2740 results about "Power regulation" patented technology

The invention relates to a V2G-based alternating current charging power adjusting method and device. The method comprises the following steps: carrying out multi-scale data acquisition and preprocessing on a V2G alternating current charging system to obtain a standardized system state data set; constructing a system dynamic model comprising a power grid voltage characteristic and a charging power characteristic; carrying out decomposition to obtain a power output mapping relation calculation, and obtaining a power modulation control parameter; establishing a fast and slow time scale coordination control framework, and designing a power regulation agent and a voltage regulation agent to obtain a coordination control strategy; checking a charging power limit value constraint, a voltage limit value constraint and a power factor constraint to obtain a constraint violation judgment result, and executing constraint projection calculation to obtain a target control instruction; and controlling a power conversion circuit of the charging pile to execute power regulation operation. According to the invention, a hierarchical control structure is adopted, the control complexity of the system is reduced, and the robustness and the adaptive ability of the control strategy are improved.

The invention discloses a regional energy internet hierarchical control method considering flexible loads, which comprises the following steps of: constructing a global layer, dividing a regional energy internet into a plurality of electrically strongly coupled sub-regions by adopting a dynamic partitioning algorithm, aggregating equivalent adjustable capacities of the flexible loads in the sub-regions, and performing rolling optimization in an hour-level time scale, an improved Benders decomposition algorithm is adopted to accelerate solving and generate a partition-level power regulation instruction; constructing a regional layer, designing a thermodynamic-economic hybrid constraint model according to flexible load physical characteristics and user behavior elasticity, introducing a user comfort recovery time constraint and elastic electricity price response function, and decomposing an adjustment instruction issued by the global layer to each flexible load cluster in a minute-level time scale by adopting a parallel ADMM optimization algorithm; and constructing a load layer, constructing a millisecond-level adjustable load priority switching mechanism based on FPGA hardware acceleration and finite-state machine logic, calculating a load adjustable power boundary in real time, and dynamically adjusting a response queue in combination with system frequency deviation.

The invention discloses an electromagnetic heating and heat preservation system for a wind power blade girder plate pultrusion die, and relates to the technical field of thermal field regulation and control, comprising the following steps: activating an electromagnetic coil array to generate an alternating magnetic field, synchronously starting a heat preservation layer device, and triggering a gradient heating mode when the temperature of the die reaches a preset threshold value; a mold temperature field is monitored in real time, the power of an electromagnetic coil and parameters of a heat preservation layer are dynamically adjusted, a target temperature gradient is established, an electromagnetic heating device and a mechanical traction device are linked in the pultrusion process, and heat dissipation control is triggered according to the material flowing state; and after heat dissipation control is completed, the main power source is cut off, the mode is switched to the waste heat recovery mode, mold waste heat is guided into the energy storage device, and the cooling rate is controlled. According to the method, accurate mode switching of electromagnetic heating from uniform temperature rise to gradient heating is achieved through cooperation of magnetic field activation and a gradient triggering mechanism, and the temperature gradient establishment speed and the morphological stability are effectively improved in cooperation with power regulation and control partition differentiation power instruction and thermal insulation layer parameter dynamic matching.

The invention discloses a game reinforcement learning-based reactive power dispatching method for an electric vehicle to participate in a power distribution network, and the method comprises the steps: collecting node voltage, line current, electric vehicle charging and discharging states and topological information, and constructing graph attention embedding; generating an initial reactive power regulation action in the multi-agent game reinforcement learning framework, and shaping and updating a strategy gradient through double rewards; the improved particle swarm is initialized according to the updating strategy gradient, and a self-adaptive inertia coefficient is set; iteratively searching according to the node voltage sensitivity, the line reactive margin and the expected convergence step number to obtain an optimized particle swarm; the particle speed is mapped to a main strategy network through online cooperative training, the inertia coefficient is synchronously adjusted, a cooperative optimization strategy is output, a reactive power dispatching instruction is generated, and the algorithm is updated in a closed-loop mode according to real-time feedback. According to the invention, rapid and cooperative reactive dynamic scheduling of an electric vehicle group is realized, and the voltage stability and the electric energy quality are remarkably improved.

