641 results about "Wind power system" patented technology

The invention discloses a stability analysis method of a network tracking / constructing hybrid station based on an impedance model, and relates to a modeling and stability evaluation technology of a wind power plant grid-connected system. The method comprises the following steps: firstly, respectively establishing sequence impedance models of a following network type direct-driven fan and a construction network type direct-driven fan based on a harmonic linearization method, and verifying the accuracy of the established models in different frequency bands by combining an impedance sweep frequency method; secondly, on the basis of considering the influence of line impedance, deducing to form an impedance network structure of a hybrid wind power plant grid-connected system, and constructing a stability judgment condition suitable for system analysis; and finally, based on the established impedance stability criterion, identifying possible oscillation risks of the system in subsynchronous and supersynchronous frequency bands. The method is suitable for wind power system stability analysis in various hybrid access scenes, and provides theoretical basis and technical support for subsequent system parameter setting, control strategy optimization and oscillation suppression measures.

The invention relates to the technical field of wind power generation. The impeller imbalance detection method based on multi-source data fusion comprises the steps that operation state data of a draught fan unit and environment data of corresponding time are obtained, and a multi-source data set is obtained; preprocessing the multi-source data set to obtain a preprocessed data set; feature parameters in the preprocessed data set are extracted, data fusion is carried out, and a multi-source feature fusion vector is constructed; according to the multi-source feature fusion vector, constructing a time sequence prediction model based on a gating circulation unit, and predicting a theoretical vibration baseline value under the current working condition in real time; and calculating a deviation degree between an actual vibration value and a predicted baseline through residual analysis, dynamically adjusting a detection threshold, and triggering imbalance early warning when the deviation degree exceeds the threshold. The problems that the accuracy of a detection result of a traditional impeller imbalance detection method is affected by various factors, misjudgment and missed judgment are prone to occurring, and the requirement of a modern wind power generation system for high-precision fault detection cannot be met are solved.

The invention discloses a wind power generation system operation optimization method based on intelligent control, and the method comprises the following steps: S1, collecting the real-time data during the operation of a wind power generation system, including the wind speed, the wind direction, the rotating speed of a generator, the output power, and the environment temperature; s2, constructing a performance model of the wind power generation system according to the real-time data; s3, based on the performance model, adjusting the operation parameters of the generator in real time to optimize the power generation efficiency of the system; and S4, when detecting that the system is abnormal, automatically triggering a fault diagnosis module, generating a fault processing suggestion and executing an optimization strategy. Through real-time data acquisition, performance model construction, operation parameter dynamic adjustment and intelligent fault diagnosis, the problems that a traditional wind power generation system is low in efficiency and not timely in fault response are solved, and the system has the advantages of dynamically optimizing power generation efficiency, timely processing system abnormity and improving operation stability.

The present disclosure provides a method and device for calculating fault measurement impedance of a hybrid-connected grid-following and grid-forming wind power system. The method includes: obtaining characteristics of the grid-following and grid-forming converters and a corresponding low voltage ride-through control strategy; establishing an equivalent circuit under a corresponding fault state; conducting a simplified analysis on the wind power system to obtain an equivalent network diagram; obtaining a sub-circuit diagram of each power source excitation acting alone; obtaining short-circuit currents on both sides of the corresponding system and a grid connection point voltage; superimposing to obtain total short-circuit current on both sides of the wind power system and total grid connection point voltage; and obtaining a measurement impedance at a protection installation location on the new energy source side. The method can accurately calculate the measurement impedance value at the protection installation location after the wind power system has fault.

The invention discloses an analysis and design method and system for a floating type wind power foundation structure, and the method comprises the steps: selecting a part of section according to a preliminary design scheme of a floating type wind power foundation, and dividing the section into a plurality of floating body subareas; performing multi-body frequency domain hydrodynamic analysis on the floating body partition to obtain a multi-body hydrodynamic coefficient; calculating a rigidity coefficient at a part of the cross section; a wind turbine generator, a tower drum, a mooring system and the floating type wind power foundation are built into a multi-body coupling model, floating type wind power system time domain coupling analysis is conducted, internal force and stress of part of sections are calculated, the strength of the part of sections is checked, and the design scheme of the floating type wind power foundation is determined. According to the method, on the basis of floating body partition of the floating type foundation, the floating type foundation serves as a multi-body system composed of the multiple rigid bodies, the internal force at the connecting cross section of the multiple rigid bodies is obtained during time domain coupling analysis, analysis and design of the floating type wind power foundation structure are improved, and the design precision and the safety coefficient of the floating type wind power foundation structure are improved.

