2337 results about "Wind power generation" patented technology

A method, system, and device for wind speed prediction and layout optimization in wind power generation are provided. The method includes: obtaining a basic wind resource dataset of a target region; constructing a physics-informed neural network model based on the basic wind resource dataset; obtaining wind speeds data at a specific location in a velocity field based on the physics-informed neural networks and constructing a training dataset; training the physics-informed neural network model based on the training dataset; reconstructing a wind speed distribution within the velocity field and predicting wind speeds for a next time period with a wind farm using the trained physics-informed neural network model; and optimizing a layout of a wind turbine cluster based on a reconstructed wind speed distribution within the velocity field. The present application reconstructs a two-dimensional velocity field of the wind farm by training the PINN and enables accurate ultra-short-term wind speed prediction.

The invention discloses a dynamic monitoring method and system for settlement and inclination of a tower drum of a wind generating set, and relates to the technical field of safety monitoring of wind power generation infrastructure, the method comprises the following steps: synchronously collecting inclination data and positioning data of each monitoring point, and carrying out space-time alignment to obtain a fusion data set; decoupling the dynamic elastic response of the tower drum and the steady-state deformation of the foundation from the fused data through frequency domain analysis, and further calculating the overall inclination rate, the settlement amount and the non-uniform settlement rate of the tower drum; performing safety assessment based on the calculated parameters and a preset safety threshold, and determining a basic safety state and a risk mode; and finally, generating graded early warning information and decision information including risk positioning and trend prediction according to an evaluation result. Through the above mode, the method achieves the precise separation and monitoring of the dynamic deformation characteristics of the tower drum, improves the accuracy of safety evaluation and the timeliness of early warning, and provides an effective data support for the operation and maintenance decision of a wind generating set.

The present application relates to the technical field of wind power generation, and discloses a control method and apparatus for a grid-forming doubly-fed wind turbine generator, a generator, and a medium. In embodiments of the present application, a current reference value of a grid connection point is determined on the basis of measurement parameters of the grid connection point in combination with an internal potential parameter of a grid-forming doubly-fed wind turbine generator and a virtual impedance reference value, a voltage reference value of a grid-side converter is further determined on the basis of the current reference value of the grid connection point, and the grid-side converter is modulated on the basis of the voltage reference value, thereby implementing closed-loop control of the grid-side converter, such that a difference between an output voltage value and the voltage reference value of the grid-side converter is less than a preset threshold.

The invention discloses a blade bolt state monitoring system and method based on an acoustic emission technology in the technical field of state monitoring of wind power generation equipment. The method comprises the following steps: acquiring acoustic emission signal data of a blade bolt connection area acquired by an acoustic emission sensor array; sequentially carrying out preprocessing and feature extraction processing on the basis of the acoustic emission signal data, and then calculating a wavelet packet energy entropy value; judging whether a triggering condition of multi-sensor data fusion weighting judgment is met or not based on the wavelet packet energy entropy value; when any triggering condition is met, it is judged that the state of the bolt is abnormal, and after comprehensive state recognition is conducted through multi-sensor data fusion weighted judgment and modal acoustic emission wave velocity correction positioning, early warning information including the damage type, the severity degree and position information is output; when the triggering condition is not met, it is judged that the bolt state is normal, and circulating monitoring continues. According to the invention, accurate evaluation and early warning of the blade bolt state are realized through signal acquisition, processing, analysis and early warning.

The invention discloses a laser radar-assisted wind power generation wind shear modeling method, and relates to the technical field of wind shear modeling, and the method comprises the steps: collecting the wind speed measurement data of a laser radar at a plurality of heights in a target fan region, and constructing a measurement volume integral operator matrix; constructing a unit induction field correction model based on large eddy simulation in combination with a gradient boosting tree; coupling the measurement volume integral operator with the unit induction field correction model, and obtaining a high-precision wind speed vertical section and a corresponding wind shear parameter through inversion; on the basis of the high-precision wind speed vertical section and the corresponding wind shear parameters, physical constraints are fused, a wind shear model is generated, and uncertainty evaluation is carried out; according to the wind shear modeling method, the problems that the measurement error of the laser radar is difficult to correct, the wind shear modeling lacks the physical constraint and the result credibility cannot be quantified are solved by constructing the volume measurement integral operator and the unit induction field correction model for coupling inversion and fusing the physical constraint and the Bayesian uncertainty evaluation method.

