1806 results about "Power regulation" patented technology

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.

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 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 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 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 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.

An active-reactive voltage cooperative control method for multiple reactive compensation devices considering energy storage comprises the steps that 1, simulation analysis is conducted on time sequence voltage fluctuation characteristics of a high-permeability photovoltaic grid-connected system, and dynamic influences of photovoltaic output fluctuation in different time periods on system node voltage are quantitatively evaluated; 2, solving a non-dominated solution set of the model by adopting a multi-target particle swarm optimization algorithm, realizing collaborative optimization and trade-off analysis of multi-dimensional performance indexes, and establishing a reactive power regulation model and an energy storage active power support model; and organically coupling the reactive power regulation model and the energy storage active power support model. By means of the method, high photovoltaic area voltage treatment can be effectively carried out in real time, and the method has high engineering application value and wide popularization prospects.

The invention provides a dynamic power adaptive charging control system and method based on a W algorithm, and relates to the technical field of electric two-wheeled vehicle charging control. The system comprises a battery state sensing module, a charging power standard calculation module, a regulation and control model construction module, a model dynamic optimization module and a deviation early warning and regulation and control module. The battery state sensing module generates battery charging basic data; the charging power standard calculation module calculates a charging operation power standard value; the regulation and control model construction module generates an initial power regulation and control curve; the model dynamic optimization module calculates a self-adaptive charging power regulation and control curve; and the deviation early warning and regulation module realizes self-adaptive regulation of the charging power of the electric two-wheeled vehicle. According to the method, the power grid adaptability correction model is constructed and the regional differentiation parameters are introduced, so that power grid fluctuation is flexibly coped, wide-voltage stable operation is guaranteed, and the adaptability, the safety and the intelligent level of the electric two-wheeled vehicle charging system are comprehensively enhanced.

The invention relates to the technical field of power system stability control, in particular to a new energy station transient voltage and frequency coordination stability control method, which comprises the following steps of: analyzing a transient energy evolution rule of an equivalent synchronous motor and stored energy by constructing an alternating current and direct current hybrid dynamic model and fusing with multi-time scale characteristics; based on dynamic weight matrix optimization and a multi-target coordination control strategy, self-adaptive balance of power distribution is realized; a nonlinear feedback algorithm and a real-time compensation mechanism are designed in combination with the Lyapunov theory, and voltage frequency fluctuation in a disturbance scene is suppressed; establishing a multivariable cooperative control architecture, and dynamically adjusting a power adjustment priority and an inertia time constant through coupling iterative optimization of a source storage cooperative strategy to realize adaptive compensation of a transient energy propagation path; according to the method, the dynamic stability and the anti-interference capability of the new energy station under transient impact are remarkably improved, and safe operation of a high-proportion new energy power grid is guaranteed.

The invention provides a distributed energy storage device group intelligent cooperative control optimization method and system, and relates to the technical field of group intelligence, and the method comprises the steps: obtaining source load fluctuation data, constructing a dynamic defense topological graph with energy storage devices as nodes and electrical coupling relations as edges, recognizing a disturbance propagation path and a node disturbance arrival time sequence through graph convolution operation, and obtaining a distributed energy storage device group intelligent cooperative control optimization model. Obtaining a node disturbance sensitivity quantized value; dividing the energy storage equipment group into a front defense domain and a back-up defense domain based on the quantized value and a preset layering threshold value; reversely deducing a power regulation sequence aiming at the front defense domain to generate an active defense instruction, and generating a following type scheduling instruction aiming at the back-up defense domain; issuing and executing the instruction, collecting topological response data, and jointly updating the edge weight and the propagation coefficient based on the deviation. According to the method, disturbance pre-compensation control is realized through dynamic topology modeling and a layered defense strategy, and the cooperative response efficiency of the energy storage equipment group and the system stability are improved.

The invention relates to the technical field of intelligent power grid and electric vehicle cooperative control, and discloses a plug-and-play and flexible power regulation and control integrated vehicle network interaction cooperative control system, which comprises a protocol adaptive conversion module, a multi-modal data alignment module, a flexible power regulation and control module, a vehicle pile identity authentication module and a power grid state sensing module, and realizing inter-generation vehicle millisecond-level identification and data unified modeling through the protocol middleware. According to the method, the problems of protocol compatibility and data alignment in a plug-and-play scene are solved, and deep coordination between the charging process and the power grid state is realized through flexible power regulation and control and a multi-stage safety mechanism. The system guarantees the non-inductive charging experience of a user, reduces the impact on a power grid to the maximum extent, prolongs the service life of a battery, and improves the energy utilization efficiency.

