the batteries can be transferred to the grid. V2G operation is conducted in accordance with a grid code(s) implemented at the grid. Grid codes can be forwarded from respective grid operators to a central system (remotely located from the EV), and subsequently forwarded for implementation to the EV. Based on EV location, the central system can control which grid code is forwarded to the EV and also whether the EV can perform V2G operation(s).

The invention discloses a micro-grid-multi-EV aggregator mixed game optimization method considering low-carbon economic operation. The method comprises the following steps: constructing a single EV slow charge capacity boundary model considering user travel uncertainty; constructing a carbon transaction model considering a certificate-carbon fusion mechanism; an operation model is optimized based on a mixed game: an optimal energy selling price strategy of a regional user aggregator is determined through a master-slave game, and a micro-grid operator solves an equilibrium solution for minimizing the comprehensive cost of the two parties based on a pricing boundary; and secondly, each aggregator obtains electric energy transaction payment in the alliance through cooperative game solution based on the transaction power determined in the previous stage, allocates interests of each user according to asymmetric Nash negotiations with different user contribution degrees, and finally forms a multi-agent cooperation mechanism giving consideration to market benefits and environmental benefits.

A method for controlling an electricity distribution grid having a nominal grid voltage, in particular in a critical grid situation, wherein a grid control center is provided for controlling the electricity distribution grid and the electricity distribution grid has at least one control region that comprises a plurality of mutually geographically separate wind farms, comprising the steps of: querying power outputs available from the wind farms, in particular on the basis of a weather forecast; defining a control node within the control region, in particular on the basis of the queried available power out-puts, preferably performed by the grid operator; combining a number of wind farms at the calculated control node to form a wind power plant on the basis of the queried available power outputs and / or a probability distribution of the available power output; controlling the wind power plant, in particular through the grid control center, by way of a wind power plant control unit, such that a required voltage quality and / or frequency stability and / or uninterrupted availability is provided in the control region.

This invention discloses a method, apparatus, equipment, and medium for collaborative optimization decision-making involving a fleet of vehicles in demand response. The method involves: receiving V2G demand response event signals from a grid operator, including demand power, response time period, and real-time electricity price; secondly, acquiring in real-time the location, battery state of charge (SoC), and task status of each autonomous electric vehicle in the fleet, as well as the location information of V2G charging stations; then, using a resource-task network (RTN) model to uniformly model vehicle resources, charging station resources, passenger service resources, and grid demand resources, constructing all potential task sequences, and quantifying resource consumption and task benefits; next, with the objective of maximizing the total profit of the fleet, performing optimization solutions under conditions such as battery SoC boundaries, charging station power constraints, and minimum grid response power, generating task sequences, path planning, and charging / discharging plans for each vehicle; finally, distributing the optimization decision results to the fleet for automatic execution.

The application discloses a power supply guarantee type light storage micro-grid operation method, system, equipment and medium based on multi-party game, and comprises the following steps: acquiring network parameters and equipment parameters of the power supply guarantee type light storage micro-grid; constructing a new incentive benefit model and a power supply guarantee subsidy model of the power supply guarantee type light storage micro-grid according to the network parameters and the equipment parameters of the power supply guarantee type light storage micro-grid; constructing a net income model of an investment subject; constructing a light-storage-grid cooperation game model; solving the light-storage-grid cooperation game model through an NSGA-II algorithm to obtain a Nash equilibrium point of the light-storage-grid cooperation game model, and obtaining and outputting an optimal operation strategy. The application considers the cooperation game of a photovoltaic investor, an energy storage investor and a micro-grid operator, realizes the emergency power supply guarantee of the micro-grid by using the photovoltaic and the energy storage, and maximizes the economic benefits of the three subjects.

The invention discloses a hydroelectric generating set all-condition simulation modeling method and system, and relates to the related technical field of hydroelectric generating sets, and the method comprises the steps: fusing multiple characteristics, and building a set first twin model and an all-condition label matrix; a registration error is analyzed through a multi-scale grid operator, and cross-scale reconstruction is carried out to generate a second twinborn model of the unit; performing inversion accident tracing by using the all-condition label matrix to construct a tracing graph network, and performing fault simulation factoring by combining the fault label matrix to establish a factoring graph network; and cooperatively fusing the all-condition inversion tracing graph network and the fidelity abnormal factorial graph network, and optimizing to generate a unit third twinborn model with higher fidelity. The technical problems that in the prior art, a hydroelectric generating set digital twinborn model is insufficient in fidelity, poor in all-working-condition coverage and dynamic inversion capacity and low in fault simulation and abnormal factorization accuracy are solved, and the technical effects that the hydroelectric generating set digital twinborn model with all-working-condition coverage is constructed, and the fidelity, interpretability and cross-scale consistency are improved are achieved.