Disclosed in the present invention are a voltage control method and system for clusters of a power distribution network having a high proportion of photovoltaics. The method comprises: acquiring parameters of a power distribution network, and constructing a comprehensive electrical distance by means of adjustable active power and reactive power reserves of each node in the parameters of the power distribution network; forming an improved weight matrix by means of distributed photovoltaic reactive power and active power supporting capacities, a reactive power sensitivity matrix and an active power sensitivity matrix, and obtaining an optimal reactive power cluster and active power cluster division result by a community algorithm by means of a node coupling degree index in each cluster and the comprehensive electrical distance; and selecting, by means of a clustering algorithm on the basis of the division result, a key node in each cluster to act, to improve the cluster voltage regulation and control capability. Starting from the relationship between active power sensitivity and reactive power sensitivity, and considering the impact of different changes on other nodes, efficient utilization of the reactive power regulation capability of a grid-connected PV inverter can be achieved, the complexity of control strategy computation is greatly reduced, and the situation where there are too many adjustable distributed photovoltaics in clusters is avoided.

The invention discloses a distributed wind set virtual inertia active support control method suitable for a weak power grid, and the method comprises the steps: dynamically adjusting the inertia support strength according to the frequency disturbance of a power grid through adaptive virtual inertia adjustment; multi-mode cooperative control is adopted, and an operation mode is switched according to the frequency deviation and the change rate so as to provide an optimal response; by means of dynamic damping compensation, frequency oscillation is suppressed in combination with multiple factors and an optimization algorithm, and system damping is improved; multi-time-scale cooperative control is implemented, and inertia support, power adjustment and rotating speed recovery are coordinated at a millisecond level, a second level and a minute level; and rotor kinetic energy graded release is adopted, kinetic energy release is accurately controlled according to the frequency drop degree, and sudden rotation speed drop is avoided. In addition, additional frequency damping control is introduced to enhance suppression of frequency fluctuation. The method can significantly improve the response speed and adaptability of the wind turbine generator to the frequency fluctuation of the weak power grid, ensures the frequency stability of the power grid, and provides key technical support for stable grid connection of wind power in the weak power grid.

The invention provides a power grid frequency modulation power energy coordination control method and system based on a super capacitor, and relates to the technical field of power grid frequency modulation, and the method comprises the steps: carrying out the time-frequency analysis of a collected power grid frequency signal, obtaining a frequency disturbance characteristic value, and determining power control data through combining with an electrical parameter value of a super capacitor group; and performing nonlinear programming calculation based on the power control data to obtain a power distribution sequence, dividing the power distribution sequence into a quick response section, a dynamic transition section and a steady state maintenance section according to a preset threshold value, and solving a control value by adopting an augmented Lagrange equation, recursive least square operation and a Lyapunov function respectively. Obtaining a power control instruction; and inputting a power control instruction into the disturbance observer, calculating a dynamic error value, constructing a nonsingular terminal equation, and outputting a power regulation signal in combination with recursive minimum entropy calculation and a superhelix algorithm.

The invention discloses a DC bus voltage fluctuation suppression method of a renewable energy hydrogen production system, and relates to the technical field of renewable energy electrolysis hydrogen production. The method comprises the following steps: collecting system operation parameters in real time; bus voltage disturbance power is estimated based on a disturbance observer, and frequency decomposition is carried out; fusing the ARIMA model and the LSTM model to predict the load power, and calculating a prediction deviation; dynamically setting upper and lower limits of a bus voltage control interval according to the predicted deviation and the operation state; a multi-objective optimization function is constructed, bus voltage disturbance power, prediction deviation and a control limit value are comprehensively considered, and power regulation instructions of battery energy storage, a fuel cell and an electrolytic cell are solved; and executing power regulation control to realize bus voltage stabilization. The method can improve the grading response capability of voltage disturbance, the prediction accuracy of load power change, the adaptability of the control boundary and the overall operation stability of the system, and is suitable for the electric energy quality control of the hydrogen production system in a multi-source fluctuation scene.

