608 results about "Optical storage" patented technology

An inertia cooperative control method of an integrated optical storage alternating current and direct current hybrid micro-grid comprises the steps that firstly, according to static and dynamic power capacities of energy storage units in direct current sub-grids and allowed direct current voltage deviation, sub-grid equivalent virtual resistance and virtual capacitance are calculated; secondly, RC + R type parallel virtual impedance parameters are distributed according to the power proportion of each energy storage unit, and multi-energy-storage cooperative response power disturbance according to the capacity is achieved; then, a phase angle is generated based on the mapping relation between direct-current side voltage and frequency, an alternating-current voltage amplitude instruction is determined in combination with reactive power droop control and feeder impedance voltage drop compensation, and a dq-axis voltage instruction is generated through virtual impedance compensation; normalized three-phase modulation waves are obtained through voltage-current double closed-loop control and dq / abc coordinate transformation, and six paths of PWM signals are generated to drive an interconnection converter after the normalized three-phase modulation waves are compared with triangular carrier waves. The method does not need to depend on external communication, has the capabilities of autonomous inertia support, voltage and frequency coordinated regulation and reasonable multi-source power distribution, and improves the stability and dynamic response performance of the system under island operation.

The invention discloses a distributed hierarchical cooperative control method and system for an optical storage all-in-one machine cluster, and the method comprises the steps: collecting voltage, frequency and harmonic data, and calculating a global voltage deviation, a frequency deviation and a harmonic content consensus value; calculating a unified transient support index judgment working condition based on the consensus value, and generating a global virtual inertia and impedance demand in emergency; calculating a schedulable potential index of each node based on local data of the node; distributing the requirements for the first time according to the indexes, and adjusting the parameters of the inverter to execute control after the nodes which do not meet the requirements are distributed for the second time; a three-layer architecture of'decision-aggregation-execution 'is constructed, a global state consensus and a nearby-global secondary distribution strategy are realized in combination with a consistency algorithm, a set of'local priority-adjacent support-global bottom-taking' allocation mechanism is formed, the adaptive capacity of the optical storage cluster to complex working conditions and the regional power quality are improved, and the optimal power quality is improved. And the grid-connected stability and the absorption level of the large-scale distributed energy in the weak power grid environment are remarkably improved.

The invention discloses a power control method, system, equipment and medium for an optical storage and charging station, and belongs to the field of optical energy storage. A health degree factor is determined based on collected equipment operation data; determining a predictive factor based on the collected photovoltaic data; based on the power allocation weight and operation factors, a weight function is established to calculate the instruction weight of each device, and the operation factors comprise a planned maintenance factor, a sudden failure factor, an energy storage correlation factor, a health degree factor and a prediction factor of the parallel devices; calculating to obtain a power instruction of each parallel device; and controlling the parallel equipment to operate according to the power instruction through the station controller. According to the method, the bearable degree of the equipment is measured by calculating the dynamic weight comprehensively obtained on the basis of the health factor, the prediction factor, the maintenance factor, the sudden failure factor and the energy storage correlation factor, and the power instructions with inconsistent stagger degrees are distributed according to the actual operation condition, so that the operation stability is improved.

The invention discloses a method and system for improving the energy utilization rate by utilizing light storage resource prediction, and the method comprises the steps: collecting irradiance temperature historical output data and load consumption feature data through a distributed sensor and an edge gateway, processing time sequence features through a sequence prediction model, and integrating multi-dimensional input through the fusion of an integrated learning model; a future prediction result of photovoltaic output and load demand is obtained; further acquiring real-time parameters of the charge state and the charge and discharge efficiency of the energy storage equipment, constructing an energy storage full life cycle state evaluation model to calculate dynamic indexes, and determining an available capacity boundary; and if the boundary exceeds a preset threshold value, peak-valley period characteristics are extracted, and an optimal strategy sequence including photovoltaic peak charging and load peak discharging is generated by adopting an intelligent optimization algorithm in combination with power grid peak-valley electricity prices and carbon emission constraints. According to the invention, the photovoltaic consumption rate is obviously improved, the operation cost is reduced, the carbon emission requirement is met, and intelligent and efficient management of the optical storage system is realized.