The invention provides a ship shaft power generation and lithium battery coordinated multi-working-condition energy optimization management system, which is applied to the technical field of ship power systems and energy management and comprises a data acquisition module, an energy optimization processing module and a power regulation and control module, wherein the energy optimization processing module is provided with a prediction unit, a working condition identification unit, a loss evaluation unit and a decision-making unit, the prediction unit is used for predicting a ship load demand in a preset period, the working condition identification unit is used for identifying a ship operation working condition, and the loss evaluation unit is used for determining a life loss factor by combining a prediction result and an energy storage unit state; the decision-making unit generates a regulation and control instruction based on the life loss factor and the state of the power generation unit to realize power distribution of the power generation unit and the energy storage unit; according to the system, multi-working-condition energy consumption requirements of the ship are met, meanwhile, comprehensive optimization of fuel consumption cost and energy storage unit service life loss cost is achieved, the energy utilization rate is increased, the service life of the energy storage unit is prolonged, and the full-life-cycle operation cost of the ship is reduced.

The invention provides a dispatching management system and method for an EMS deep fusion electric ship battery, and relates to the technical field of electric energy management, and the method comprises the steps: building a digital twin based on the state information of the electric ship battery, and obtaining a health attenuation coefficient; acquiring an abnormal fluctuation sequence of the temperature, and performing dynamic boundary division on the health attenuation coefficient through the abnormal fluctuation sequence to obtain a dynamic safety boundary; grading and limiting the output power of the battery according to the dynamic safety boundary to obtain a power regulation and control parameter set, and carrying out joint modeling on the power regulation and control parameter set to obtain an out-of-limit penalty term; performing subnet partition reconstruction on the power grid topological structure to obtain an electrical collaboration graph, and performing multi-target optimization scheduling on the electrical collaboration graph through an out-of-limit penalty term to obtain a scheduling strategy vector; according to the method and the device, dynamic electric energy optimal scheduling based on health perception can be realized, so that the stability of electric ship battery scheduling is improved.

The invention relates to the technical field of building intelligent control and energy saving, and discloses a building equipment intelligent control optimization management system based on a green low-carbon building. The system comprises five subsystems, wherein an environmental parameter sensing subsystem is used for acquiring temperature and humidity gradients, illumination intensity distribution and personnel activity thermodynamic diagram data inside and outside a building through a distributed sensing network to form a multi-dimensional environmental state vector; the equipment operation state acquisition subsystem acquires an operation power curve, an energy efficiency conversion rate curve and an equipment health degree index of heating ventilation air conditioning, illumination and renewable energy equipment in real time; the dynamic load prediction subsystem establishes an energy consumption load space-time distribution prediction model according to historical data time sequence relevance; the control strategy generation subsystem is used for generating an optimized instruction set containing an equipment start-stop time sequence, a power regulation gradient and an energy distribution weight in combination with the current environment vector and a predicted load; the execution terminal adapts the subsystem to convert the instruction into a device compatible signal and calibrate a response delay.

The invention discloses a distribution-micro collaborative operation simulation optimization method, which belongs to the technical field of simulation optimization, and comprises the steps of preprocessing grid-connected point voltage data, tie line power data and communication time delay data, constructing a power distribution network power flow physical network following a Kirchhoff's law, outputting a source load power prediction curve by using a long short-term memory network algorithm, and calculating the distribution-micro collaborative operation according to the source load power prediction curve. And a distribution-micro collaborative simulation optimization model is obtained based on residual error rolling correction tie line impedance parameters, a delay penalty term is set in a target function in combination with the preprocessed communication delay data, a power regulation instruction is obtained by using a particle swarm optimization algorithm, and a dynamic simulation video stream is generated. According to the invention, through rolling correction of the tie line impedance parameters and setting of the delay penalty term positively correlated with the time delay, the problem of control failure caused by physical deviation caused by model parameter solidification and communication time delay accumulation is solved, and the defects of voltage deviation calculation distortion and inaccurate network loss evaluation are eliminated. And the simulation precision and the operation stability of distribution-micro cooperation are improved.