The invention discloses a micro-grid anti-countercurrent control method and system based on multi-objective optimization, and the method comprises the steps: generating a dynamic load prediction result according to the power grid side voltage, user side load power and energy storage system charge state data collected by an energy management system in real time; based on the dynamic load prediction result, obtaining a countercurrent risk quantitative index; generating a corresponding dynamic anti-reflux threshold curve according to the reflux risk quantitative index; the dynamic anti-reflux threshold curve is corrected through a real-time collaborative verification module, and an anti-disturbance optimization threshold is generated; and converting the anti-disturbance optimization threshold value into a PCS power regulation and control instruction, synchronously displaying a threshold value execution state and reverse feed early warning information on an energy management interface, and triggering adaptive power clamping protection when detecting that the voltage is out of limit or the power is reverse. According to the embodiment of the invention, the intelligent level of countercurrent prevention and control of the micro-grid can be improved, and safe and stable operation of the grid is guaranteed.

The invention relates to a self-adaptive pressure regulation vacuum pump closed-loop control system and method. The system comprises a model building module which is used for acquiring real-time data flow of a vacuum pump and building a nonlinear dynamic model to obtain a pressure-flow-power feature mapping relation; the predictive analysis module calculates a pressure-flow predictive value based on the relationship and compares the pressure-flow predictive value with the real-time power data for analysis. And generating a parameter adjustment instruction once the deviation value exceeds a preset threshold value. And the control scheme generation module corrects the control parameters according to the parameter adjustment instruction and generates an optimized power adjustment scheme. And if the data is abnormal, generating a state update value. And the control scheme updating module fuses the state updating value and the pressure-flow prediction value to obtain an optimized model parameter so as to adjust a weight coefficient of an adaptive control strategy and generate a control scheme. The system effectively improves the accuracy of vacuum pump pressure control, greatly enhances the ability of the system to deal with abnormal conditions and equipment performance changes, and ensures long-term stable operation of the vacuum pump.

The invention relates to the technical field of new energy power systems, and discloses an energy storage coordination system and control method based on meteorological prediction and multi-energy complementation, and the system comprises a power generation end module which carries out the dynamic adjustment according to a power adjustment instruction of a power generation end; the meteorological prediction and data acquisition module is used for acquiring meteorological data in a future time period in real time and sending the meteorological data to the intelligent control and scheduling platform; the energy storage end module sends data including lithium battery SOC and hydrogen storage tank pressure to the intelligent control and scheduling platform and performs charging and discharging according to an energy storage end charging and discharging priority strategy; and the intelligent control and scheduling platform receives the electricity price data of the weather prediction and data acquisition module, the energy storage end module and the power grid in real time, generates a power generation end power regulation instruction and an energy storage end charging and discharging priority strategy, and meanwhile, improves the income and maximizes the hydrogen energy use proportion through electricity price peak-valley arbitrage and green electricity transaction premium. The power grid stability and the energy utilization rate are greatly improved, the energy storage life is prolonged, and the investment payback period is shortened.

The invention relates to the technical field of power management, and provides a power distribution method based on BMS power control and related equipment thereof. The method comprises the following steps of: performing multi-mode synchronous acquisition and self-adaptive preprocessing on detected battery pack global state data to obtain a battery state tensor, and performing unsteady-state signal decomposition and time-space feature extraction on a received load power demand signal to obtain a power component matrix; performing multi-constraint dynamic planning on the battery state tensor and the power component matrix to obtain an initial power distribution strategy, performing dynamic correction in combination with a deep reinforcement learning model to obtain an adaptive distribution strategy, and performing multi-layer circuit equalization optimization on the adaptive distribution strategy to obtain a power regulation instruction set; and finally, performing multi-physics field coupling verification and fault-tolerant reconstruction on the power regulation instruction set to obtain an execution signal sequence. According to the invention, through data fusion, demand prediction, strategy optimization and deep learning, power distribution is accurately regulated and controlled according to the battery state and the load power demand.