The invention belongs to the technical field of energy station management, and particularly relates to a comprehensive energy station management system based on a light storage and charging micro-grid, and the system comprises a sensing layer which is used for collecting the real-time operation data of a photovoltaic facility, an energy storage system, a charging pile and an environment; the network layer is used for transmitting data of the sensing layer in real time and establishing two-way communication with a power grid dispatching center at the same time; and the application layer is used for realizing energy optimization scheduling, equipment cooperation, fault early warning and power grid interaction according to the data transmitted by the network layer. The AI dynamic energy scheduling module, the prediction model module, the optimization model module and the solving module are arranged, so that the energy utilization efficiency can be improved, the light abandoning rate can be greatly reduced, the electricity purchasing cost can be remarkably reduced, and economic optimization is realized.

The invention discloses a household light storage and charging countercurrent prevention and grid-connected and off-grid intelligent switching system based on a closed-loop algorithm. The system comprises the following units: a data acquisition unit, a prediction model construction unit, a dynamic mode adaptive adjustment unit, a risk calculation unit and a grid-connected and off-grid control unit. The data acquisition unit is used for acquiring multi-source real-time operation data of the household optical storage and charging system; and the prediction model construction unit is used for constructing an energy demand prediction model and a photovoltaic generating capacity prediction model based on an intelligent algorithm and outputting a prediction result. According to the household optical storage and charging countercurrent prevention and grid-connected and off-grid intelligent switching system based on the closed-loop algorithm, the closed-loop algorithm is adopted, the operation mode of the system can be intelligently judged through real-time prediction and dynamic mode adjustment, self-adaptive adjustment is achieved, efficient operation of the optical storage and charging system is ensured, and the service life of the system is prolonged. And energy waste caused by excessive dependence on a fixed rule of the system can be avoided.

The invention relates to the technical field of power electronics and new energy control, in particular to a hybrid inverter collaborative energy management system and method suitable for an optical storage system. According to the system, by constructing an alternating current and direct current side impedance collaborative matching framework, the power grid impedance and the direct current link state are sensed in real time, direct current equivalent impedance and alternating current reactive output are optimized in a collaborative mode, and the frequency domain impedance characteristic of the system is actively reconstructed to suppress oscillation. The invention provides a hybrid inverter collaborative energy management system and method suitable for an optical storage system, which solve or at least alleviate the problem of AC-DC coupling oscillation of the optical storage system under weak power grid and power fluctuation, improve the dynamic robustness, operation efficiency and safety reliability of the system, realize millisecond-level oscillation detection and suppression, and improve the reliability of the system. The energy storage life is prolonged; and the overall energy efficiency is improved.

The invention relates to the technical field of photovoltaic power generation, in particular to a photovoltaic charging and discharging control method and system based on a direct-current coupling optical storage all-in-one machine, and the method comprises the steps: monitoring system operation parameters in real time; after the countercurrent risk is judged, energy storage is preferentially utilized to absorb redundant electric energy; when the stored energy is saturated, the photovoltaic output is dynamically adjusted instead of shutdown; when photovoltaic power generation is insufficient, the gap is supplemented through energy storage discharge. By monitoring system operation parameters in real time and dynamically coordinating photovoltaic power generation, energy storage charging and discharging and load requirements, photovoltaic energy is utilized to the maximum extent while reverse current of a power grid is avoided, redundant electric energy is preferentially stored in a battery, and photovoltaic output is intelligently adjusted instead of direct shutdown after energy storage is saturated; and when the load demand is higher than that of photovoltaic power generation, a gap is supplemented through energy storage discharge, so that energy waste is remarkably reduced, the system operation time is prolonged, the overall power generation income and economy are improved, and safe and stable operation of a power grid is ensured.

