1501results about "Energy storage" patented technology

The invention discloses a self-generating and self-using distributed photovoltaic power station power anti-countercurrent control method and system, and relates to the technical field of photovoltaic anti-countercurrent control, and the method comprises the steps: obtaining the real-time load power of a grid-connected point of a power grid and the output power of a photovoltaic inverter, and calculating the net load power deviation; when the net load power deviation is smaller than a preset countercurrent risk threshold value, it is judged that a countercurrent risk exists, and an anti-countercurrent adjusting instruction is generated; in response to the anti-countercurrent regulation instruction, dynamically correcting the maximum output power limit value of the photovoltaic inverter, and synchronously activating the charge and discharge compensation mode of the energy storage system; an anti-countercurrent control coefficient is calculated, and the power reduction proportion of the photovoltaic inverter and the compensation power of the energy storage system are synchronously adjusted based on the anti-countercurrent control coefficient, so that the power flow of the grid-connected point of the power grid is kept to be zero or forward flow; according to the method, dynamic and accurate cooperation of photovoltaic reduction and energy storage compensation power in time and magnitude is realized, and the efficiency of a self-generating and self-using distributed photovoltaic power station is improved.

The invention relates to a photovoltaic power grid energy storage optimization regulation and control method based on multi-scale prediction. The method comprises the following steps: A1, obtaining historical power generation data, real-time meteorological data and numerical weather forecast of a photovoltaic power station; a2, generating a multi-time-scale photovoltaic output prediction sequence; a3, establishing an energy storage dynamic model of charge and discharge efficiency, capacity attenuation and operation constraint; a4, generating an energy storage charging and discharging demand curve under different time scales; a5, constructing a multi-time scale coupled optimization model by taking power grid operation cost minimization and renewable energy consumption maximization as targets; a6, updating an energy storage scheduling instruction in a rolling manner based on latest prediction data by adopting a model prediction control framework; a7, monitoring the deviation between the actual photovoltaic output and the power grid load, and dynamically adjusting the energy storage charging and discharging power; and A8, correcting a prediction error through Kalman filtering and a closed-loop feedback mechanism. According to the invention, high-efficiency operation can be realized, and power grid cost minimization and renewable energy consumption maximization can be realized.

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

The invention discloses an on-site monitoring system for the performance of an elastic loose type anchorage system suitable for deep-sea buoys, and particularly relates to the field of deep-sea monitoring. The on-site monitoring system auxiliary comprises a central processing module, wherein the output end of the central processing module is separately connected with an information display module,an information storage module, an auxiliary recovery module and a driving module, and the input end of the central processing module is separately connected with a power supply module, a monitoring module, a correction module and a positioning module. According to the on-site monitoring system for the performance of the elastic loose type anchorage system suitable for the deep-sea buoys, the auxiliary recovery module is arranged, air bags are installed at a plurality of node positions on the anchorage system, a booster pump in a pressurization unit is used, outside air is conveyed into a floating ball unit through a pipeline unit, so that the retractable air bags are enabled to bulge upwards to float, the whole anchor system is directly floated in sections, people conveniently recycle theanchorage system greatly, the workload during the recycling process is reduced, and the practicability is high.

The invention relates to the technical field of power system operation and control, and discloses a primary and secondary frequency modulation cooperative control system of a hybrid energy storage coupling wind generating set, which comprises a wind power generation unit, a hybrid energy storage unit and a central cooperative controller. A total power demand including inertia response and primary and secondary frequency modulation is synthesized, a primary and secondary frequency modulation cooperative distribution module generates a dynamic adjustment weight by using an S-type nonlinear function based on a frequency change rate and frequency deviation coupling relationship, and an energy relay compensation mechanism is introduced to fill a power gap in a switching process. And the SOC adaptive constraint and execution module applies direction selective boundary constraint to the state of charge, and controls hybrid energy storage to perform internal energy self-balancing in a frequency modulation dead zone. According to the invention, seamless connection of multi-time scale frequency modulation is realized, frequency secondary drop is effectively prevented, and the frequency support capability and the self-recovery capability of the system are 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 the technical field of intelligent control of a power system, in particular to a photovoltaic power generation-energy storage-power grid intelligent scheduling method and system based on multi-mode energy management, and the method comprises the steps: 1, collecting and fusing multi-source operation data in real time; 2, establishing a multi-modal feature fusion model; 3, according to the photovoltaic fluctuation amplitude and the frequency deviation component, the energy storage adjusting capacity is formed; 4, constructing a differential control strategy for each mode, and achieving the dynamic matching of the virtual inertia and the power grid demand in the power grid supporting mode; and step 5, executing multi-time scale rolling optimization control, triggering strategy reconstruction according to mode switching, and maintaining power continuity among different modes through a transition process. According to different modal requirements, differentiated control strategies are adopted, so that the service life loss of the energy storage system can be reduced and the service cycle of the energy storage equipment can be prolonged while the energy storage system is ensured to quickly respond to the power grid requirement.

