1227 results about "Wind direction" patented technology

The invention discloses an energy-saving control method based on a building group spatial form, which relates to the technical field of energy-saving control, and comprises the following steps: constructing an airflow track analysis region based on a region with hot pressure difference direction change in a spatial pressure covering sensing matrix, and collecting continuous wind direction and wind speed data; judging whether the airflow direction is abnormal or not according to the change of the flow direction consistency entropy; performing spatial coincidence processing on the spatial pressure shielding sensing matrix and the airflow direction abnormal region, and generating an air outlet ventilation and heat extraction efficiency evaluation index based on the heat conduction rate in the coincidence region and the stability of an airflow output path; and on the basis of the ventilation and heat removal efficiency evaluation index of the exhaust outlet, an exhaust response condition matrix containing a space pressure shielding parameter, an airflow disturbance level and a heat retention level is constructed, and a ventilation control judgment sequence is generated. According to the method, the problem of air exhaust failure under pressure shielding interference is solved, ventilation efficiency accurate judgment and energy-saving regulation and control optimization are achieved, and the ventilation stability and the energy utilization efficiency of the building group are guaranteed.

The invention discloses a wind power generation abnormal data analysis method and system, and relates to the technical field of data analysis, and the method comprises the following steps: constructing a wind direction change rate enhanced perception model, analyzing the potential omen of wind direction abrupt change based on an ultra-short time scale wind direction change trend curve and a wind speed fluctuation coupling index collected at multiple measurement points, and determining the wind direction abrupt change. Generating a risk early warning label of wind wheel pointing deviation; and based on the risk early warning label, executing a high-frequency yaw disturbance prediction mechanism, and predicting an inflow angle continuous offset window caused by yaw response lag by using a nonlinear time sequence evolution trend and a short-term wind direction reversal probability curve. The wind direction sudden change early warning is realized through multi-measuring-point wind direction enhanced perception and wind speed coupling analysis, the response precision is improved and the energy consumption is reduced in combination with predictive yaw compensation and torque balance, the yaw parameters are dynamically optimized by using adaptive closed loop and reinforcement learning, the inflow angle is kept stable for a long time, and the power generation efficiency and the structural safety are improved.

The invention discloses an SAR sea surface flow velocity inversion method based on physical guidance and data driving fusion, and relates to the field of flow velocity inversion, and the method comprises the steps: carrying out the non-geophysical Doppler frequency shift correction of the Doppler frequency shift observed by a spaceborne synthetic aperture radar, and obtaining the geophysical Doppler frequency shift; predicting based on a wave-induced Doppler frequency shift model according to a radar incident angle, reanalyzed wind direction data, a sea surface 10-meter height wind speed inverted by an SAR (Synthetic Aperture Radar), a simulated wind wave parameter, a simulated surge parameter and a simulated maximum wave parameter to obtain a wave-induced Doppler frequency shift; the wave-induced Doppler frequency shift model is obtained based on physical guidance and data-driven modeling; doppler frequency shift generated by sea surface flow is determined according to the geophysical Doppler frequency shift and the wave-induced Doppler frequency shift; according to the method, the Doppler frequency shift generated based on the sea surface flow is converted to obtain the sea surface radial flow velocity, the wave-induced Doppler frequency shift is accurately removed, and reliable inversion of the sea surface flow velocity is realized.

The invention discloses a photovoltaic support structural member strength analysis method and system based on a wind load, and relates to the technical field of photovoltaic equipment detection, the method improves the accuracy and economy of photovoltaic support wind resistance design through multi-modal data fusion and intelligent algorithm iteration, and improves the photovoltaic support structural member strength analysis efficiency. Firstly, wind speed / wind direction separation modeling based on machine learning breaks through the limitation of traditional static wind pressure calculation, and the extreme wind condition prediction accuracy is effectively improved; secondly, non-dominant dangerous working conditions such as a 52-degree inclination angle can be automatically positioned through linkage of a parameterized model and a global optimization algorithm, and the efficiency is obviously improved compared with manual trial calculation; and finally, a stress threshold dynamic early warning mechanism realizes conversion from passive checking calculation to active defense.

The invention provides a method for monitoring and controlling cable-stayed buckling construction of a concrete-filled steel tube arch bridge based on a digital twin system, and the method comprises the steps: collecting the monitoring data, such as wind speed and wind direction, arch rib stress displacement, tower bottom stress, tower deviation and cable force, through a sensor; establishing a concrete filled steel tube arch bridge construction digital twinning system based on a three-dimensional model, real-time monitoring, data analysis and a visual platform; time sequence data is decomposed into different frequency components through variational mode decomposition (VMD), a bridge construction stage prediction model is established through a long short-term memory network (LSTM), and real-time accurate prediction of the construction progress and state is achieved. And secondly, based on the prediction model and on-site real-time monitoring conditions, an intelligent load adjustment construction control method based on a digital twin system is provided, and high-precision control over automatic load adjustment of cable hoisting and real-time rectification of tower displacement is achieved. The problems that in a traditional monitoring and control method, early warning is not timely, the assembling precision is insufficient, and the arch axis shape control difficulty is large are solved.