The invention discloses a wind power generation device and a wind power generation control method.The wind power generation device comprises a supporting column, a sensor and a wind power generation mechanism, the wind power generation mechanism comprises a generator and a fan blade set, the wind power generation device further comprises a speed reduction mechanism, the speed reduction mechanism is electrically connected with a control system, and the sensor is electrically connected with the control system; when the sensor detects that the external wind speed reaches the first preset value, the control system controls the speed reduction mechanism to blow air to the fan blade set, speed reduction is conducted through blowing, a braking speed reduction structure does not need to be additionally installed between the blades and the generator, and therefore mechanical abrasion and maintenance cost are reduced; a complicated mechanical braking speed reduction structure is not arranged, so that the design of the wind driven generator is simpler, the weight is lighter, and the installation and the maintenance are more convenient; and mechanical parts are reduced, so that the reliability of the whole system is improved, potential fault points are reduced, and the service life of the wind driven generator is prolonged.

The invention relates to the technical field of wind power generation, in particular to a wind turbine generator deformation vibration monitoring device based on millimeter wave radar. The core function module comprises a benchmark sensing radar, a blade monitoring radar, a reference beacon, an inertial measurement unit, a data synchronization and acquisition unit and a signal processing unit; a reference beacon fixed on a substrate is detected through a reference sensing radar, an absolute motion vector A of the reference sensing radar is solved, then the absolute motion vector A is converted into an absolute motion vector B of a blade monitoring radar, then data C measured by an IMU (Inertial Measurement Unit) is converted into data D of the blade monitoring radar in a coordinate system of the blade monitoring radar, and the blade monitoring radar can be used for monitoring the blade. The absolute motion vector E of the blade monitoring radar is fused and extracted through an extended Kalman filter, and is finally used for compensating original data of blade measurement by the blade monitoring radar, so that the influence of cabin motion on deformation vibration monitoring is eliminated.

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 belongs to the technical field of wind power generation, and particularly relates to a fault diagnosis and early warning method and system for a wind power plant, and the method comprises the steps: collecting the state data of a plurality of physical fields through a plurality of types of sensor arrays disposed at key parts of a fan; performing preprocessing and feature extraction on the data to obtain high-dimensional feature data; driving the field-level digital twinborn model to perform real-time simulation based on the high-dimensional feature data, and determining an initial fault recognition result and severity by comparing a simulation predicted value with actual sensing data and combining with an unsupervised anomaly detection algorithm; a diagnosis result is calibrated through multi-modal high-dimensional feature data fusion; predicting the remaining useful life of the key component based on the fault severity and the evolution trend thereof, and generating a collaborative operation and maintenance decision by using a multi-objective optimization algorithm; and an operation and maintenance decision is automatically executed through a closed-loop feedback execution mechanism. According to the invention, the accuracy of fault diagnosis and early warning of the wind power plant is improved.

The invention discloses a fan blade monitoring system and method based on multi-modal data fusion analysis, and belongs to the technical field of wind power generation. The method comprises the steps that multi-modal characteristic data of a fan blade in operation are acquired; inputting the multi-modal feature data into a pre-constructed multi-modal feature fusion anomaly detection model, a damage factor quantitative calculation model and a health trend prediction model, and respectively performing comprehensive anomaly detection, comprehensive damage detection and health degree prediction on the operation state of the fan blade; based on calculation results of comprehensive anomaly detection, comprehensive damage detection and health degree prediction, comparing the calculation results with a corresponding normal state threshold range; and triggering early warning when any calculation result deviates from the normal state threshold range. According to the method, the multi-modal feature information in the operation of the fan blade is obtained, and the deep learning and machine learning algorithms are combined, so that the early fault under the complex operation condition is effectively identified, and the intelligent operation and maintenance requirements of a modern wind power plant are met.

The invention discloses a wind generating set transmission chain fatigue load prediction method and system considering sandstorm characteristics, and belongs to the technical field of wind power generation and structure fatigue prediction. According to the method, a wind speed time sequence capable of representing sandstorm evolution characteristics is obtained and serves as external physical excitation to be input into a wind-machine-electricity coupling state space model, and a dynamic torque time sequence of a transmission chain low-speed shaft is obtained through calculation; on the basis, a load spectrum is generated by adopting a rain flow counting method, and the accumulated fatigue damage degree corresponding to the sandstorm event is calculated in combination with the Miner linear accumulated damage criterion and the S-N curve of the low-speed shaft material; and further comparing the damage degree with a preset threshold value, and when the damage degree exceeds the threshold value, automatically generating a preventive active load reduction control strategy aiming at the sandstorm, thereby realizing a closed loop of prediction and control. According to the method, the influence of extreme non-stable wind conditions such as sandstorm and the like on the fatigue damage of the transmission chain can be quantitatively evaluated, and technical support is provided for safe operation and predictive maintenance of a wind turbine generator in extreme weather.