The invention relates to a water-drop-shaped captive balloon high-altitude wind power generation system. The water-drop-shaped captive balloon and kite cloth carried by the water-drop-shaped captive balloon are used for generating lift force to drive a ground power generator to generate power. The lift force generation mechanism is that the windward side and the wind resistance are increased by adjusting the pitch angles of the aerostat and the bearing kite cloth, and the wind resistance is converted into cable tension to drive power generation. A V-shaped pulley expansion mode is adopted to uniformly distribute tension of main and auxiliary cables, so that bag damage caused by non-uniform stress in a posture adjusting process is avoided; the captive balloon is provided with an attitude controller, communicates with a ground control system through wireless data transmission, adjusts the take-up and pay-off speed of a main cable and an auxiliary cable to control the pitching angle to achieve lift force control, and greatly improves the power generation efficiency. The main cable power output winch drives a generator to generate electricity through a one-way bearing, and the input end is connected with a motor through a clutch to achieve cable recovery. The backpack kite cloth can be controlled to open and close through a small winch to increase and decrease wind resistance; lift force and wind resistance control is optimized, the power generation efficiency is improved, safety is enhanced, operation is simplified, and maintenance is convenient.

The invention discloses an umbrella ladder type land-based high-altitude wind power generation system optimal working point determining method and device, equipment, a medium and a product, and relates to the field of land-based wind power generation. The method comprises the following steps: in a ground coordinate system, respectively constructing a polar coordinate system of an umbrella body and a wind-facing coordinate system of the umbrella body; based on the constructed polar coordinate system and the wind-facing coordinate system, establishing a dynamic model of an umbrella ladder system in the umbrella ladder type land-based high-altitude wind power generation system; determining a cable output mechanical power model according to the kinetic model; and a wind speed-rope speed relation model in the optimal operation state is obtained through deduction in combination with a simulation test auxiliary theory, so that the optimal working point is determined, and the rope releasing speed in the rising process of the umbrella ladder system in the umbrella ladder type land-based high-altitude wind power generation system is controlled according to the optimal working point. According to the method, the operation parameter data in the optimal operation state can be determined, so that the umbrella ladder type land-based high-altitude wind power generation system works in the optimal operation state.

The invention relates to the technical field of new energy power generation monitoring, in particular to a new energy wind power system fault detection method, system and device based on multi-parameter fusion and a medium. The method comprises the following steps: acquiring various operating parameters such as wind speed, wind direction, generator speed, temperature, voltage and current of a wind power system in real time, and performing feature extraction on the operating parameters to obtain key features related to a fault; analyzing the key features based on a deep learning algorithm, and judging the fault type of the wind power system; and outputting a fault diagnosis result in a visual mode, and sending the fault diagnosis result to a control center for remote monitoring and fault early warning. The technical problems that fault detection of a traditional wind power system is poor in real-time performance, not high in accuracy, low in intelligent degree and the like are solved, and reliable guarantee is provided for safe and stable operation of the wind power system.

The present disclosure provides a fault measurement impedance calculation method and device for a hybrid grid-following / grid-forming wind power system. The method comprises: acquiring characteristics of a grid-following converter and a grid-forming converter, and corresponding low-voltage ride-through control strategies; establishing an equivalent circuit corresponding to a fault state; performing simplified analysis on a hybrid wind power system to obtain an equivalent network diagram; obtaining a branch circuit diagram under individual action of each power excitation; obtaining short-circuit currents and grid-connected point voltages on two sides of the system corresponding to the individual action of each power excitation; performing superimposition to obtain a total short-circuit current and a total grid-connected point voltage at the two sides of the hybrid wind power system; and obtaining a measurement impedance at a protection installation point on a new energy side. In the method, a measurement impedance value at a protection installation point of a hybrid wind power system after a fault occurs can be accurately calculated, so that the setting calculation of distance protection is ensured, so as to accurately reflect fault characteristic information of a hybrid AC system, thereby providing a basis for the distance protection applicability research of the hybrid wind power system, and thus ensuring the safe and stable operation of new energy systems.