The invention relates to the technical field of electric digital data processing and energy storage system safety control, in particular to an optical storage and charging integrated station energy storage system. Comprising a data acquisition module which is used for acquiring a state feature vector of an energy storage system, planned scheduling power of an upper-layer energy management system, an external power grid interference index, and a real-time safety state and an economic value index of a battery management system in real time; the risk assessment module is used for generating a predictive risk score; the decision threshold module is used for calculating a dynamic intervention threshold; the arbitration decision module is used for generating a negative sign; the instruction correction module is used for determining a derating factor in response to the override mark and generating a correction scheduling instruction; or when the negative sign is not generated, outputting the planned scheduling power as a corrected scheduling instruction. According to the invention, early warning and active prevention of the potential thermal runaway risk are realized, and the intrinsic safety level and the operation reliability of the system are obviously improved.

The invention discloses a self-adaptive load balancing method for a light storage and charging system based on dynamic scene perception, and relates to the technical field of load balancing of the light storage and charging system, and the method comprises the following steps: calculating the time period photovoltaic generating capacity of different electricity price time periods based on a sunshine time period; analyzing the single-hour power load of the power grid per hour within one day based on the historical power utilization data of the region; analyzing the overload time period and the normal time period, and calculating the required electric quantity of the overload time period; analyzing the energy storage consumption required to be consumed by the optical storage and charging system in the overload period; analyzing a storage balance scheme of the optical storage and charging system in a normal time period based on the energy storage consumption; the method is used for solving the problems that only the influence of the economic level is considered and the electricity consumption of residents is difficult to accurately predict in the existing load balancing technology of the optical storage and charging system, so that the effect of the optical storage and charging system is not fully played, and the proportion of charging and discharging cannot be accurately planned in advance.

The invention discloses a megawatt-level optical storage and charging system bidirectional power coordination control method and system based on a network construction technology, and relates to the technical field of power system control. The method comprises the following steps: initializing a multi-port energy router of the megawatt-level optical storage and charging system, and configuring control parameters of a virtual synchronous generator (VSG); a mains supply signal and the maximum mains supply power of a mains supply power grid system connected with the megawatt-level optical storage and charging system are obtained regularly, a grid-connected mode signal is generated if the running state of a mains supply power grid is normal, an off-grid mode signal is generated if the running state is abnormal, and network construction type bidirectional power coordination control is executed according to the signals. According to the invention, switching between the grid-connected mode and the off-grid mode can be rapidly and accurately carried out according to the real-time operation state of the power grid, and stable connection and cooperative operation of the system and the power grid are ensured in the grid-connected mode; in the off-grid mode, the independent and stable operation of the system after the system is separated from the power grid is guaranteed, and the adaptability of the system to different power grid working conditions is improved.

The invention discloses a multi-type resource participation power grid frequency modulation method based on a consistency algorithm, and the method comprises the steps: firstly constructing an improved frequency response model fusing distributed optical storage equipment, hydrogen storage and energy storage equipment and a DC flexible load, identifying system parameters, solving a multi-resource comprehensive adjustment coefficient, constructing a directed graph model, employing a grouping consistency algorithm, and obtaining a multi-type resource participation power grid frequency modulation model; the optimal adjustment coefficient of each resource is solved through distributed optimization of an augmented Lagrange function and a consistency index, and primary frequency modulation of a multi-type resource collaborative response system is driven. According to the multi-type resource participation power grid frequency modulation method based on the consistency algorithm, by driving a multi-type resource collaborative response system to perform primary frequency modulation, collaborative regulation and control of light storage, hydrogen storage and flexible load are realized, economy and operation constraints are considered through distributed optimization, and communication complexity is reduced through a clustering iteration mechanism; and the frequency stability of the high-proportion new energy power grid is obviously improved.

The invention discloses a power distribution method, a storage and charging system, an optical storage and charging system and a computer program product, and relates to the technical field of power system control, the power distribution method is applied to power distribution of a target system, and the method comprises the following steps: obtaining charging request data of each charging load, the charging request data represents the charging demand of each charging load in a future period of time; calculating or determining the total request power of each charging load according to the charging request data; a power distribution strategy meeting a preset condition is obtained through calculation according to the total request power, and the preset condition is that under the condition that the actual charging power of each charging load is equal to the total request power, when power distribution is carried out according to the power distribution strategy, the off-grid power of the public power grid connected to the target system is larger than or equal to a preset threshold value. According to the power distribution scheme, the load power conversion state is sensed in advance, and actions are performed in advance, so that the accuracy, rapidity and reliability of countercurrent prevention are improved.