The invention discloses a wind turbine generator whole life cycle fault prediction method and device, relates to the technical field of wind power generation, and aims to improve the fault prediction accuracy of a wind turbine generator whole life cycle. According to the technical scheme, the method comprises the steps of collecting multi-modal original data corresponding to each core component of the wind turbine generator, and performing single-modal feature extraction on the multi-modal original data to obtain a standardized feature set; performing deep fusion on the standardized feature set to obtain a fusion feature vector; based on the fusion feature vector, determining a fault identification result and a component health index corresponding to each core component; converting the component health index of each core component into an initial damage degree, and correspondingly inputting the initial damage degree into a pre-constructed hybrid degradation model of each core component to obtain a final damage degree of each core component; calculating the residual life of each core component based on the final damage degree of each core component; and according to the residual life of each core component and the fault identification result, generating graded early warning information corresponding to the wind turbine generator.

The invention relates to the technical field of wind power generation, and particularly discloses a train-mounted ducted airflow coupling wind energy recovery power generation system and method. The train-mounted ducted airflow coupling wind energy recovery power generation system comprises N ducted windmills which are sequentially connected through connecting assemblies; the supporting assemblies are in one-to-one correspondence with the ducted windmills; the supporting assembly is used for supporting the ducted windmill and can achieve rotation and turning of the ducted windmill. The energy storage devices are in one-to-one correspondence with the ducted windmills, and the energy storage devices are connected with generators in the ducted windmills through cables; the connecting assembly comprises a first fixing part, a connecting section and a second fixing part; the first fixing part is connected with the outlet end of the ducted windmill, the second fixing part is connected with the inlet end of the ducted windmill, and the two ends of the connecting section are detachably connected with the first fixing part and the second fixing part respectively. The multiple ducted windmills are connected in series and installed on the train, the ducted windmills can rapidly turn around based on different driving directions, and the ducted windmills can be used for train power generation.

The invention belongs to the technical field of wind power generation, and relates to a fan tower reliability evaluation method and system, electronic equipment and a medium, and the method comprises the steps: obtaining a weather fatigue accumulated damage coefficient according to different weather data information; obtaining a load coefficient based on the load stress and a preset allowable stress; the inclination is collected in real time through an inclination angle sensor, and according to the inclination and a preset inclination threshold value, an inclination coefficient is obtained through normalization processing; obtaining the service time and the design life of the fan tower, and obtaining a life attenuation coefficient based on the service time and the design life; and obtaining the reliability according to the weather fatigue accumulated damage coefficient, the load coefficient, the inclination coefficient, the life attenuation coefficient, a preset weather fatigue accumulated damage weight, a load weight, an inclination weight and a life attenuation weight. According to the method, the reliability is obtained through the weather fatigue accumulated damage coefficient, the load coefficient, the inclination coefficient and the life attenuation coefficient, and the problem of low reliability evaluation accuracy of the existing fan tower is solved.

The invention provides a method for constructing a digital twinborn body of a wind turbine generator, and belongs to the technical field of wind power generation, and the method comprises the steps: constructing a refined mechanism model, converting a historical meteorological data sequence into a physical field parameter sequence, inputting the physical field parameter sequence into the refined mechanism model, and outputting a simulation output sequence; acquiring a simulation output sequence and an actual operation output sequence of the wind turbine generator, and calculating a derivative dynamic time warping distance between the simulation output sequence and the actual operation output sequence; sparsification processing is carried out on parameter vectors of the refined mechanism model, and a key parameter subset influencing the derivative dynamic time warping distance is screened out; taking a minimum derivative dynamic time warping distance as a target function, and adopting a moss optimization algorithm to carry out optimization solution on the key parameter subset to obtain an optimal parameter combination; and backfilling the optimal parameter combination into corresponding parameters of the constructed refined mechanism model to obtain the digital twin model of the wind turbine generator. And the model precision is improved.