The invention discloses a charging and discharging control method for a photovoltaic energy storage system based on a dynamic threshold value, relates to the technical field of photovoltaic energy storage, and solves the technical problem that energy waste or battery life attenuation is easily caused due to the fact that shunting treatment and discharging control lack a refined grading strategy when photovoltaic power is excessive or insufficient. The charging threshold upper limit and the discharging threshold lower limit are combined with the energy storage rated capacity and the charging and discharging efficiency for dynamic calculation, overcharging and overdischarging are avoided, the power is dynamically limited by the SOC-related charging and discharging limiting function according to the real-time SOC, the cycle loss of the battery is reduced, the service life is prolonged, and the reliability of the battery is improved. A grading strategy of local adjustable load priority, grid-connected electricity selling and limited power protection is adopted for shunting processing during photovoltaic excess, it is ensured that key loads are not affected by power, key loads and non-key loads are distinguished through discharging control during photovoltaic insufficiency, energy storage discharging is triggered only for the key loads, the non-key loads are cut off in advance through an early warning threshold value, and therefore the energy storage efficiency is improved. Discharge pressure is reduced, and power supply continuity is improved.

The invention relates to the technical field of electric power operation and maintenance, in particular to a distributed optical storage unit cooperative scheduling control method and system, the method is applied to a distributed optical storage system comprising a plurality of optical storage units, each optical storage unit comprises a photovoltaic unit, an energy storage unit and a load unit, and is configured with a local unit controller. Comprising the following steps: collecting real-time operation data of an optical storage unit, and extracting local collaborative scheduling characteristics and a local DC bus voltage instantaneous fluctuation ratio from the real-time operation data; each unit controller inputs the corresponding local cooperative scheduling feature into a preset local scheduling strategy generation model, and outputs an initial scheduling action instruction set; and performing global voltage stability evaluation on the distributed optical storage system based on the local direct current bus voltage instantaneous fluctuation rates corresponding to all the optical storage units, and calculating to obtain a system voltage fluctuation index. The distributed local control capability and the global collaborative demand are organically fused, and the global voltage stability and the collaborative scheduling consistency are ensured.

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

The invention discloses a photovoltaic energy storage cooperative control method and system, and the method comprises the steps: obtaining the real-time state data and environment information of distributed photovoltaic and energy storage equipment, and constructing a system network topology; constructing a hierarchical prediction model including photovoltaic power generation prediction, load demand prediction and electricity price prediction based on the system state data set; constructing a multi-objective function containing an economic benefit objective and a system stability objective based on a prediction result, and performing objective decomposition through recursive iteration; according to a local optimization target, generating a photovoltaic power adjustment strategy and an energy storage charging and discharging strategy by reducing a distributed maximum matching gap and reducing an order to break a distributed maximum independent set obstacle algorithm; and based on the distributed control strategy set, the system operation state is monitored in real time, and control parameters are dynamically adjusted by adopting an event triggering mechanism. According to the method, the problems of calculation complexity and communication dependence of traditional centralized control in a large-scale photovoltaic energy storage system are solved.

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

The invention discloses an electric power control method based on a diesel generator, commercial power and photovoltaic grid connection. The method comprises the following steps: acquiring operation data of commercial power, a diesel generator and photovoltaic-energy storage through an energy management system, constructing a multi-target dynamic optimization model, and distributing power by taking the lowest comprehensive operation cost, the highest power supply reliability and the minimum carbon emission as targets; the power analysis and regulation unit adopts a double-loop mechanism of outer-loop Kalman filtering prediction compensation and inner-loop model prediction control, synchronizes the voltage, frequency and phase of the side to be connected with the grid and the power grid side, and smoothly switches the power change rate of each energy source in the process through a self-adaptive sliding mode control strategy; and the grid-connected switching unit intelligently pre-judges the grid-connected switching opportunity by using a long short-term memory (LSTM) network and fuzzy logic fusion model. According to the invention, the energy utilization efficiency and the power supply stability are improved, multi-energy intelligent dynamic regulation and control are realized, the comprehensive operation cost of the system is effectively reduced, and reliable power supply under complex working conditions is ensured.