Abstract A bidirectional electric vehicle (EV) charger that incorporates blockchain, smart load, and network stabiliser functionalities. The charger can both charge EVs and discharge energy back to the grid during unstable periods. The invention uses measurement of voltage and frequency to detect disturbances, fast home load management for smart load shedding (i.e. adjusting energy consumption based on grid conditions to enhance grid stability), and blockchain technology for secure energy trading between EV owners and grid operators. 12 / 13 BRIEF DESCRIPTION OF THE DRAWINGS Figure-1 shows that how the overall view of the offered invented system. Figure-2 shows the charger’s flowchart of the different mode of operation 12 / 13 BRIEF DESCRIPTION OF THE DRAWINGS Home Solar generation can't be used when grid is off It needs reference and the invented charger can do it. Electric Vehicle Block-Chain Based Smart EV-Charger as a Network Stabilizer - Generate virtual Inertia V2G mode - Use Blockchain base Smart Contracts - Disconnect from the network and using V2H mode - Support as smart load - Using the modern protection scheme to detect grid instability - Support home's solar generation in case of grid outage - Grantee the money back to EV owners in case of grid support Figure-1 shows that how the overall view of the offered invented system. Invented Charger's mode of operation Block-Chain Based Smart EV-Charger as a Network Stabilizer Mode A Mode Mode C Grid support Smart Load Standalone power source Grid unstabale Grid unstabale Independent Detected Detected Power Needed Isolate from Grid Isolate from Grid Direct injecting power to the grid based on the AS4777.2 and utility requirements Smart Load mode, by disconnecting the home loads EV owner can energize from the grid and start supply the home and use the Blockchain Garantee payment and managing the home loads Solar generation in case of grid outage. Off grid camping as Blockchain Garantee payment another example. Blockchain Payment Blockchain Payment Return to Mormal Condition Return to Mormal Condition Figure-2 shows the charger's flowchart of the different mode of operation 20 24 28 71 38 22 D ec 2 02 4 H o m e 2 0 2 4 2 8 7 1 3 8 2 2 D e c 2 0 2 4 M o d e A M o d e B M o d e c S t a n d a l o n e p o w e r s o u r c e G r i d u n s t a b a l e D e t e c t e d D e t e c t e d P o w e r N e e d e d B l o c k c h a i n P a y m e n t B l o c k c h a i n P a y m e n t R e t u r n t o M o r m a l

The application provides a three-dimensional neural rendering method and device based on a Fourier grid, and the method comprises the following steps: S1, image acquisition, a plurality of view images of a scene are acquired through a photographing device; S2, camera positioning device regression camera pose, camera pose information of each image is determined by using a camera positioning device; S3, solving a neural rendering field, an unbounded radiation field is modeled by using a grid operator FourierGrid, wherein FourierGrid is used for expanding an input signal into a plurality of frequency components by using a Fourier feature mapping, and a grid is used for modeling different frequency components; S4, input view acquisition, camera position and direction are converted into corresponding input views by using acquired camera pose information; and S5, input view sampling, a picture of a new view is rendered. By introducing the FourierGrid operator, the efficiency and accuracy of processing the unbounded radiation field are improved, and compared with an existing VoxelGrid operator, FourierGrid has better performance and efficiency in scene modeling and view synthesis tasks.

The invention discloses a system stability discrimination method and system based on a physical mechanism and a heterogeneous expert model, and relates to the field of power system analysis and artificial intelligence application, and the method comprises the specific steps: carrying out the track prediction based on collected data, and generating a future prediction sequence and a model parameter estimation value; constructing two types of parallel physical mechanism characteristics based on a future prediction sequence and a model parameter estimation value; constructing a heterogeneous expert model to carry out stable form discrimination; an expert output coupling item is introduced into the multi-gating hybrid expert architecture, and a comprehensive judgment result is generated based on gating fusion and an expert coupling mechanism; and converting a comprehensive judgment result into a structured judgment conclusion. According to the method, the stable state and the dominant instability type of the power system can be rapidly and accurately identified under the complex disturbance condition, and a key decision basis is provided for a power grid operator to adopt a targeted emergency control strategy.

The invention relates to the technical field of power grid dispatching, in particular to a multi-micro-grid optimal dispatching method and system considering new energy power generation uncertainty, and the method comprises the steps: building an upper layer model which is a revenue maximization objective function of a micro-grid operator, and a lower layer model which is a revenue maximization objective function of the micro-grid operator; the lower-layer model is a cost minimization objective function of the microgrid cluster; solving the upper layer model to obtain the purchase and sale electricity price by taking the income maximization of the micro-grid operator as a target, and transmitting the purchase and sale electricity price and a carbon emission factor dynamically released by the micro-grid operator to a lower layer model; updating the cost minimization objective function based on the carbon emission factor, solving the lower-layer model by taking the cost minimization of the microgrid cluster as an objective to obtain the purchased and sold electric quantity, and transmitting the purchased and sold electric quantity to the upper-layer model; performing iterative solution until the upper-layer model and the lower-layer model obtain optimal solutions, and performing optimal scheduling on the micro-grid cluster based on the optimal solutions; the overall operation efficiency of the power system can be improved.