The invention discloses a wind power generation fault on-line detection method and system based on multi-frequency-converter cooperation, and relates to the technical field of frequency converters, and the method comprises the steps: connecting U frequency converters, and collecting real-time operation parameters; obtaining a first connection state sequence of each wind power generation assembly corresponding to a first frequency converter in the U frequency converters; traversing the U frequency converters to obtain U connection state sequences, combining with historical fault examples, setting fault feature vectors, constructing a fault diagnosis model, and performing fault reasoning; based on the fault diagnosis model, in the wind power generation topological graph, setting V health state evaluation nodes, uploading real-time operation parameters, and carrying out optimal configuration; and configuring a fault diagnosis mechanism of the U frequency converters by using the V health state evaluation nodes. The technical problems of low efficiency and poor accuracy of frequency converter fault diagnosis in the prior art are solved, and the technical effect of improving the efficiency and accuracy of fault diagnosis is achieved by monitoring and analyzing the operation state of the frequency converter in real time.

The invention provides a micro-grid system supply and demand balance and green energy scheduling optimization method and system, which can accurately match the user side power demand and green energy production, and can call an energy storage system to release stored electric energy or buy electricity through a main power grid to complement power vacancy when there is a supply and demand electric quantity difference in a power generation trough and a power consumption peak period; in the peak period of solar power generation, photovoltaic electric energy is preferentially used for meeting the load requirement, when the total power generation amount is larger than the total power consumption amount, redundant power can be used for charging an energy storage device, efficient consumption of renewable energy sources is achieved, meanwhile, the stable and continuous characteristics of wind power generation are utilized, basic power is provided for loads in the whole time period day and night, and energy is saved. And in the solar valley stage and the load valley stage, the energy storage system is matched to carry out charging and discharging scheduling and stabilize power fluctuation, challenges caused by load peak-valley difference and renewable energy intermittency can be effectively handled through multi-energy cooperative control logic, and the reliability, economical efficiency and clean energy permeability of micro-grid operation are improved.

The utility model belongs to the technical field of wind power generation equipment, and relates to a main shaft device of a wind generating set, which comprises a front main shaft body, a middle main shaft body, a rear main shaft body, a front bearing outer ring, a rear bearing outer ring, a bearing seat, a front roller and a rear roller, the rear bearing outer ring is mounted at the other end of the bearing seat; the front roller is arranged in an annular space formed between the front bearing outer ring and the front main shaft body, and the rear roller is arranged in an annular space formed between the rear bearing outer ring and the rear main shaft body; the two ends of the middle spindle body are connected with the front spindle body and the rear spindle body respectively. The outer surfaces of the front main shaft body and the rear main shaft body are directly used as bearing raceways, and the bearing raceways, the corresponding front bearing outer ring, the corresponding rear bearing outer ring, the corresponding front roller and the corresponding rear roller form an inner-ring-free bearing system, so that the ring running phenomenon is avoided, and the stability of the main shaft in the running process is enhanced; and by splitting the main shaft, the overall size of the main shaft is reduced, and the manufacturing cost is reduced.

The invention discloses a wind power generation system model prediction control method and device based on event triggering. The method comprises the following steps: establishing a wind power generation system model; based on the wind power generation system model, whether an event triggering mechanism is activated or not is judged according to the deviation between the current state and the target state of the system and the maximum sampling interval time; designing an LMPC algorithm based on event triggering: if an event triggering mechanism is activated, solving an optimization problem in a finite time domain to obtain an optimal control sequence of the system, and fusing Lyapunov function constraint to ensure the closed-loop stability of the system; wherein the optimization problem takes a minimum weighted sum of a system output tracking error and a control input variable quantity as a target; and deploying the LMPC algorithm based on event triggering into a control device of the wind power generation system so as to realize optimal control of the wind power generation system. The stability and robustness of the wind power generation control system can be effectively improved.

The invention discloses a collaborative operation method, system, equipment and medium for an electricity-hydrogen storage integrated system, and relates to the technical field of electricity-hydrogen storage, comprising the steps of generating total output power based on environmental parameters by integrating photovoltaic power generation and wind power generation, performing electric energy conversion treatment on the total output power, and supplying the converted electric energy to a water electrolysis hydrogen production process. Hydrogen is generated by electrolyzing water, the hydrogen production rate is monitored in real time, the generated hydrogen is stored, the hydrogen storage pressure is adjusted according to a dynamic pressure model, the stored hydrogen is supplied to the fuel cell power generation process, electric energy is generated according to the load requirement, and through the cooperative control process and based on a multi-stage optimization control framework, the power generation efficiency of the fuel cell is improved. And power generation, conversion, hydrogen production, storage and power generation processes are cooperatively controlled in real time. According to the method, the problems of renewable energy fluctuation absorption and efficient conversion are solved, the breakthrough improvement of millisecond-level real-time response is realized, and the safety and economy of long-term operation of the system are guaranteed.