The invention provides a photovoltaic energy storage inverter power coordination control method based on an adaptive algorithm, and relates to the technical field of data processing, and the method comprises the steps: collecting the output power data of a photovoltaic module, the state data of an energy storage device, and the load demand data of a grid connection point, and carrying out the normalization processing of the data; calculating to obtain an initial power distribution parameter of the current period; respectively calculating a load change trend factor and a power fluctuation trend factor based on the load demand data and the output power data of the historical period, and coupling the load change trend factor and the power fluctuation trend factor to form a trend coupling factor; carrying out self-adaptive repair through a trend coupling factor; combining real-time grid-connected point load demand data with energy storage device state data to generate a target power distribution instruction and an energy storage charging and discharging adjustment instruction, and respectively issuing the instructions to an inverter control unit and an energy storage device control unit; according to the invention, the accuracy of the photovoltaic energy storage inverter power coordination control method is improved.

The invention discloses a distributed photovoltaic and energy storage cooperative power distribution network voltage fluctuation suppression method and system, and relates to the technical field of voltage fluctuation suppression, and the method comprises the following steps: building an inter-node disturbance propagation accessibility matrix based on the real-time operation data of a power distribution network, and recognizing a voltage disturbance path set; constructing a disturbance irreversible structure chart based on the voltage disturbance path set, and identifying a one-way amplification chain; according to historical disturbance data of a unidirectional amplification chain source node, calculating a disturbance excitation probability and generating a disturbance active propagation domain; constructing an energy storage intervention buffer area in the disturbance active propagation domain; in the energy storage intervention buffer area, the reverse blocking capability of energy storage is evaluated by simulating disturbance propagation, and a collaborative strategy activation condition is generated. Through disturbance path simulation evaluation, energy storage redundancy configuration and power consumption are reduced, and the suppression efficiency and adaptability of the system are improved.

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

A system for supplying power to a portable battery pack including a battery enclosed by a wearable and replaceable pouch or skin using at least one solar panel is disclosed, wherein the pouch or skin can be provided in different colors and / or patterns. Further, the pouch or skin can be MOLLE-compatible. The battery comprises a battery element housed between a battery cover and a back plate, wherein the battery element, battery cover, and back plate have a slight curvature or contour. Further, the battery comprises flexible leads.

The invention relates to the technical field of micro-grid control, in particular to a cooperative control method based on optical storage and charging and a micro-grid, and the method comprises the steps: collecting multi-source data in real time; predicting a photovoltaic output prediction value; screening temporary units; determining an energy storage unit; determining a collaborative exception unit; dynamically correcting the power threshold; and executing power adjustment control. According to the method, a self-adaptive closed loop is constructed by organically coupling multi-dimensional real-time parameters of output power, a charge state value, a load demand and a user behavior: a power fluctuation threshold value and a charging request growth rate jointly trigger temporary unit screening, so that quick response to sudden load change is ensured; the charge state value and the queuing duration jointly determine energy storage unit scheduling, and a power generation side and a demand side are balanced; and then, a coordination index is generated through the reconnection frequency and power-load normalization weighting, coordination abnormity is accurately recognized, and the problem that the coordination control response speed is low due to model staticization and single index judgment is effectively solved.

The invention provides a hybrid energy storage optimization method and system considering fluctuation stabilization and energy storage protection, and relates to the technical field of hybrid energy storage optimization. Comprising the steps of calculating hybrid energy storage total power; the total power of the hybrid energy storage is decomposed, a low-frequency component and a high-frequency component are distributed to a lithium battery and a super capacitor in the hybrid energy storage respectively, and primary power distribution is completed; on the basis of primary power distribution, the power of the lithium battery and the power of the super capacitor are adjusted on the basis of a low-amplitude component in low-frequency components, the charging and discharging states of the lithium battery and the super capacitor and the charging and discharging margin of the super capacitor, and the power of the lithium battery is optimized on the basis of fuzzy control; and the power of the lithium battery is corrected based on the grid-connected power fluctuation rate condition, and secondary power distribution of the lithium battery and the super capacitor is completed. According to the invention, the energy storage charging and discharging conversion frequency is reduced, the SOC of the super capacitor and the lithium battery is ensured not to be out of limit, the problem generated by adopting traditional fuzzy control on the super capacitor is avoided, and the grid-connected fluctuation ratio is prevented from being out of limit.