The invention discloses a collaborative optimization configuration method and system for a light storage micro-grid in an expressway service area, and the method comprises the steps: firstly considering the photovoltaic bearing capability of the expressway service area, and constructing a master-slave game model of the light storage micro-grid; the master-slave game model comprises a capacity investment configuration master model with minimum investment cost and maximum photovoltaic bearing capacity as targets and an operation scheduling optimization slave model with minimum operation cost as targets; and solving the master-slave game model by nesting a commercial solver through adopting a Lu Eupe fox optimization algorithm, and obtaining a collaborative optimization scheme of capacity investment configuration and operation scheduling of the optical storage micro-grid in the expressway service area. According to the method, the master-slave game model of the optical storage micro-grid is constructed, the key problems of scattered resource allocation, insufficient operation coordination and the like of the optical storage micro-grid in the expressway service area are effectively solved, the power purchase cost of the power grid is effectively reduced, and the power supply reliability of the optical storage micro-grid is greatly improved.

The invention provides a multi-target dynamic optimization optical storage and charging operation control method. The method comprises the following steps: step 1, a dynamic priority control mechanism; 2, a multi-time-scale optimization model is established; step 3, an energy storage life protection strategy; and step 4, a power market interaction module. According to the invention, through dynamic optimization of cooperative scheduling of photovoltaic power generation, energy storage charging and discharging and charging pile loads, multi-target cooperative optimization of economy, energy efficiency and power grid stability is realized, the economy is improved, the light abandoning rate is reduced, and the power grid supporting capability is improved.

The invention relates to the technical field of power systems, and discloses a self-adaptive equalization control method, system and device for the state of charge of energy storage units of an optical storage direct current micro-grid and a medium, and the method comprises the steps: building a system model comprising a photovoltaic power generation assembly and a plurality of parallel energy storage units, constructing a droop control coefficient adjustment mechanism associated with the state of charge of each energy storage unit, and realizing dynamic nonlinear adjustment of the control coefficient along with the state of charge; meanwhile, a bus voltage secondary compensation mechanism based on the average value of the output voltage of the energy storage unit and a current balance adjustment mechanism based on the virtual voltage drop difference are constructed; and overlapping the two types of compensation quantities to a voltage control instruction of each energy storage unit, and synchronously realizing the voltage stabilization of the direct-current bus and the rapid equalization of the charge states of the energy storage units. Manual intervention is not needed, uneven power distribution caused by line impedance difference or operation condition change is effectively restrained, the system reliability can be improved, and the energy storage service life can be prolonged.

The invention relates to the technical field of power system stability constraint optimization and computer algorithms, and provides an energy storage fault ride-through optimization method considering optical storage access weak power grid stability constraint, which comprises the following steps: collecting power grid operation data to generate a dynamic enhancement data set; constructing and correcting a digital twinborn body on line; generating a guide vector field and initializing an optimization framework; executing hybrid iteration to generate a candidate strategy; an optimization process is fed back through simulation evaluation; verifying a decision output control instruction after convergence; and deploying an instruction and realizing online updating. According to the method, the characteristics of the power grid are accurately modeled by using the digital twin, optimization search is guided in combination with the guide vector field, the non-convex optimization problem caused by stability constraints is effectively processed through a hybrid iteration strategy, and the voltage and frequency recovery capability in the fault ride-through process is improved.

The invention discloses an optical storage charging-UPQC multi-port cycle calendar life cost collaborative energy management method, and belongs to the technical field of electric energy quality management and optical energy storage collaborative control of a power distribution and utilization system. The invention aims to provide a light storage and charging-UPQC multi-port cycle calendar life cost collaborative energy management method which introduces a photovoltaic flexible power regulation and'cycle + calendar 'combined life modeling mechanism and embeds energy storage life cost into a model predictive control (MPC) framework on the premise that UPQC undertakes power quality compensation. According to the invention, a model predictive control (MPC) framework is adopted to carry out cooperative energy management on photovoltaic flexible output, energy storage power distribution and charging load limit, and when the SOC approaches a boundary, photovoltaic load reduction and power change rate limitation are automatically triggered. According to the method, energy storage deep circulation and excessive loss can be actively inhibited while the energy balance of the direct-current bus is maintained, and the comprehensive targets of electric energy quality treatment, energy stabilization and energy storage life protection are achieved.