The invention discloses a wind power cabin inspection robot, and relates to the technical field of operation and maintenance of wind power generation equipment. Comprising a walking mechanism, an installation mechanism and a detection mechanism, the walking mechanism comprises a left installation frame, a right installation frame is arranged on one side of the left installation frame, a notch is formed in one side of the right installation frame, and an insertion strip is inserted into the notch. Through the arrangement of the walking mechanism, the mounting mechanism and the detection mechanism, in the use process, after the detection mechanism moves to a target area, a second motor drives a third gear to drive a second gear to rotate, so that a rotating rod rotates around a connecting frame, the transverse detection range is expanded, and meanwhile, the third motor drives a rotating shaft to rotate; the device can cover most of equipment and dead angles in a cabin, and the visual angle can be adjusted without moving the robot body.

The invention belongs to the technical field of wind power generation, and particularly discloses a wind energy directional rectifier which comprises a body and at least one airflow channel, the body is provided with at least one airflow channel in the extending direction of the central axis, and the body and the airflow channels are each of a streamline gradual change structure and have the same gradual change direction. Comprising a device for converting the wind energy rectified by the wind energy directional rectifier into mechanical kinetic energy to drive a generator to generate electricity. Wind energy in different directions is collected through the wind energy directional rectifier and then converged together to become high-speed jet flow consistent in direction and stable in flow speed, then the high-speed jet flow is converted into mechanical kinetic energy through the power conversion structure, finally the generator is driven to generate electricity, the wind energy utilization efficiency of the wind power conversion device is effectively improved, and the wind energy utilization efficiency is improved. The power generation efficiency of the wind-power conversion device is improved.

The invention provides a construction method of a mixed tower fan foundation formwork supporting system, and relates to the field of wind power generation infrastructure construction. Supporting cushion components are arranged at the bottoms of the first supporting vertical rods, the first supporting vertical rods are arranged, and transverse horizontal rods and longitudinal horizontal rods are erected to form an annular supporting frame body; a first inner formwork is arranged on the outer side of the annular supporting frame body, a center supporting frame body formed by matching of an inner-layer supporting frame and an outer-layer supporting frame is synchronously erected in the annular supporting frame body, and the center supporting frame body and the first inner formwork are connected through a first horizontal supporting rod; a second inner template is mounted at the top of the annular frame body; a third inner formwork is arranged on the second inner formwork and connected with the center supporting frame body through a second horizontal supporting rod; binding foundation bottom plate reinforcing steel bars and stand reinforcing steel bars, and carrying out foundation outer formwork construction. And by reasonably reinforcing the mixed tower fan foundation template, the economical efficiency is improved while the construction quality is guaranteed.

The invention relates to the technical field of wind power generation control, and discloses a yaw calibration method and system based on a fan sensor, and the method comprises the steps: carrying out the frequency domain and multi-resolution decomposition of a real-time wind direction signal, and obtaining a short-term disturbance level; if yes, recursive state estimation is executed to obtain a smooth wind direction trend; calculating a long-term drift value and carrying out probability state simulation and power loss model mapping to obtain nonlinear influence estimation; if high turbulence is judged, a dynamic compensation threshold value is calculated to generate an adaptive yaw instruction; the actuator is driven, and the alignment precision grade is determined according to the corrected feedback position; and iteratively updating the reference turbulence intensity index to match and optimize the compensation control parameter. According to the method, accurate identification of short-term disturbance and long-term change under complex turbulent flow can be realized, yaw maloperation is effectively reduced, and the alignment precision and the power generation efficiency are improved.

The invention discloses a high-altitude wind power generation system which comprises a main air bag extending in the front-back direction, and the peripheral face of the main air bag is a rotary face; the ring wing sleeves the radial outer side of the main air bag and is spaced from the main air bag, and a duct space is formed between the inner wall of the ring wing and the outer wall of the main air bag; the first supporting frame and the second supporting frame are sequentially arranged on the radial outer side of the main air bag in a sleeving mode in the axial direction of the main air bag; the wind power assembly is mounted on the first supporting frame; the first supporting frame comprises a plurality of supporting units, an annular supporting frame with an inner ring and an outer ring is defined by the multiple supporting units, the annular supporting frame comprises ducts formed between the adjacent supporting units, and the wind power assembly is installed in the ducts; the second supporting frame is of an annular grid truss structure and comprises a main body frame and truss rod pieces assembled in the main body frame through truss nodes, and the truss rod pieces and the truss nodes are modularly expanded to form the grid truss structure.