The invention provides a short-term wind power prediction method for dynamic time sequence fusion of multi-source heterogeneous data, which comprises the following steps: reading and preprocessing multi-source data, and extracting time sequence characteristics; constructing a uniform feature representation space by applying an adversarial hash generator, and performing disturbance immune training and projection diversity regularization processing; the physical law and data distribution characteristics of the wind power system are integrated into the enhanced Hash code set, constraint projection and distribution calibration are carried out, a heterogeneous relation graph is constructed based on the processed Hash codes, and correction is carried out by using historical similar condition data; and performing short-term wind power prediction on the dynamic fusion relation graph by applying GCN. According to the method, the prediction precision and robustness are remarkably improved, and particularly, the prediction error is reduced by about 50% under the extreme meteorological condition.

This invention relates to a method and system for adaptive reclosing of single-phase AC transmission lines in wind power systems. The invention utilizes single-ended electrical quantity to determine the type of fault. After a fault occurs, a signal acquisition device is used to sample the voltage of the fault phase. The obtained voltage is subjected to short-time Fourier transform to extract the amplitude of the fundamental frequency voltage component, and then processed with differential amplification to construct a fault nature identification criterion. Combined with a sliding time window for fault identification, if it is identified as a permanent fault, the reclosing device is locked out; if it is identified as a transient fault, the fault disappearance time is calculated to determine the reclosing time and output the closing signal. This invention is designed for adaptive reclosing after a circuit breaker trips in wind power AC transmission lines.

The invention discloses a wind power generation system. The system comprises a ground device; the floating device comprises an adjusting air floating piece and a first annular air floating piece, the adjusting air floating piece is movably connected with the ground device, the first annular air floating piece is connected with the adjusting air floating piece, and a through duct is defined by the inner wall of the first annular air floating piece; the wind power generation device is arranged in the duct; and the position of the gravity center of the adjusting air floating piece in the extending direction of the duct is adjustable. According to the wind power generation system, the influence of airflow disturbance, temperature change and buoyancy lift gas leakage on the floating device can be reduced, the phenomenon that the pitching posture change amplitude is large is reduced, particularly, the included angle between the wind receiving face of the blade of the wind power generation device and the airflow direction is closer to the optimal value, the effective wind energy area flowing through the blade is increased, and the wind power generation efficiency is improved. And the fluctuation of the wind energy yield along with the posture is reduced, so that the wind energy utilization efficiency and the power generation output power are improved.

The invention discloses a draught fan and a blade icing fault diagnosis method and device thereof, a storage medium and a computer program product, and the method comprises the steps: obtaining the operation data of a draught fan from an SCADA system of a wind power generation system, sequentially carrying out the preprocessing and feature engineering processing, obtaining the feature variables of the draught fan, and dividing a training set and a test set as a sample; optimizing the neural network model by using an HO algorithm to obtain an optimized neural network model; training the optimized neural network model by using the training set to obtain a trained neural network model; evaluating the training neural network model by using the test set to obtain an evaluation result; and correcting the training neural network model according to an evaluation result to obtain a corrected neural network model, and recording the corrected neural network model as a blade icing fault diagnosis model of the fan. According to the scheme, neural network training is carried out based on the data acquired by the SCADA system, the fan blade icing fault diagnosis model is obtained, the cost is low, and the detection precision is high.

The invention discloses a wind power system composite oscillation suppression strategy and system based on a static synchronous compensator, and the strategy comprises the steps: firstly constructing a sequence impedance model of a GFM-STATCOM and an equivalent wind turbine generator (EWTG) based on a wind power output system containing the GFM-STATCOM; combining the impedance contribution degree beta, analyzing the interaction between the two, and determining the oscillation risk dominant factor of the sub / super-synchronous frequency band; and finally, performing frequency-band suppression: aiming at the problem of negative damping dominance of the subsynchronous frequency band GFM-STATCOM, adopting a control parameter optimization strategy based on parameter sensitivity, and reducing a reactive loop integral coefficient by increasing virtual resistance so as to reduce a negative damping range. In order to solve the problem of negative damping leading of a super-synchronous frequency band EWTG, a virtual admittance control strategy based on voltage feedforward is adopted to reduce the output impedance amplitude of a GFM-STATCOM, the leading position of positive damping of the GFM-STATCOM is enhanced, and then the negative damping of the system is eliminated. According to the invention, precise suppression of composite oscillation is realized, and the stability of a wind power sending system under a weak power grid is improved.