The invention provides a method and a device for controlling active power of an optical storage magnetic reactance type dynamic voltage restorer, and relates to the technical field of power electronics. Determining a power grid side fundamental wave voltage amplitude, a load actual fundamental wave voltage amplitude and a target frequency voltage harmonic equivalent amplitude, extracting energy storage available active power and a preset fundamental wave and harmonic compensation coefficient, calculating a fundamental wave voltage deviation rate and a harmonic deviation rate, and when the fundamental wave voltage deviation rate reaches a preset deviation threshold value, determining the harmonic equivalent amplitude of the target frequency voltage; active power compensation amounts of fundamental waves and harmonic waves are calculated respectively, and a total compensation active power demand is obtained through superposition; according to a comparison result of energy storage available active power and a total compensation demand, a distribution proportion of the two is adjusted, a fundamental wave voltage amplitude change slope and a fundamental wave voltage deviation rate variance are calculated based on a monitoring interval comprising a plurality of sliding windows, and a fundamental wave compensation coefficient is adjusted so as to correct the total compensation demand.

The invention discloses a panoramic situation awareness and early warning method, system, equipment and medium for real-time interaction between an optical storage and charging micro-grid and a power distribution network, and belongs to the technical field of situation awareness and early warning, and the method comprises the steps: building a data collection network covering the optical storage and charging micro-grid and the power distribution network, obtaining electrical quantity, environmental quantity and equipment state information, carrying out the preprocessing of the data, and carrying out the early warning of the real-time interaction of the optical storage and charging micro-grid and the power distribution network; pre-processed multi-source data is obtained; inputting the multi-source preprocessed data into an improved Kalman filtering algorithm to obtain fused state data; constructing a panoramic situation vector of the optical storage and charging microgrid and the power distribution network based on the fused state data, and obtaining a situation assessment result; inputting the situation assessment result into a hybrid prediction model composed of a long short-term memory network and a Bayesian network to generate a risk assessment result; constructing a multi-objective optimization model according to a risk assessment result, and outputting an intervention control signal; and performing operation monitoring and feedback updating based on the intervention control signal. According to the invention, the accuracy and real-time performance of situation identification are improved.

The invention relates to a distributed optical storage network energy regulation and control system based on an unmanned aerial vehicle cluster. The system comprises an energy network module; a mobile energy routing module; the decision control module is configured to execute the following work: according to the electric energy state and position of each node and the electric energy state and position of each unmanned aerial vehicle which are acquired in real time, establishing an energy topological relation mapping table of the nodes and the unmanned aerial vehicles; based on the electric energy gradient difference between the nodes in the mapping table and the mobile energy consumption cost of the unmanned aerial vehicle, a virtual guide signal is introduced to generate a routing map; discretizing the routing map into a field intensity vector set, broadcasting the field intensity vector set to the unmanned aerial vehicle cluster, triggering the self-organizing behavior of the unmanned aerial vehicle cluster, and enabling the unmanned aerial vehicle cluster to execute power taking or reverse feed operation. Therefore, for the technical problems that dynamic supply and demand imbalance is caused by the island effect of the distributed optical storage system, and a traditional micro-grid cooperation mode is high in cost and cannot adapt to the urban complex environment, global optimization configuration of the distributed energy is achieved by constructing a multi-stage cooperation architecture.

The invention discloses an end-end self-control-based transformer area light storage and charging coordinated regulation and control system and an autonomous method. The system constructs an end-end-transformer three-level autonomous architecture: an end-level autonomous unit is responsible for local millisecond-level reflection control; the edge autonomous nodes realize intra-zone collaboration through federated learning, and physical security constraints are embedded into AI decisions by using digital twin bodies; the court-level federation learning center realizes knowledge sharing under cross-court privacy protection through secure multi-party computing, the method further integrates transfer learning to solve the cold start problem of a new court, and a three-time scale regulation and control mechanism is adopted to cope with disturbance of different rates; the autonomous capability, the response speed, the safety level and the intelligent degree of the system are improved.