A method for determining a vortex-induced resonance region of a wind turbine blade and an anti-vortex device are provided, and relates to the technical field of wind power equipment. The method includes: obtaining the natural frequency of the wind turbine blade; segmenting the wind turbine blade to obtain a plurality of blade sections; calculating a vortex shedding frequency of a cross section of each of the plurality of blade sections at different wind speeds or under different operating conditions; and determining at least one vortex-induced resonance region of the wind turbine blade by comparing the vortex shedding frequency of the cross section of each of the plurality of blade sections at different wind speeds or under different operating conditions with the natural frequency.

The invention discloses a polar region environment-oriented two-stage micro-siting optimization method for a wind generating set, and relates to the technical field of polar region renewable energy planning and wind power generation, the optimization method comprises the following steps: polar region environment parameter initialization and scene modeling; the first stage is grid primary selection based on mixed integer linear programming; the second stage is coordinate refinement based on a multi-population genetic algorithm; and scheme output and efficiency evaluation. According to the method, a sector reweighting mechanism of extremely cold correction parameters is realized through reweighting of biochemical parameters and scenes in an environment special for a polar region, the extremely cold correction parameters are directly embedded into a wind regime scene set and a power model, and the problem that a conventional land model can obviously underestimate or overestimate single-machine power and wake flow propagation distance under extremely low temperature and low roughness conditions, so that the reliability of the model is improved is solved. Therefore, the power prediction and wake flow loss evaluation are more practical under the polar region conditions such as the south pole, so that the engineering reliability of site selection decision and the accuracy of generating capacity prediction are improved.

The invention provides a subsynchronous oscillation monitoring system and method for a wind power generation system, and the system comprises a signal collection module which is used for obtaining an output current parameter and a power grid interface voltage parameter in a target wind power plant region, and generating a current and voltage monitoring value; the feature extraction module is used for extracting oscillation frequency parameters and oscillation feature parameter values based on the current and voltage monitoring values; the dynamic threshold module is used for acquiring a power grid load parameter and a wind speed parameter and generating a dynamic threshold parameter value through weighted calculation; the state judgment module is used for performing state logic judgment based on the oscillation frequency parameter and the dynamic threshold value to obtain an oscillation state judgment value; and the result output module is used for generating a monitoring alarm signal value based on the oscillation state judgment value. According to the method, dynamic environment response and accurate feature extraction can be combined, the monitoring sensitivity and reliability are enhanced, the misjudgment probability caused by external interference is reduced, the protection action accuracy is optimized, and stable operation of a power grid is guaranteed.

The invention belongs to the technical field of wind power generation, and particularly discloses a method for monitoring the vibration state of a transmission chain of a wind generating set, and the method comprises the following steps: firstly, obtaining vibration data of each part of the transmission chain; then abnormal values in the transmission process are eliminated through a data processing module, and false vibration signals are eliminated based on correlation analysis of the vibration signals and the temperature signals to obtain effective vibration signals; respectively carrying out time domain analysis, frequency domain analysis and time-frequency domain analysis on the preprocessed effective vibration signals; and finally, the fault diagnosis module judges the current health state of the transmission chain in combination with an analysis result. Aiming at the problem that the current fixed sampling parameters cannot meet the monitoring requirements of different rotating speed components in a transmission chain, data acquisition resource optimization is realized by dynamically adjusting the sampling frequency; the problem that monitoring requirements of different rotating speed components in a transmission chain cannot be considered by adopting unified sampling parameters when the vibration state of the transmission chain is monitored in the prior art is solved.

The invention discloses a hierarchical simulation modeling system for a new energy station cluster and a real-time verification method, belongs to the technical field of new energy power generation simulation, and solves the problems of high simulation calculation complexity, difficulty in real-time operation and closed-loop interaction verification with an external control system of a large-scale new energy station cluster. According to the technical scheme, the method comprises the steps that a digital dynamic real-time simulation platform configured with a multi-thread parallel computing architecture is adopted, and a new energy station detailed model comprising a wind power generation unit model, a photovoltaic power generation unit model, an energy storage power generation unit model and a current collection system model is deployed on the platform; generating an independent wind speed sequence for each fan through a wind resource distribution model; and constructing a large-base station cluster model composed of a plurality of station simplified models through aggregation equivalence. The system is mainly used for real-time simulation testing of a large-scale new energy base and closed-loop verification of a control system.