The invention discloses a wind power inertia analysis method considering fan inertia support, and relates to the technical field of wind power system control, and the method comprises the following steps: collecting dynamic response data of a target generator set under a preset disturbance condition, and building a double-loop dynamic model based on the dynamic response data; performing closed-loop coupling on the double-loop dynamic model and a preset power grid model, and constructing a unit-power grid joint dynamic simulation model; based on the joint dynamic simulation model, acquiring a multi-dimensional inertia response characteristic matrix; based on the inertia response characteristic matrix, obtaining a contribution value of a virtual inertia control layer to power grid frequency support; and dynamically adjusting control parameters of a virtual inertia controller in the target generator set according to the quantized contribution value. According to the method, the response characteristics of the wind turbine generator under different disturbances are simulated through the double-loop dynamic model and unit-power grid joint simulation, the inertia response characteristics are analyzed based on real-time data, the capability of efficiently and accurately adjusting the virtual inertia control layer is achieved, and the stability of the power grid is enhanced.

The invention discloses a wind power generation device and system, and the device comprises a main bag body which extends in the front-back direction, and the peripheral surface of the main bag body is a rotary surface; the annular wing is arranged on the radial outer side of the main bag body in a sleeving mode, the annular wing and the main bag body are spaced, and an airflow channel is formed between the inner wall of the annular wing and the outer wall of the main bag body; the airflow channel is divided into a plurality of air channels through components, the air channels are arranged in the circumferential direction of the main bag body, and fan blades are arranged in at least part of the air channels. By means of the coaxial layout of the main bag body and the annular wing and the combination of division of an airflow channel by a component, efficient capture and energy conversion of wind energy are achieved. Compared with a traditional floating power generation device, the wind sweeping area of the fan blades can be remarkably reduced under the same power generation power, the economical efficiency of the wind power generation device is improved, and the technical feasibility of stepping towards a higher altitude and a higher wind energy density area is achieved.

The invention relates to the field of wind power generation control, and particularly discloses a cooperative control analysis system and method of a distributed wind power generation system. The artificial intelligence technology based on the deep learning field is used for calculating wind intensity values of a plurality of preset time points in a preset time period of the wind power plant, wind frequency values of the plurality of preset time points in the preset time period and wind frequency values of the plurality of preset time points in the preset time period. And performing feature extraction and coding on the wind speed values at the plurality of preset time points in the preset time period and the wind direction values at the plurality of preset time points in the preset time period to obtain a classification result of the type of the wind driven generator which is suitable for running. Therefore, wind energy can be effectively utilized by intelligently selecting the type of the wind driven generator which runs properly, and the stability and reliability of power generation of the wind power plant are improved.

The invention discloses a wind power plant inertia damping adaptive regulation and control method and system fused with a deep Q network, and belongs to the technical field of power systems. The method comprises the following steps: establishing a doubly-fed wind turbine generator, a converter mathematical model and an interaction model of a wind power system connected to a power grid, and analyzing the grid-connected stability of the wind power system; the dynamic response characteristic of providing inertia support by the VSG system under different conditions is researched, and the primary frequency modulation capability is improved; a depth Q network is adopted to select rotational inertia and a damping coefficient, a damping inertia adaptive control strategy is improved, cooperation of inertia support and frequency response capability improvement of a wind turbine generator and continuous and smooth adjustment of active power is realized, the stability of a power grid is improved, and the operation performance of a wind power plant is optimized. According to the method, dynamic optimal matching of inertia response, primary frequency modulation and the running state of a unit is achieved, auxiliary services are provided, meanwhile, the running safety and service life of a draught fan are guaranteed, and smooth and impact-free adjustment of active power is achieved.

The invention discloses a wind power generation system control method and system based on an improved recurrent neural network (RNN), and belongs to the field of wind power generation system control. The method comprises the following steps: training an improved RNN model by adopting a training data set, and carrying out forward propagation on an input vector to obtain gain data; quantizing a loss value between the gain parameter and an ideal gain parameter, constructing a loss function according to the loss value, obtaining a weight gradient of each layer by using a gradient back propagation algorithm, updating a network weight according to the weight gradient and in combination with a momentum gradient descent algorithm, applying amplitude constraint to a recursive weight, and performing iterative training to obtain an ideal gain parameter. A trained RNN network model is obtained; obtaining a gain parameter of the wind power generation system according to the trained RNN network model, and controlling the operation state of the wind power generation system according to the gain parameter; according to the method, PI controller self-adaption is achieved by introducing the recurrent neural network, the system response time, static errors and overshoot can be remarkably reduced, and therefore the system performance is improved.