The invention discloses a power distribution network voltage control method based on distributed photovoltaic active-reactive cooperation, and the method comprises the steps: analyzing the influence of reactive / active injection on voltage stability through building a sensitivity matrix, deducing a critical control gain constraint condition, and guaranteeing the static stability of the voltage of a power distribution network; a photovoltaic inverter active / reactive cooperative control general model suitable for different scenes is constructed based on an intra-day scheduling and real-time control two-stage framework, and control curve parameters of each node photovoltaic inverter are optimized by taking minimization of network loss cost, active reduction cost, inverter voltage regulation cost and voltage deviation as targets in the intra-day scheduling stage; in the real-time control stage, active power reduction and reactive power regulation are dynamically coordinated based on an optimal control curve, reactive power margin is preferentially utilized to suppress voltage rise, and power flow distribution is directly regulated through active power reduction when reactive power capacity is saturated. According to the method, the safety and economy of the power grid are considered, and theoretical support and a practical solution are provided for voltage control of the high-permeability photovoltaic power distribution network.

The invention relates to a dynamic power regulation and control method and system for an electric vehicle charging pile, and the method comprises the following steps: S1, based on the real-time operation data of a charging pile cluster, employing a multi-source information fusion technology, collecting a power grid voltage fluctuation signal through a Hall sensor disposed at a charging pile end, and combining with the battery charge state data transmitted by a vehicle-mounted BMS, and eliminating noise interference by using an improved Kalman filtering algorithm, and realizing multi-dimensional data fusion by using a D-S evidence theory to generate a multi-source working condition feature set. The method has the advantages that the power grid voltage fluctuation signal and the battery charge state data are integrated through the multi-source information fusion technology, the improved Kalman filtering algorithm is adopted to eliminate noise interference, multi-dimensional data fusion is achieved in combination with the D-S evidence theory, the integrity and reliability of working condition feature extraction are remarkably improved, and the working condition feature extraction efficiency is improved. And the LSTM-ARIMA hybrid prediction model is utilized to synchronously process the nonlinear features and the periodic rules.

The invention relates to the technical field of power system frequency, and discloses a thermal power generating unit-energy storage coupling frequency modulation system for improving power grid frequency stability, which comprises a thermal power generating unit module, an energy storage system module, an energy management and distribution control module and a communication and monitoring module. The thermal power generating unit provides a frequency stabilization basis through inertia response and power regulation, and the energy storage system compensates frequency deviation in a quick response mode. And the energy management module dynamically adjusts the power distribution proportion between the thermal power generating unit and the energy storage system based on the optimized objective function to realize efficient collaborative frequency modulation. The output power and the state of charge of the energy storage system are controlled by constraint conditions. The communication and monitoring module collects power grid frequency, load fluctuation and energy storage state data in real time, generates frequency modulation control signals and issues the frequency modulation control signals to each module. By combining the stability of the thermal power generating unit and the quick response characteristic of the energy storage system, the response speed and the adjustment precision of power grid frequency adjustment are remarkably improved, and meanwhile the frequency adjustment cost is reduced.

The invention is suitable for the technical field of power grid control, and provides a virtual power plant cooperative control scheduling method and system, and the method comprises the following steps: constructing a multi-dimensional resource library, each resource node in the multi-dimensional resource library corresponding to real-time adjustable power, power adjustment cost, response delay time, a carbon emission coefficient and a resource availability coefficient; establishing a global optimization model at the cloud, wherein the global optimization model fuses economy, environmental benefits and system stability; solving the global optimization model by adopting an improved non-dominated sorting genetic algorithm to obtain an optimal scheduling strategy, and issuing the optimal scheduling strategy to a control center and an edge terminal; and determining a real-time state of the resource node based on the edge terminal, and adjusting the optimal scheduling strategy according to the real-time state. According to the method, the response precision and the system stability of the virtual power plant are remarkably improved by constructing the global optimization model and dynamic cooperative control and adopting the improved non-dominated sorting genetic algorithm for solving.