The invention relates to a multi-energy collaborative intelligent micro-grid control method, device and equipment and a medium. According to the method, a micro-grid frequency signal is collected in real time, the change rate of the micro-grid frequency signal is calculated, the inertia requirement of a system is accurately evaluated, the maximum virtual inertia capable of being provided by each unit is dynamically calculated in combination with the physical characteristics and operation constraints of each energy unit, and the system requirement and the unit capacity are dynamically matched through grey correlation analysis to generate an optimal distribution scheme. And then the special control models of all the units are driven to generate differentiated power regulation instructions, and finally power support is cooperatively executed through the power electronic converter, so that accurate matching and efficient cooperation of multi-energy virtual inertia capability are realized, the frequency stability of a high-proportion new energy power grid is remarkably enhanced, and the system performance is improved. The problems of resource allocation mismatch, poor control adaptability and the like in a traditional method are effectively avoided, and the dynamic safety of the system is guaranteed under the complex operation working condition.

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 relates to a multi-modal oscillation suppression method and system for a network construction type power supply grid-connected system, belongs to the technical field of power system control, and solves the problem that multi-modal oscillation of a large-scale inversion type power supply grid-connected system cannot be cooperatively and rapidly suppressed. The method comprises the following steps: when a system generates broadband oscillation, collecting grid-connected point voltage and current signals of each power station to extract a dominant oscillation mode of each power station; constructing a modal coupling matrix based on the dominant oscillation mode to extract modal coupling strength; identifying a key path of oscillation propagation in the dominant oscillation mode, and extracting a path weight and a power station participation degree; calculating the comprehensive power regulation and control weight of each power generation station in multiple modes so as to determine the power regulation quantity; and distributing the power regulation quantity to an energy storage device, a static var generator (SVG) and each power generation station according to oscillation characteristics of different frequency bands so as to cooperatively suppress multi-modal oscillation. The active / reactive oscillation energy is cooperatively adjusted, so that the oscillation energy of each frequency band is effectively suppressed.

An elevator energy-saving control system of a direct feed network relates to the technical field of elevator energy-saving control, and comprises an energy conversion module for converting kinetic energy and gravitational potential energy generated during operation of an elevator car into direct current; the control system module monitors elevator running state data and power grid parameters in real time, judges whether the elevator is in a power generation state or not according to a monitoring result, automatically starts an energy feedback mode and controls starting and stopping of energy feedback and power adjustment; the inversion grid-connected module is used for converting the direct current into alternating current, processing the generated alternating current and feeding back the electric energy in the form of the processed alternating current to a power grid; and the man-machine interaction module is used for receiving data information of the control system in real time and converting the data information into visual display content, so that a worker can master the operation condition of the system in time and deal with abnormal problems. The elevator running energy consumption is remarkably reduced, the running cost is reduced, meanwhile, the service life of equipment is prolonged, the stability of the equipment is improved, and the influence on the environment is reduced.

The invention discloses a fused salt heat storage and Carnot cell combined coal-fired unit peak-load regulation operation method, device and equipment, a medium and a product, and relates to the field of unit peak-load regulation operation. Acquiring information data; based on a power regulation demand prediction model, performing peak regulation demand prediction according to the information data to obtain a prediction result; the power regulation demand prediction model is obtained by adopting a multi-objective optimization model and performing time sequence analysis on a long-short-term memory network model; determining an energy scheduling strategy based on the prediction result; the energy scheduling strategy comprises a heat storage power coordination instruction and a heat release power coordination instruction; and according to the energy scheduling strategy, operation adjustment is conducted on the coal-fired unit, the fused salt heat storage subsystem and the Carnot battery subsystem based on the control system. The invention aims to improve the peak regulation performance of the coal-fired unit.