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 cluster regulation and control method, system and device based on distributed calculation and a medium, and belongs to the technical field of wind power cluster regulation and control, and the method comprises the steps: obtaining the historical wind speed and wind direction data of each wind driven generator in a wind power cluster; calculating a wind condition correlation coefficient between any two wind driven generators; constructing a graph model of a wind power cluster; based on the clustering number, clustering wind power generators in the wind power cluster to obtain a plurality of wind power groups; on the basis of a wind power set, an optimization objective function is constructed in combination with resource constraint conditions of the distributed computing nodes, and a distribution strategy of the distributed computing nodes is determined through an optimization algorithm; and operation regulation and control of the wind power cluster are realized. According to the method, the wind regime correlation coefficient is introduced to construct the graph model, the wind regime correlation degree between the wind driven generators can be accurately reflected, and the physical reasonability of clustering division is improved. The clustering number is determined through graph feature similarity matching, and the problem that parameter setting depends on experience in a traditional clustering method is avoided.

According to the complex mountain fan arrangement optimization method, the positions of fans in an array are adjusted one by one towards one side, the purpose of increasing the angle with the prevailing wind direction is achieved, the wake flow influence is reduced, the generating capacity is calculated and compared, and therefore the optimal fan position is determined. Through the optimization method, the position of the fan can be dynamically adjusted according to the actual situation, the wake flow influence and the shielding effect are reduced, and the generating capacity is improved. According to the method, the wind resource evaluation software micro-siting result and the wake flow adjustment strategy are combined, fan arrangement can be effectively optimized in the complex mountain environment, and the wind energy utilization efficiency is improved.

The invention discloses a control method and device of a wind driven generator, a terminal and a storage medium, particularly relates to the technical field of operation control of the wind driven generator, and is used for solving the problem that a supporting structure bears violent asymmetric loads due to dynamic response differences of wind and wave load directions in a marine environment in an existing control method. Wind direction and wave direction data are synchronously obtained in real time, the wind direction change rate is calculated, supporting structure vibration signals are analyzed to recognize wave excitation dominant frequency components, and when it is detected that wave excitation energy suddenly changes and the wind direction change rate exceeds the limit, the wind wave direction difference is analyzed; meanwhile, a wave spectrum energy concentration frequency band is determined by analyzing the tower top movement track, the load asymmetry risk level is evaluated by combining the direction difference and the wave energy concentration frequency band, finally, the yaw speed and the variable pitch speed are adjusted in a self-adaptive mode according to the risk level, and accurate recognition and early warning of the wind wave load direction mismatching working condition are achieved. And the operation reliability of the wind driven generator in extreme weather is improved.

The invention discloses an automatic cruise system for a cleaning robot of a power insulator of a transformer substation, and relates to the technical field of intelligent operation and maintenance of the transformer substation, the automatic cruise system comprises a data extraction module, a processing module, a decision module and an execution module, and solves the technical problems of excessive shutdown when a wind field approaches danger and discontinuous operation when the wind field is safe. The decision-making module sets safety indexes according to the weights of the wind speed and the wind direction, divides the wind speed into four risk intervals, divides the wind direction into three grades, calculates the total safety score of the wind field through weighted summation, corresponds to three operation grades of safety, yellow early warning and red early warning, generates differential instructions according to different grades, and sends the differential instructions to the wind field. And real-time path updating during early warning level switching is supported, and safe operation under the dynamic change of the wind field is realized.

The invention relates to a radar synthetic wind speed resolving method, device and equipment and a storage medium, and is applied to the field of radar speed measurement, the radar synthetic wind speed resolving method comprises the steps that radar sight wind speed and the rotation angle of a radar are acquired, and the rotation angle is the angle of a radar roll angle; performing radar beam azimuth calculation according to the rotation angle to obtain a radar beam vector; and performing synthetic wind speed calculation according to the radar sight wind speed and the radar beam vector, and generating scalar wind speed and wind direction. The method has the technical effect that the calculation accuracy of the synthetic wind speed is improved.