The invention relates to the technical field of network load prediction, and particularly discloses a power supply energy saving system and method based on a load prediction intelligent dormancy strategy, and the method comprises the steps: collecting base station service load and power supply power data, and employing a neural network to accurately fit the nonlinear relation between the two for adjusting the power; constructing a multi-mode service load prediction model, generating a power supply power adjustment instruction in advance, and adjusting the power in time when the load prediction deviation exceeds a threshold value; frequent power fluctuation is avoided through a dynamic threshold mechanism based on hysteresis comparison; a sleep and wake-up strategy and a buffer mechanism are established to ensure that the state of the power supply is switched only when the load changes continuously, so that the switching accuracy and stability are improved; self-adaptive sleep duration and progressive wake-up adjustment are introduced, so that smooth transition and intelligent energy conservation of power supply operation are realized; the method can improve the energy efficiency of the power supply and reduce the energy consumption.

The invention relates to the technical field of generator control, and particularly discloses an SVG static var generator control method and system, and the method comprises the steps: constructing a reactive-voltage sensitivity matrix containing a node sensitivity weight based on the real-time measurement data of a power grid, and obtaining a node sensitivity matrix; a dynamic sorting strategy of device priority grading is generated, a distributed compensation priority queue of all devices is obtained, and the devices comprise an SVG cluster and a photovoltaic inverter cluster; executing reactive power distribution under a capacity constraint condition based on the distributed compensation priority queue, and generating a target reactive power compensation amount with the capacity constraint condition; generating a hierarchical coordination control instruction of the SVG and the inverter according to the target reactive compensation amount, and obtaining a hierarchical control instruction set; executing the distributed cooperative compensation driven by the hierarchical control instruction set, and completing the dynamic regulation of the power grid voltage; the reactive power regulation capability of different devices in a power grid can be fully utilized, the accuracy and response speed of reactive power distribution are improved, and resource waste and excessive compensation are avoided.

The invention relates to the technical field of communication base station energy-saving control, and discloses an energy-saving optimization control method and system for a communication base station. The method comprises the following steps: collecting and preprocessing traffic energy consumption data of a communication base station to obtain standardized characteristics; inputting the features into a double-flow space-time convolutional network, and carrying out parallel calculation through time and space branches to predict a load; performing hierarchical quantitative pruning on the network, and distributing bit width according to the influence degree to obtain a compression structure; and processing the real-time data based on the compression network, and generating an energy-saving control strategy for radio frequency resource configuration and power regulation. Based on accurate load prediction and differentiated resource scheduling strategies, the optimal balance between energy saving and service quality is realized, the problems of passive response and coarse-grained control in a traditional method are effectively solved, and the energy saving effect is maximized on the premise of ensuring communication quality.

The invention relates to the technical field of power plant data processing, in particular to a virtual power plant integrated management system, which comprises a data acquisition module for acquiring voltage fluctuation characteristics and power climbing rate parameters of energy equipment in real time; the equipment fingerprint database construction module generates an equipment fingerprint code comprising a dynamic response time-lag coefficient and an adjustment margin quantized value; the dynamic clustering module is used for dividing simulation sub-models of regional topology constraints based on the geographic position of the equipment and a power regulation threshold value; the multi-time scale prediction module is used for generating source load prediction data by fusing meteorological parameters through a space-time diagram convolutional network; the digital twin simulation module outputs an energy storage charging and discharging threshold value and a demand response priority strategy; and the cross-domain collaboration module adopts a double-chain block chain architecture to realize security verification and data integrity binding of federated learning feature parameters. According to the invention, through equipment characteristic digital modeling, regional co-simulation and multi-energy flow coupling regulation and control, the resource aggregation precision and response real-time performance in a new energy strong fluctuation scene are improved.

The invention discloses a radio frequency power adjusting system, an adjusting method thereof and semiconductor process equipment. The adjusting system comprises an interference monitoring module which obtains a time domain signal of radio frequency power in a reaction cavity and obtains interference data based on frequency domain characteristics of the time domain signal; the adaptive control module takes the interference data as a state input variable, updates an action output variable by learning an optimal strategy, and determines an optimal action output variable based on an objective function of interference suppression and energy consumption, and the action output variable comprises a frequency regulation variable, an amplitude regulation variable and a pulse width regulation variable; and the feedback adjusting module is used for dynamically adjusting a plurality of process parameters in the reaction cavity based on the optimal action output variable so as to enable the process parameters to reach the target process parameter range. According to the invention, the radio frequency power density in the reaction cavity can be adaptively adjusted, and the optimal dynamic balance between interference suppression and energy consumption is realized, so that the radio frequency interference suppression effect, the process stability and the equipment efficiency are improved.