The invention discloses a modular expressway chain-type micro-grid optical storage and charging capacity optimal configuration system, and relates to the field of expressway electric energy configuration, and the method comprises the steps: constructing an expressway chain-type micro-grid model; simulating the traffic flow and the traffic flow charge state distribution of the expressway based on the expressway chain type micro-grid model; according to the electric vehicle entry rate and the vehicle flow of each service area node, the average waiting time of the electric vehicles at each service area node is determined; according to the charging load capacity of each service area node and the average waiting time of the electric vehicles at each service area node, taking the minimum comprehensive cost as a target, and taking the node source storage and charging quantity, the node source storage and charging capacity and the average waiting time as constraints, establishing an expressway chain type micro-grid optical storage and charging capacity optimization model; and solving to obtain an optimal scheme of optical storage charging capacity configuration. According to the invention, the cost is reduced on the basis of satisfying the electric energy supply of the electric vehicle, and the charging queuing time of the electric vehicle is reduced.

The invention belongs to the technical field of VSG network construction active support, and particularly discloses a transient support power coordination control method and system for a network construction type optical storage system, and the method comprises the steps: building an equivalent mathematical model of the network construction type optical storage system, and obtaining key control parameters of a virtual synchronous generator control link of the optical storage system based on the equivalent mathematical model; constructing an internal energy flow characteristic analysis model of the network construction type optical storage system based on key control parameters of a control link of the virtual synchronous generator, and further obtaining a core defect of passive participation of energy storage in transient response; and based on the core defects, designing an energy storage driving control strategy based on VSG transient response power decomposition to control an energy storage subsystem to charge and discharge, and completing transient support power coordination control of the network construction type optical storage system. The problems that in the prior art, due to the fact that energy storage passively participates in frequency modulation, response timeliness and accuracy are insufficient, and due to the fact that VSG transient control complexity is high, large-scale engineering application adaptability is poor are solved.

The invention provides a micro-grid optical storage capacity optimal configuration method and system, and relates to the technical field of micro-grid optimization, and the method comprises the steps: setting a sectional capacity configuration parameter according to a load characteristic parameter and an energy access condition of a micro-grid; setting a first compensation correction value and a second compensation correction value based on impedance matching characteristics of the micro-grid and charge and discharge efficiency parameters of the energy storage unit; reversely analyzing the capacity optimization configuration parameter combination obtained through optimization into the sectional capacity configuration parameters; and collecting real-time monitoring data in real time through an industrial Ethernet, and performing dynamic refreshing and rolling optimization on a capacity optimization configuration parameter combination according to a preset power balance threshold value and an actual operation deviation of an optical storage cooperative configuration execution scheme. According to the invention, the technical problem of capacity redundancy or insufficiency caused by static and fixed configuration of the optical storage capacity of the micro-grid in the prior art is solved, and the configuration precision of the optical storage capacity of the micro-grid is improved.

The invention discloses an optical storage diesel energy management system and method. The system comprises a photovoltaic power generation system, an energy storage system, a diesel power generation system, an alternating current bus, a load and an energy management controller. The photovoltaic power generation system, the energy storage system, the diesel power generation system and the load are all electrically connected with the alternating current bus, and the photovoltaic power generation system, the energy storage system and the diesel power generation system are all in communication connection with the energy management controller; and the energy management controller controls the operation states of the photovoltaic power generation system, the energy storage system and the diesel power generation system according to the photovoltaic power generation power of the photovoltaic power generation system, the total load power of the load, the energy storage charge state of the energy storage system and a priority control strategy. According to the invention, the photovoltaic power generation system is directly and electrically connected to the AC bus, so that the photovoltaic power loss can be avoided, the system operation efficiency is improved, and the real-time cooperative control of three paths of energy sources of the photovoltaic power generation system, the energy storage system and the diesel power generation system is realized through the photovoltaic power generation power, the total load power and the energy storage charge state.