The invention relates to the technical field of electric power systems and artificial intelligence, in particular to a day-ahead electricity price prediction framework, device and method based on time-frequency domain feature learning, and the method comprises the following steps: collecting electricity price data, total power, a new energy output ratio and thermal power bidding space real-time data; inputting the real-time data into a pre-constructed electricity price prediction model to obtain an electricity price prediction result; wherein the electricity price prediction model is an EPform model and comprises multiple encoders and a single decoder, the multiple encoders and the single decoder output feature information to the prediction decoder, and the prediction decoder fuses the outputs of the two encoders to perform electricity price prediction. The method is suitable for daily transaction strategy formulation of power market participants, scheduling optimization of power generation enterprises and risk management and control of power grid operators, supports adaptation of different market data characteristics by adjusting parameters such as patch length and encoder layer number, can integrate a real-time data updating mechanism, and provides decision support for dynamic optimization of a power system.

A grid simulation (GS) service performs scalable electrical grid simulations for clients of the service. The GS service receives, from a client (e.g., a utility / grid operator), a request to initiate a simulation session for an electrical grid. Based on the request, the service determines an initial amount of compute capacity to be provisioned for the simulation session. The service initiates the simulation session and provisions the initial amount of compute capacity. The service receives a request to implement a number of electrical grid simulations. If needed, the service will scale up or down the amount of compute capacity to implement the requested electrical grid simulations. The results may be provided to an endpoint.

Example systems, methods, and non-transitory computer readable media are directed to obtaining a power prediction to be provided to a grid operator of an electrical network, wherein the power prediction estimates an energy output of a power generation resource; determining a possible deviation from the nominal grid frequency indicative of a possible imbalance penalty during the power prediction period; determining whether a possible reduction in imbalance penalty is achieved by (a) adjusting power prediction or (b) controlling a battery energy storage system (BESS) associated with a power generation resource; in response to determining that a possible reduction in the imbalance penalty is achieved by adjusting the power prediction: determining an adjusted power prediction; and providing the adjusted power prediction to a power grid operator; and in response to determining that a possible reduction in the imbalance penalty is achieved by controlling the BESS associated with the power generation resource: causing an adjustment to the charge rate or discharge rate of the BESS.

To sufficiently supply inertia even when an abnormality occurs in a power grid under output restrictions imposed by a grid operator in a grid-forming power conversion device.SOLUTION: A grid-forming power conversion device for interconnecting an asynchronous DC power source to an AC power grid, includes a main circuit for converting DC to AC, and a control circuit for controlling the main circuit as a grid-forming device. The control circuit includes a restriction command acquisition unit that acquires a restriction command Plim limiting AC power from an external source, a frequency detection unit that detects a fundamental frequency ω0 of the AC voltage of the AC power, and a restriction command correction unit A1 that corrects the restriction command according to the rate of increase or / and decrease of the fundamental frequency.SELECTED DRAWING: Figure 2

This application discloses a peak-shaving dispatching method and system for energy storage power stations in a power system, relating to the field of power system operation dispatching and optimization control technology. The system accurately identifies power flow crossing conditions by synchronously collecting data and quantifies the resulting settlement deviations. It then directly links the charging and discharging dispatching of energy storage power stations with the economic objective of minimizing settlement deviations. By solving an optimization model, it obtains the optimized charging and discharging power plan for the energy storage power station within a future dispatching cycle. This optimized power plan is then distributed to the energy management system of the energy storage power station to control the station to perform corresponding charging and discharging operations. This effectively compensates for settlement errors caused by complex power flow in the grid, improves the fairness and accuracy of new energy power trading, and provides grid operators with a refined and automated means of controlling settlement deviations.

The application provides a multi-agent game optimization method and device for a renewable energy micro-grid, and the multi-agent game optimization method for the renewable energy micro-grid comprises the following steps: obtaining interaction data among a micro-grid operator, an energy storage operator and a user, respectively constructing a micro-grid operator model, an energy storage operator model and a load side model based on the interaction data among the micro-grid operator, the energy storage operator and the user; constructing a one-master multi-slave multi-agent game model based on the micro-grid operator model, the energy storage operator model and the load side model; solving the one-master multi-slave multi-agent game model to generate a multi-agent game optimization strategy; and wherein the multi-agent game optimization strategy is used to provide energy for the operation of the renewable energy micro-grid. The method realizes the maximization of multi-agent benefits, solves the problem of the game behavior strategy among the micro-grid, the energy storage and the user, makes the energy supply more economical, and makes the user electricity use more reasonable.