The invention provides a self-adaptive low-voltage ride-through control method for a network-building type converter considering virtual impedance, and the method comprises the steps: defining a reactive power adjustment coefficient and an active power adjustment coefficient, obtaining a power parameter, building an active-reactive power self-adaptive low-voltage ride-through control strategy formula when the influence of the virtual impedance is not considered, and carrying out the self-adaptive low-voltage ride-through control of the network-building type converter. The relation between the virtual impedance and the output reactive power is analyzed through the reactive power of the network-forming converter control system after the virtual impedance link is switched in, so that the enlightenment that the virtual impedance needs to be introduced to carry out linear correction on the reactive power regulation coefficient is obtained; a corrected value function can be obtained after linear correction is carried out on reactive adjustment parameters through virtual impedance, the corrected value function is finally substituted into a strategy formula, an active-reactive self-adaptive low-voltage ride-through control strategy formula considering the influence of the virtual impedance is obtained, the transient power angle stability of a grid-forming type converter system can be enhanced, and the stability of the grid-forming type converter system is improved. And meanwhile, the problem of over-current of the converter under large disturbance is solved.

The invention relates to an optimization method based on a distributed solar photovoltaic power generation control system. The method comprises the following steps: collecting generating capacity data, voltage data, current data and solar radiation data; inputting a photovoltaic multi-mode deep learning prediction model for processing, and generating an active power adjustment strategy and a reactive power adjustment strategy; generating a control instruction, performing hierarchical security constraint check on the control instruction, and generating a remote control instruction and a local control instruction; performing hierarchical reinforcement learning control and power optimization adjustment on the inverters in the plurality of control groups to obtain a group total output value; performing real-time monitoring to generate operation parameter data; and calculating the active power qualified rate, the control response time, the control precision and the system volatility, and carrying out multi-target optimization on the adjustment dead zone range, the control gain and the response time constant to obtain a target power distribution scheme. According to the invention, reasonable load distribution of each inverter is ensured, and the operation stability and reliability of the system are improved.

The invention provides a voltage control method based on dynamic cluster division of a high-permeability photovoltaic power distribution network, and the method comprises the steps: carrying out the Newton-Raphson method load flow calculation of a power distribution network power system based on the topological structure data of the power distribution network, line parameters, the access position of a photovoltaic inverter and energy storage equipment, and equipment parameter information, and constructing a comprehensive modular function; based on the comprehensive modularization function, according to the load capacity of each moment, taking the average load capacity as a standard, utilizing an improved artificial hummingbird algorithm to dynamically divide time segments of the clusters and selecting dominant nodes of each cluster; based on the dominant node, taking the minimum node voltage deviation and the minimum system loss as objective functions, and constructing a second-order cone programming model when a preset constraint condition is satisfied; and solving the second-order cone programming model by using a solver CPLEX to obtain the reactive power regulation quantity of the distributed photovoltaic inverter and the active power regulation quantity of the energy storage equipment, thereby improving the power supply reliability and the electric energy quality of the photovoltaic power distribution network.

The invention discloses a new energy voltage ride-through parameter optimization method considering polymorphic voltage stability constraint, a storage medium and equipment, and belongs to the technical field of power system safety and stability improvement. In order to solve the problem that an existing new energy voltage ride-through parameter optimization method is only suitable for a single fault scene and only aims at a voltage stable form to optimize a new energy voltage ride-through parameter, the invention provides a new energy voltage ride-through parameter optimization method. Based on the dynamic characteristics of the new energy during the power grid fault period, the new energy general control model is established so as to determine the dominant control parameters influencing the dynamic characteristics of the new energy during the high / low voltage penetration period, the influence of the dominant control parameters on the voltage stability under different faults is considered, and the voltage regulation capability and the power regulation cost of the new energy are considered. A new energy voltage ride-through parameter optimization model considering polymorphic voltage stability constraints is established, and the optimization model is solved by adopting a particle swarm optimization algorithm. The method is used for voltage ride-through parameter optimization of new energy.