The invention discloses an optical storage diesel micro-grid based on analog quantity control and a dynamic load tracking control method. The power grid comprises a photovoltaic power generation unit, a diesel power generation unit, an energy storage cluster, a sampling and signal processing module, an analog quantity control interface module and an energy management system. The energy management system is configured to control the energy storage cluster to perform discharge compensation under the condition that the power change rate is greater than a preset positive threshold value; under the condition that the power change rate is smaller than a preset negative threshold value, the energy storage cluster is controlled to carry out absorption charging; controlling the energy storage unit to correct the output power according to the deviation between the average charge state of the energy storage cluster and the charge state of the energy storage unit; and controlling the diesel power generation unit to stop when the total charge state of the energy storage cluster is greater than the first charge threshold percentage, and controlling the diesel power generation unit to start when the total charge state of the energy storage cluster is less than the second charge threshold percentage. Therefore, power fluctuation quick response, energy storage SOC balance and efficient starting and stopping of the diesel engine are achieved.

The invention relates to the technical field of power system automatic control, and discloses an optical storage and charging integrated flexible access optimization control method, system and device and a medium. Sequentially executing the steps of system initialization, real-time data acquisition, multi-time scale prediction planning, multi-objective optimization solution, model prediction rolling control and reinforcement learning adaptive optimization. The core of the method is that rolling optimization is carried out by adopting model predictive control, a multi-objective function integrating economic cost, power grid friendliness and user satisfaction is combined, and a reinforcement learning mechanism is introduced to adjust a control strategy online. According to the method, the photovoltaic consumption rate and the user satisfaction degree are effectively improved, the system operation cost is remarkably reduced, the robustness of photovoltaic output and load fluctuation uncertainty is enhanced, and efficient, economical and reliable cooperative operation of the photovoltaic storage and charging system is realized.

The invention relates to the technical field of optical storage charging stations, and discloses an optical storage charging station optimized operation method considering stepped carbon transaction and multi-agent collaboration, which comprises the steps of collecting carbon emission data of each agent in a charging station, considering interaction between the charging station and a power grid, and establishing a stepped carbon transaction mechanism; comprehensively considering the interest appeal and operation safety of each main body, and establishing a comprehensive optimization objective function by taking the maximization of the comprehensive benefit of the charging station as an objective; schedulable resources in the charging station are abstracted into intelligent agents, the intelligent agents cooperate with a carbon transaction mechanism, a multi-agent reinforcement learning framework is constructed to solve a comprehensive optimization objective function, and a multi-agent cooperative optimal operation scheduling strategy is obtained. According to the method, the nonlinear stepped carbon transaction mechanism close to the real carbon transaction market is established, the optimal scheduling strategy obtained based on the carbon transaction mechanism has perspectiveness, the benefits of the power grid and the optical storage charging station can be balanced, and the overall market competitiveness and risk resistance of a power system are effectively improved.

The invention relates to the field of power prediction, and discloses a multi-modal photovoltaic power generation power prediction system based on a logistics unmanned aerial vehicle cluster, and the system comprises the steps: obtaining multi-modal data through employing the unmanned aerial vehicle cluster; processing and evaluating the multi-modal data, and evaluating the accuracy, integrity and consistency of each modal data; constructing a respective prediction model for each model, and performing iterative training by using the obtained data to obtain a feature extraction value of each modal; and carrying out multi-modal fusion on the feature extraction values obtained by each modal based on Transform, inputting the feature extraction values into an integrated prediction model, and predicting to obtain the power generation power of each optical storage and charging cluster. Through multi-modal data complementarity enhancement, the unmanned aerial vehicle collects local cloud layer images, high-resolution meteorological sensor data and historical power generation time sequence data, and the space-time blind area of traditional single meteorological station data is effectively made up. A complementary prediction mechanism is formed by adopting the dynamic feature extraction of the CNN on the cloud layer image and the time sequence modeling of the LSTM on the historical power generation data in combination with the physical rule regression analysis of the meteorological data.