The invention relates to the technical field of microchip power compensation, and discloses an efficient power compensation method and system based on a microchip. According to the method, power parameter data of the microchip are collected through monitoring equipment, and the data comprehensively reflect the real-time power condition of the microchip. And then the collected power parameter data and a preset power threshold are compared and analyzed, and a corresponding power compensation control signal is generated according to an analysis result so as to realize accurate power regulation and control. And then the fluctuation characteristic of the power compensation control signal is evaluated to obtain a power compensation lag index and a power compensation efficiency index, and the acquisition frequency of the power parameter data and the execution mode of the power compensation control process are respectively adjusted based on the two indexes, so that the compensation efficiency is improved and the system flexibility is enhanced. And finally, the overall stability of the power compensation control process is monitored, and when the stability does not meet a preset condition, a power compensation invalid mark is generated to guarantee stable operation of the system.

The invention discloses an industrial park virtual power plant reactive voltage control method of multi-target multi-agent deep reinforcement learning considering energy storage life, and belongs to the technical field of virtual power plant reactive voltage control methods based on industrial data acquisition. The problem that in the prior art, a traditional industrial park virtual power plant reactive voltage control method is difficult to consider park network loss optimization and energy storage life protection at the same time is solved. According to the method, a multi-objective optimization model including network loss minimization, node voltage deviation minimization and energy storage battery service life maximization is constructed, a virtual power plant is divided through a distributed multi-agent framework, each agent trains multiple strategies in parallel through a multi-objective multi-agent deep reinforcement learning algorithm based on local observation, the Pareto front is approached, and the energy storage battery service life is maximized. High-efficiency control is realized, and each intelligent agent independently generates an energy storage reactive power regulation and active power charging and discharging instruction. The reliability of the energy storage equipment is improved, and the method can be applied to an industrial park active power distribution network scene with high renewable energy source permeation.

The invention discloses a dynamic impedance matching wireless charging power adaptive adjustment system, which comprises a dynamic impedance detection module used for being connected with a wireless charger, monitoring voltage and current of a transmitting end and a receiving end of the wireless charger in real time, and calculating a phase difference to obtain a current impedance value; the control module is used for calculating matching network parameters needing to be adjusted according to the detected current impedance value; the matching network adjusting module is used for adjusting matching network parameters according to an instruction of the control module, so that transmitting end impedance and receiving end impedance are in conjugate matching; the power adjusting module is used for adjusting transmitting power according to the dynamic impedance matching result; a communication module; according to the invention, through cooperation of the dynamic impedance detection module, the control module, the matching network adjustment module, the power adjustment module and the communication module, full-process automation from impedance detection, parameter calculation to dynamic adjustment is realized, and adaptability and efficiency of wireless charging are significantly improved.

The invention discloses a virtual reactive power plant user single-phase asynchronous motor reactive power regulation method, and relates to the technical field of electrical equipment control, and the method comprises the steps: collecting the real-time state data of a key node of a power distribution network, and building a short-term prediction model based on the state data; setting a judgment condition according to a prediction result of the model, generating a preliminary reactive power regulation instruction, and adjusting the priority and the regulation amplitude of the preliminary reactive power regulation instruction in real time based on dynamic updating of a prediction trend; issuing the adjusted reactive power adjustment instruction to a user terminal, and performing cooperative processing based on distributed coordination control to generate a final cooperative adjustment instruction; executing an action of cutting off the split-phase capacitor of the single-phase asynchronous motor according to the coordinated adjustment instruction; according to the invention, the split-phase capacitance of the single-phase asynchronous motor at the user side is regulated and controlled by using the virtual reactive power plant, so that low-cost, quick-response, continuous and accurate reactive power regulation is realized, and the problems of reactive power excess and high voltage of a power grid are effectively solved.

The invention discloses a battery charging and discharging power self-regulation control circuit, which relates to the technical field of battery control, and comprises a power supply module, a micro-control module, a voltage sampling and comparison module, a battery charging and discharging power self-regulation control module, a battery charging and discharging power self-regulation control module, a battery charging and discharging power self-regulation control module and a battery charging and discharging power self-regulation control module, the power regulation module compensates the direct-current electric energy, the battery module stores energy, the power regulation module and the direct-current electric energy are superposed and supply power to the battery module, during the discharging period, according to the voltage comparison condition, the power regulation module carries out voltage compensation processing on the battery module, and the battery module directly supplies power to the discharging module; and the power regulation module performs voltage balance control on the battery module. The battery charging and discharging power self-adjusting control circuit can prolong the service life of the battery, improve the charging and discharging efficiency, reduce the electric energy loss of the power adjusting module, improve the energy utilization rate and provide higher charging voltage.