The invention discloses a power system frequency modulation method and system based on flywheel energy storage auxiliary wind power, a flywheel energy storage system is equivalent to a first-order inertia link, an inertia time constant of the flywheel energy storage system is dynamically adjusted, a virtual damping coefficient is optimized in real time in combination with a fuzzy logic controller, and the stability of power grid frequency is remarkably improved. When the frequency of the power grid fluctuates, the flywheel energy storage system can respond quickly, the frequency modulation power close to the rated frequency can be output in an extremely short time, and the steady-state frequency deviation is strictly controlled in an extremely small range. Meanwhile, the fuzzy logic is used for dynamically correcting the power instruction, and the problem of frequency modulation instruction tracking errors caused by wind power output randomness is effectively solved. Besides, after frequency modulation is finished, the damping coefficient is dynamically adjusted through a fuzzy decision mechanism, the flywheel rotating speed recovery time is greatly shortened, secondary frequency disturbance caused by rotating speed lag is avoided, and the recycling efficiency of flywheel energy storage in a continuous frequency modulation scene is ensured.

The invention discloses an intelligent energy storage method and system for a photovoltaic power station, and relates to the technical field of intelligent energy storage, and the method comprises the steps: collecting meteorological data, photovoltaic power station and geographic information data to construct a fusion data set, importing a photovoltaic prediction model, and outputting a photovoltaic prediction power sequence; the method comprises the following steps: acquiring time-of-use electricity price from a power transaction platform, receiving a power fluctuation limit value issued by a scheduling system, acquiring a charge state of a battery pack, namely an energy storage SOC state in real time, adopting a rolling time domain optimization solution model, solving a dual-target model, and outputting an optimal charge and discharge power instruction sequence; the energy storage unit submits an acceptable power range and a unit power quotation; a market clearing algorithm is executed; the quotation of the subject matter and the quotation of the energy storage unit are summarized; and after priority sorting according to prices and accumulative matching, issuing instructions are distributed according to a bid winning proportion, and the issuing instructions are distributed to the physical energy storage unit. And the whole life cycle cost minimization is realized.

The invention relates to an offshore wind power-energy storage-hydrogen production system cooperative control method and device and a medium, and the method comprises the steps: collecting wind power plant operation data, energy storage system data and hydrogen production system data in real time, and obtaining a state vector; the state vector is input into a strategy network, a current action vector is calculated, the strategy network is obtained through training of a double-evaluator reinforcement learning framework, a first evaluator evaluates an economical efficiency target value function, and a second evaluator evaluates a safety target value function; the strategy network outputs a control instruction corresponding to the current action vector, and issues the control instruction to each execution device for adjustment, including adjusting fan operation parameters according to the axial induction factor and the yaw angle; adjusting the electrolytic cell input power according to the electrolytic load power; and controlling the charging and discharging operation of the energy storage system according to the energy storage power. Compared with the prior art, the method has the advantages of high collaboration, high adaptability, safety and the like.

The invention discloses a power distribution area energy storage control and capacity configuration method, system, equipment and medium, and the method comprises the steps: firstly, setting a plurality of different energy storage control strategies according to a preset discharge lower limit and a preset charge upper limit of an energy storage device of a power distribution area in combination with the residual capacity condition of the energy storage device; then, on the basis of time-of-use electricity price data and load data of the power distribution area, according to an energy storage control strategy, an objective function composed of the minimum operation cost of the power distribution area, the maximum photovoltaic consumption rate of the power distribution area and the minimum net load variance of the power distribution area is constructed; solving the objective function through an optimization algorithm to obtain a charging and discharging power vector of the energy storage device; and finally, calculating the optimal configuration capacity of the energy storage device according to the charging and discharging power vector of the energy storage device. According to the invention, the problems of too low photovoltaic consumption rate and too high total cost are solved, and the stability of the power grid is improved.

A system for supplying power to a portable battery pack including a battery enclosed by a wearable and replaceable pouch or skin using at least one solar panel is disclosed, wherein the pouch or skin can be provided in different colors and / or patterns. Further, the pouch or skin can be MOLLE-compatible. The battery comprises a battery element housed between a battery cover and a back plate, wherein the battery element, battery cover, and back plate have a slight curvature or contour. Further, the battery comprises flexible leads.

The invention relates to the technical field of micro-grid control, in particular to a source-grid-load storage and charging integrated control method and system based on a micro-grid, and the method comprises the steps: considering the current SOC, health state and charging and discharging rate of a battery energy storage system, and evaluating the available capacity and charging and discharging capability of the battery energy storage system; according to the predicted charging load curve, the photovoltaic output curve and the energy storage state evaluation result, taking peak load shifting, photovoltaic consumption and charging station power supply guarantee as targets, generating a scheduling strategy by using an optimization algorithm, and determining a power distribution relationship among a photovoltaic system, a battery energy storage system and a charging station in each time period; and executing a scheduling strategy generated by the energy management module through three stages of regulation and control units, wherein the three stages of regulation and control units are respectively used for limiting grid-connected power fluctuation of the micro-grid, optimizing local energy distribution and island switching, regulating active power and reactive power and carrying out harmonic suppression. And stable operation of the micro-grid and stability of electric energy quality are ensured.