The invention discloses a multi-unmanned aerial vehicle route planning method in a multi-wind area environment. The method mainly comprises the following steps: establishing a three-dimensional map of typical task areas of unmanned aerial vehicles, dividing the areas, setting different wind directions and wind speeds, setting a plurality of unmanned aerial vehicles, and setting a fixed starting point and a fixed target point; randomly distributing a target point for each unmanned aerial vehicle by using an evolutionary algorithm, calling an improved RRT * algorithm for each unmanned aerial vehicle, and searching a feasible leg from the starting point to the target point in the three-dimensional map; iterating the distribution schemes of different target points by using an evolutionary algorithm and a fitness function to obtain an optimal target point distribution scheme, and further generating a flight path of the unmanned aerial vehicle; and performing path stretching and cubic B-spline interpolation on the initial route of each unmanned aerial vehicle to obtain route planning of the multiple unmanned aerial vehicles.

The invention discloses a yaw wind error compensation method and system based on wind measurement data, and relates to the technical field of wind power generation equipment control, and the method comprises the steps: setting a wind measurement point position, and collecting an original wind field data set; calculating an incoming flow and a cabin wind direction angle according to the original wind field data set; performing deviation calculation to obtain a yaw wind error angle; triggering a dual-channel compensation module, accumulating errors, constructing an error queue, and performing batch compensation to obtain a compensation result; yawing control parameters are called, the cabin attitude is analyzed according to the compensation result, the yawing control parameters are updated, and self-adaptive compensation of yawing to the wind error is achieved. The technical problems that in the operation process of the wind driven generator, due to wake flow, terrain, turbulent flow and other environmental factors and equipment loss, a traditional yaw system cannot accurately detect the wind direction and compensate the wind alignment error, the power generation efficiency is low, and the potential safety hazard of equipment is large are solved, and the purposes of accurately improving the wind alignment precision of a wind wheel and improving the power generation efficiency are achieved. The power generation efficiency is obviously improved; and the equipment operation safety is enhanced.

The invention relates to the field of wind and sand prevention and control, in particular to a desert photovoltaic large base peripheral prevention and control system and method. The prevention and control system comprises a main air guide direction prevention and control system and a secondary air guide direction prevention and control system; the main wind direction prevention and control system is sequentially provided with three high vertical sand blocking fences, a lateral anti-lateral quicksand fence, a first sand stabilization grid area with a grid structure, two first plant sand blocking forest belts, a first plant sand stabilization area and a windproof sand blocking dust suppression fence in the direction from the upwind direction to the photovoltaic base. And the secondary wind guide direction prevention and control system comprises a second sand stabilization grid area, a second plant sand blocking forest belt and a second plant sand stabilization area. The sand prevention system can effectively solve the problems that an existing sand prevention technology is low in efficiency, unsustainable and the like, erosion and damage of sand grains to photovoltaic panels and infrastructures are reduced, the power generation efficiency is improved, the maintenance cost is reduced, long-term stable and efficient operation of a desert photovoltaic large base is guaranteed, and powerful support is provided for energy development and ecological protection balance in the desert area.

The invention discloses a short-term wind power prediction method based on dynamic graph and multi-scale space-time fusion. A dynamic space-time convolution attention network is constructed. Aiming at the dynamic topology and sequence complex characteristics of the wind power plant, a space-time topology module based on metric learning is designed, the physical distance and real-time characteristics are adaptively fused, and dynamic space correlation caused by the wind direction and wake flow effect is captured. The core ST-CAN module integrates graph convolution, time convolution and a self-attention mechanism, and through a mixed strategy of local convolution and global attention, modeling spatial dependence, local high-frequency fluctuation and a long-range period rule in a collaborative manner. According to the method, the prediction precision and generalization ability are remarkably improved, and power prediction challenges under complex wind conditions can be effectively coped with. According to the method, MAE, RMSE and MAPE indexes under different prediction step lengths are superior to those of a traditional method and an existing deep learning model, the prediction precision is high, the robustness is high, and the method is suitable for a complex wind field environment.

The invention discloses a delta-beach bar composite sand body prediction method, which comprises the following steps of S1, acquiring geological background data of a target work area, and dividing delta and beach bar deposition to obtain a beach bar deposition thickness; s2, carrying out source and sink system analysis, establishing a sediment transport channel path, and obtaining a sand body transport path plane distribution diagram; s3, the ancient landform, ancient wind field features and ancient wave field features of the target work area in the deposition period are restored, the ancient landform height and the distance to the source area of the underwater ancient protrusion are obtained according to the ancient landform, and the features include the ancient wind direction, the ancient wind path, the ancient water depth and the ancient wave height; s4, determining a favorable development zone, a favorable development layer section and a favorable development target zone of the delta-beach bar composite sand body; and S5, obtaining distribution characteristics of the delta-beach bar composite sand body of the target work area according to the favorable development zone, the favorable development layer section and the favorable development target area. According to the method, the delta-beach bar composite sand body can be accurately predicted, and technical support is provided for oil exploration and development.