The invention discloses a grid-connected inverter control method based on second-order linear active disturbance rejection, and particularly relates to the field of grid-connected inverter control. Voltage and frequency error signals between the output side of the inverter and the power grid are obtained, a pre-synchronization control model is constructed, and voltage amplitude and frequency synchronization is achieved; a second-order linear active-disturbance-rejection controller is introduced in the frequency synchronization control process, an extended state observer is adopted to estimate the output frequency, the frequency change rate and a disturbance term, and a state error feedback control law is combined to generate a frequency regulation control quantity, so that accurate frequency control is realized; after grid connection, a dual-channel LADRC power regulation controller is constructed, and decoupling tracking control is carried out on active power and reactive power; meanwhile, on the basis of fast Fourier transform processing as a stable grid-connected state criterion, the method has the advantages of being high in control precision, high in anti-interference capability, good in current waveform quality, high in adaptability and the like, and is suitable for various grid-connected application scenes.

The invention discloses a multi-mode switching control method suitable for a hydrogen-electricity combined energy storage system, and the method comprises the steps: carrying out the coupling of a plurality of control units through a DC bus, and obtaining a system architecture; according to the operation mode of the system, coordinating the power output of the energy storage unit by using a dynamic collaborative optimization method based on a virtual synchronous machine technology and a variable droop coefficient, and introducing a dynamic energy distribution model and a dynamic energy distribution constraint to obtain a power balance framework of the energy storage unit; performing collaborative optimization and joint optimization on a plurality of energy storage units in the power balance framework by using the optimization model based on the cooperative game and the dynamic power regulation model to obtain a joint dynamic balance mechanism; and iteratively optimizing and improving the combined dynamic balance mechanism by using a distributed dynamic optimization algorithm to obtain the hydrogen-electricity combined energy storage system. The invention relates to a hydrogen-electricity combined energy storage control technology, and solves the technical problems that an existing hydrogen-electricity combined energy storage system is difficult to coordinate and insufficient in dynamic response in the multi-mode switching process.

The invention relates to the technical field of energy storage cooperative control, and discloses an improved energy storage converter grid following control algorithm, which comprises the following steps of: 1, extracting positive sequence and negative sequence components of three-phase voltage of a power grid through a double-sequence decoupling phase-locked loop, and acquiring a positive sequence axis component signal by adopting forward rotation coordinate transformation; and 2, when frequency locking is carried out based on the positive sequence axis component signal, extracting a voltage amplitude corresponding to the positive sequence axis component signal, and inputting the voltage amplitude to a feed-forward passivation module. An active power regulation technical scheme based on a frequency deviation threshold value is adopted, the technical effect of simulating the primary frequency modulation characteristic of a network-forming converter is achieved by detecting the power grid frequency deviation in real time and generating an active power compensation signal, and the defect that traditional network-following control lacks frequency active supporting capacity is overcome. And the converter can spontaneously increase the active power to stabilize the power grid frequency when the power grid frequency drops.

The invention discloses a micro-grid automatic power regulation and control method, and relates to the technical field of micro-grid power regulation and control and resource management. In order to solve the defects of poor new energy consumption capability, high distributed resource management difficulty, poor power grid regulation and control flexibility, poor resource cooperation effect and poor power and load prediction accuracy of an existing micro-grid power regulation and control method, grid-connected and off-grid flexible switching of a power grid A and a power grid B is realized by constructing an integrated construction framework. And multi-source data are integrated, and new energy power generation and load demands are intelligently predicted through data center management. And during grid connection, the distribution and dispatching integrated system determines power dispatching, and the micro-grid management system B makes a dispatching plan. And during off-grid, power is supplied according to the user priority. And in the grid-connected and off-grid mode, power distribution, load regulation and control and resource optimization configuration are carried out, and distributed resources are regulated and controlled in real time through the coordination controller, so that stable operation of the power grid is ensured. The method is mainly used for flexibly regulating and controlling the micro-grid.

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.