The invention discloses an operation control method for a wind power generation system, and relates to the technical field of operation control, and the method comprises the steps: obtaining the historical operation data of a wind power generation system in a target sea area, taking an offshore environment factor as an interference factor, and coupling the time-space parameters of ocean turbulence intensity, wave load and salt spray corrosion rate; establishing a fan-marine environment digital twinborn body; operation data is acquired in real time, synchronous mapping and dynamic updating of the digital twin are realized, and a state prediction model is established in combination with historical operation characteristics; taking the maximum power generation efficiency and the minimum mechanical load as a multi-objective optimization function, and introducing a model prediction controller to obtain an optimal control sequence of the wind power generation system in a future time domain of each control period; and selecting a first control instruction in the optimal control sequence, issuing the first control instruction to a physical fan torque controller and a variable pitch system in real time, realizing rolling optimization of the wind power generation system, and obtaining a self-adaptive operation control scheme of the wind power generation system. The power generation benefit of the whole life cycle is improved.

The invention discloses a wind power converter open-circuit fault robustness diagnosis method considering wind speed fluctuation. The method comprises the following steps: establishing three groups of typical equivalent wind speed data at the height of a hub, and randomly selecting one group of typical equivalent wind speed data for modeling; obtaining a three-phase current signal through simulation and experiment, and carrying out real-time amplitude normalization on the three-phase current signal; continuously sampling the preprocessed three-phase current data by using a sliding window, converting time sequence data into image data by using a Markov transfer field, and finally combining to form a whole data set; cleaning and disrupting a data set, dividing the data set into a training set and a verification set according to a proportion, carrying out synchronous training based on an improved GRU-ResCNN-Atnn combined neural network, and storing a trained model; and selecting the remaining two groups of equivalent wind speed data to generate a test data set, evaluating model performance and finely adjusting parameters, and determining an optimal diagnosis model. In the actual operation of the unit, the abnormal state of the converter power tube is monitored and diagnosed in real time through the model.

The invention relates to the field of wind power systems, in particular to an energy efficiency dynamic optimization method and system of a wind power hydrogen production coupling system. The method comprises the following steps: acquiring real-time operation data of a wind power plant, including wind speed, generated power and equipment state information; based on the real-time operation data, a dynamic energy efficiency model of the wind power hydrogen production system is constructed through a data fusion algorithm; predicting energy efficiency performance of the wind power hydrogen production system under different operation conditions according to the dynamic energy efficiency model; based on the prediction result, a multi-objective optimization algorithm is adopted to generate an optimal operation strategy, and the optimal operation strategy comprises start-stop control of hydrogen production equipment, a power distribution proportion and charge-discharge scheduling of an energy storage system; and issuing the optimal operation strategy to a control unit of the wind power hydrogen production system to realize dynamic optimization of energy efficiency. The problems of high data fusion difficulty and insufficient energy efficiency model dynamics in the prior art are solved.

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 discloses an electricity-hydrogen hybrid energy storage direct-current micro-grid coordination control method based on bus voltage layering. The method comprises the following steps that 1, a mathematical model of an electricity-hydrogen hybrid energy storage direct-current micro-grid system is built, and a wind power generation system model, an electrochemical energy storage system model and a hydrogen energy storage system model are built; 2, dividing operation conditions for the system based on the bus voltage fluctuation range; 3, droop control and constant pressure control based on a fuzzy algorithm are adopted by the hydrogen energy storage system; 4, the electrochemical energy storage system adopts similar virtual synchronous machine control and constant voltage value control; according to the electricity-hydrogen hybrid energy storage direct-current micro-grid coordination control method based on bus voltage layering, the bus voltage of the direct-current micro-grid is kept stable under the source load fluctuation condition, good dynamic performance is achieved, and the problem of over-charging and over-discharging of a hydrogen energy storage system is effectively solved.

The invention discloses an energy storage capacity configuration method considering new energy island hydrogen production under a low-output working condition, and the method comprises the following steps: taking the maximum daily net income value of a wind and light storage combined hydrogen production system as a target, and proposing a target function; obtaining the real-time power of the wind driven generator and the real-time photovoltaic output power; constructing an electrolytic cell output model under the non-constant operation current; establishing constraint conditions for the model; and analyzing operation characteristics of a wind power system and a photovoltaic system, and simulating under a new energy low output condition according to the constraint condition to obtain an output simulation result of the wind-solar coupling hydrogen production system within one day. By supplementing the constraint conditions of the extreme working conditions in the model, the unbalanced risk of power supply in the extreme scene can be effectively reduced, and the reliability of stable operation of the power system is improved.