The invention discloses a hybrid energy storage optimization configuration method based on a multi-time scale regulation and control demand, and the method comprises the steps: collecting the operation data of a power system, and obtaining the power fluctuation and the frequency deviation of the power system under a short time scale through a preset high-proportion renewable energy power system model; on the basis of power fluctuation and frequency deviation, the regulation and control requirements of the power system are divided according to different time scales, different energy storage modules are correspondingly configured, and a multi-level collaborative energy storage regulation and control structure matched with the time scales is formed; based on the power system model and the mathematical model of each energy storage module, constructing a hierarchical nested optimization model oriented to multiple time scales; and selecting a typical scene from the operation data by adopting a time sequence clustering method, and obtaining the optimal capacity and power configuration of each energy storage module based on a hierarchical nested optimization model, and obtaining a cross-time-scale collaborative operation strategy. The global optimal configuration is realized by establishing a multi-time-scale collaborative hierarchical nested optimization architecture.

An off-grid wind turbine system comprising a wind turbine with an electric generator for generating an initial electric power output. An electrolyzer system with a hydrogen electrolyzer located inside the nacelle or tower of the wind turbine, so as to generate hydrogen by an electrolysis process. An electric converter system serves to convert the initial electric power output into a DC electric power output dedicated for powering the electrolyzer. The produced hydrogen is stored in a hydrogen storage tank.

The invention discloses a dynamic energy storage scheduling method of a modularized photovoltaic system, and relates to the technical field of photovoltaic power generation system operation control, the method comprises the steps that a photovoltaic power generation system is divided into a plurality of modules with autonomous operation capability, each module comprises a photovoltaic power generation unit, an energy storage unit and a local control unit, the local control unit is used for collecting current illumination intensity, battery charge state, temperature, power grid power flow direction and load power data of the module in real time and periodically uploading the parameters to the system central coordination unit; the central coordination unit constructs a nonlinear load prediction model based on module-level load rate change, external temperature sensitivity and day and night periodic characteristics so as to improve the responsiveness to temporary sudden load change; according to the method, the problems of low operation efficiency, non-uniform energy storage utilization rate, inaccurate load prediction and scheduling response lag are solved.

The invention discloses a wind power generation and gravity energy storage combined power supply system and method, and the system comprises a wind power generation unit, a gravity energy storage unit and an intelligent control unit. The gravity energy storage unit is dynamically controlled to store or release energy according to the difference value between the wind power generation real-time power and the threshold value, so that the combined output power is stable. The gravity energy storage unit adopts a symmetrical double-slope supporting tower and double-energy-storage structural design, and bidirectional conversion between electric energy and gravitational potential energy is achieved through a clutch mechanism. And the intelligent control unit dynamically adjusts the floating threshold by combining the predicted wind speed and the historical power fluctuation rate, so that the adaptability of the system to different wind fields is improved. The intermittent problem of wind power generation is solved through cooperative control of power generation and energy storage, the fluctuation amplitude of output power is reduced, peak clipping and valley filling can be achieved through a two-way energy conversion mechanism, energy release and power supply are achieved in the power demand peak period, energy storage is achieved in the valley period, the overall energy efficiency of a power grid is improved, and waste of energy in the power generation peak period is avoided.

The invention discloses a multi-energy system closed-loop prediction control method, system, equipment and medium, and the method comprises the steps: carrying out the decomposition, dimension reduction and nonlinear modeling of the time sequence characteristics and environmental influence factors of photovoltaic output through a photovoltaic power prediction model, and outputting a future multi-period photovoltaic power prediction sequence; establishing a state equation and an output equation, integrating equipment operation constraints, and constructing a hydrogen-containing energy storage state space model; inputting local load power and a future multi-period photovoltaic power prediction sequence into the hydrogen-containing energy storage state space model, and solving an objective function through a rolling optimization algorithm to obtain a future multi-period optimal scheduling scheme; and applying a first hour control instruction of the optimal scheduling scheme to an actual system, and proportionally superposing the deviation between an actual measurement value and a historical prediction value to a photovoltaic power prediction sequence of a next period through a feedback correction item to realize closed-loop control. According to the method, the photovoltaic local consumption rate can be improved, and the power grid fluctuation rate is reduced.