The invention relates to the technical field of distributed energy and micro-grids, in particular to a distributed energy output high-precision prediction model, which comprises the steps of collecting data and generating a power fluctuation probability envelope; constructing a complementary voltage-stabilizing virtual subgroup with a negative correlation compensation characteristic through a sequential sequence comparison algorithm; based on a power grid agent model and a kernel function SHAP algorithm, quantizing marginal contribution values of residual disturbance power of each subgroup to frequency deviation of the common connection point; performing a non-linear mapping on the contribution value to generate a virtual impedance correction parameter; and finally, through a layered decoupling closed-loop correction architecture, determining predicted power regulation and control vacancy and generating a compensation instruction. According to the method, the complementarity and the disturbance contribution of each heterogeneous power supply are quantified, so that the high-precision prediction of the distributed energy grid-connected stability influence is realized.

The invention discloses a fault ride-through coordination control method for a network construction type wind storage system. The method comprises the following steps: S1, establishing a main circuit topology model of the network construction type wind storage system; s2, considering the influence on the transient stability of the wind storage system in a system fault state by a control method based on a main circuit topology model; s3, establishing a plurality of wind storage system transient stability improvement control strategies; and S4, realizing fault ride-through coordination control of various wind storage system transient stability improvement control strategies in combination with switch control. Through strategies of active power reference value switching, energy storage power adjustment, power angle compensation, voltage amplitude switching and the like, the transient stability and safety of the system are remarkably improved, the problems of fan rotating speed fluctuation, power angle instability, short-circuit current impact and the like are effectively restrained, and the method has important theoretical significance and engineering value.

The invention discloses an energy storage device droop control method and system considering power grid stability, and belongs to the technical field of energy storage devices, and the method comprises the steps: collecting power grid state information, and obtaining the current power grid operation state data; constructing a power grid stability evaluation function based on the scoring function of the power grid operation state data; dynamically adjusting a droop coefficient through a mapping function based on a power grid stability evaluation function; and calculating the power regulation quantity of the energy storage device through the droop coefficient to obtain the output power of the energy storage device so as to regulate the frequency of the power grid, and carrying out monitoring and feedback. According to the method, the power regulation capability can be enhanced when the power grid disturbance is aggravated, and the flexible response is kept when the power grid operates stably, so that the frequency modulation precision and stability of the energy storage system are effectively improved, the problems of power jump, power grid system overregulation or energy storage overload are effectively inhibited, and the stability of the control process and the equipment safety are guaranteed.

The invention relates to an alternating-current trunk line or an alternating-current power distribution network, in particular to a method for improving the stability of a wind power system through combined control of network construction type energy storage and a nine-switch UPQC. The method comprises the following steps: firstly, proposing an active regulation and inertial support control method based on a virtual synchronous machine mechanism for network construction type energy storage; and secondly, by constructing a coordination control framework, dynamic response complementation of the energy storage system and the UPQC under disturbance is realized, so that the overall frequency stability and voltage supporting capability of the system are improved. And finally, building a system model in Matlab / Simulink, setting three typical working conditions of wind power fluctuation, frequency disturbance and serious voltage drop, and carrying out scheme validity verification. Simulation results show that the method can effectively stabilize the wind power output fluctuation, enhance the frequency and voltage support capability, and significantly improve the stability of a wind power system.

The invention belongs to the field of offshore wind power, and discloses a single-pile offshore wind turbine power regulation and load relief method, which comprises the following steps of: constructing a thrust system model of wind to a rotor and a tower; constructing a dual-mass transmission system model of the wind turbine generator; constructing a tower top front-back displacement model and a pile soil front-back displacement model; constructing a rotor speed tracking error model based on an adjustment error method; constructing a tracking error model of the change rate of the front-back displacement of the tower top; constructing an optimal control strategy based on an infinite vision field optimal cost function; and designing an optimal pitch control scheme based on a robust adaptive dynamic programming algorithm. According to the design of the RADP-based propeller pitch controller provided by the invention, the MOWT model does not need to be completely known, so that the calculation cost of the controller is reduced, and the calculation efficiency is improved.