The invention relates to the technical field of relay protection, in particular to a three-phase self-adaptive reclosing method and system for a wind power transmission line. The method comprises the following steps: when a fault is detected, collecting a secondary side voltage signal of a target fault phase of the wind power system; determining a fault phase voltage envelope value according to the peak value of the secondary side voltage signal; calculating energy in a plurality of time windows according to the fault phase voltage envelope value; sequentially calculating the energy ratio between the energy of the jth (j = 2, 3, 4,...) time window and the energy of the first time window; if the value of the energy ratio of at least three continuous time windows in the maximum discrimination time limit is greater than 1, determining a reclosing moment so as to output a circuit breaker closing signal after the reclosing moment is reached; otherwise, judging that the fault type is a permanent fault, and not outputting the circuit breaker closing signal. The objective of the invention is to solve the problem of how to identify the fault type of a wind power system before reclosing of a circuit breaker.

The method aims at solving the problems that in a wind power generation system, due to modeling errors of a prediction model in model prediction independent variable pitch control, the load of a blade root of a fan is too large, and output power is unstable. On the basis of model predictive control (MPC) independent variable pitch control, a model predictive independent variable pitch control method integrating deep deterministic policy gradient algorithm (DDPG) reinforcement learning compensation is provided, so that the modeling error of an MPC predictive model is reduced, the load reduction effect is improved, and the stability of output power is enhanced. And a DDPG compensator is designed, so that an intelligent agent continuously learns through a trial-and-error and feedback mechanism, thereby dynamically compensating a modeling error and improving the load reduction performance of MPC independent variable pitch control. According to the invention, the output power of the fan can be more stable, and the fluctuation of blade root load can be effectively reduced, so that the service life of the fan is prolonged, and the operation reliability of the system is improved.

The invention relates to the field of wind power generation system management, in particular to a wind driven generator and compressed air energy storage energy management system dynamically matched with multiple wind conditions, and dynamic response is achieved by arranging a main storage unit and an auxiliary storage unit. In order to improve efficiency, the auxiliary storage unit is generally in a dormant state, and abnormal wind conditions possibly occurring in a future time period are predicted in a rolling mode by obtaining meteorological prediction data in real time. And once the abnormal wind conditions such as gust, turbulent flow and abnormal wind power decline possibly occur, the auxiliary storage unit is started immediately, and compressed air in the auxiliary storage unit is preheated. When the abnormal wind condition comes, the main storage unit and the auxiliary storage unit with opposite working states can be used for quickly responding to the power fluctuation of the wind driven generator caused by the abnormal wind condition, so that the fluctuation of grid-connected power is avoided.

The invention discloses a power grid parameter self-adaptive detection method suitable for a voltage distortion working condition of a wind power generation system. The method comprises the steps of 1, initializing a voltage estimation value according to priori knowledge of power grid voltage; step 2, sampling through a sensor to obtain a power grid voltage containing harmonic waves and direct current components; 3, calculating an estimation error according to the power grid voltage sampling value; 4, designing a self-adaptive observer, and estimating an intermediate variable; 5, updating the voltage estimation value according to the intermediate variable obtained in the step 4; step 6, estimating the power grid voltage of the harmonic component and the direct current component of the voltage by using the intermediate variable obtained in the step 4; and step 7, repeating the step 2 to the step 6, continuously updating the parameter estimation value, and obtaining the real-time parameter of the power grid voltage. According to the invention, when the voltage of the power grid is distorted, the voltage parameter can still be accurately detected, the harmonic and direct current components are separated and extracted under the condition of no steady-state error, and the safe and stable operation of a power system is ensured.

The invention discloses a power distribution control method suitable for a wind storage combined system, and the method comprises the steps: obtaining a power balance parameter, the charge state of a battery and the charge state of a supercapacitor according to the system operation parameters of the wind storage combined system in the operation process, and obtaining the charge state of the supercapacitor according to the power balance parameter; the method comprises the following steps: determining a power balance relationship of the wind storage combined system, further determining an operation mode of the wind storage combined system according to an operation mode selected by the wind storage combined system, obtaining reference currents of a battery and a supercapacitor in a corresponding operation mode, and determining the power balance of the wind storage combined system according to the reference currents of the battery and the supercapacitor. And performing power distribution control on the wind storage combined system according to a preset power distribution control strategy. The residual electric quantity of the super capacitor is introduced as a new constraint, and the residual electric quantity and the residual electric quantity of the battery system jointly determine power distribution control, so that the hybrid energy storage system is protected while stable operation of the wind power generation system is ensured.