The invention relates to a target track association method in a multi-target environment. The method comprises the following steps: firstly, preprocessing a new received trace point; secondly, predicting the next position of each track by using the existing track historical information and adopting a Kalman filtering algorithm, meanwhile, adjusting a state transition matrix and a process noise covariance matrix in real time by considering factors such as ocean current and wind direction in an offshore environment, and adjusting an observation noise covariance matrix according to meteorological information; then comprehensively considering distance, speed difference and motion direction difference to calculate a correlation degree magnitude between a new receiving trace point and each predicted track position; and finally, judging whether the newly received trace point belongs to the existing target track or forms a new target by adopting a threshold judgment method according to the correlation degree value, and updating the state of the track. The method can effectively cope with multi-target intersection, observation loss and clutter interference, improves the stability of a matching result, can realize continuous tracking of a marine target, can adjust parameters according to the environment and target characteristics, and has high adaptability.

The invention discloses a C-SAR satellite sea surface wind speed inversion method combining spatial features, and relates to the technical field of sea surface wind speed inversion, and the method comprises the steps: selecting C-SAR data and ERA-Interim wind field data; pre-processing the C-SAR data, and then carrying out time and space matching on the pre-processed C-SAR data and ERA-Interim wind field data; and inputting the matched C-SAR data and ERA-Interim wind field data into a double-branch feature fusion network model based on attention mechanism guidance, inverting the wind speed of the central pixel position of the sub-image, and then comparing the wind speed with the ASCAT wind field data and the ERA-Interim wind field data for verification. According to the method, a double-branch neural network structure is adopted, Branch1 is utilized to construct nonlinear features among a backscattering coefficient, an incident angle, a viewing angle, a sea surface wind speed and a wind direction, and Branch2 is utilized to excavate spatial features of C-SAR data and ERA-Interim wind field data; carrying out feature fusion on the nonlinear features and the spatial features by utilizing a channel attention mechanism module; the dynamic characteristics of C-SAR inversion of the sea surface wind speed are guaranteed, and the inversion precision is improved.

The invention relates to the technical field of meteorological observation, in particular to a parameter measurement method and device based on a dual-band mode, equipment and a storage medium. Generating a dual-band excitation signal according to the aligned sine wave signal; analyzing the echo signal according to a preset gain coefficient, a time difference method and a preset attitude compensation formula to obtain a reconstructed quasi-unipolar pulse, an actual wind speed, a horizontal wind direction angle, a pitch angle, a three-dimensional wind speed vector, a roll angle and a real wind direction; acquiring real-time air pressure, and correcting a preset standard state sound velocity according to a preset sound velocity correction formula and the real-time air pressure to obtain a corrected sound velocity; according to the scheme, a dual-band signal attached to a medium is generated, after efficient transmission analysis, high-resolution pulses and multi-dimensional wind field parameters are obtained by means of gain, a time difference method, attitude compensation and the like, the sound velocity is corrected in combination with air pressure, comprehensive, accurate and rapid updating of data are considered, and the measurement reliability is improved.

The invention relates to the technical field of data detection, in particular to an unmanned aerial vehicle atmospheric data anomaly detection and correction system based on deep learning, and provides the following scheme: an air mass reference coordinate system is constructed based on the attitude of an unmanned aerial vehicle and a relative wind direction; re-projecting the original measurement data to obtain an atmosphere data sequence with a stable reference direction; then, generating a frequency mask dynamically changing along with time, wherein the frequency mask is used for constraining positioning of disturbance energy of the rotor wing in the time-frequency analysis process; performing multi-scale decomposition on the time-frequency coefficient matrix based on a multi-channel frequency mask, and respectively extracting an aerodynamic disturbance estimation signal, a background atmosphere signal and a turbulence structure signal; and inputting the three types of signals into a preset deep learning model to realize identification and corresponding correction of atmospheric data anomaly. According to the invention, rotor disturbance and a real atmospheric structure can be distinguished, and the quality and reliability of atmospheric observation data are improved.

The invention relates to the technical field of chemical gas, in particular to a chlorine leakage detection method and system in reaction kettle production. The method comprises the following steps: acquiring chlorine concentration values and wind field vectors of a plurality of positions around a reaction kettle at each moment; marking any moment as a target moment, and determining the gas diffusion contribution coefficient of each position to other positions at the target moment; determining a real gas diffusion contribution coefficient of each position to other positions at the target moment; determining the airflow correction density of each position at the target moment; and positioning a chlorine leakage source by using a density peak clustering algorithm based on the airflow correction densities of all positions at the target moment. According to the method, the wind field vector is introduced to construct the gas diffusion contribution coefficient to correct the density, the limitation of traditional static diffusion is overcome, the real leakage source and the concentration convergence point in the downwind direction are effectively distinguished, the accuracy and reliability of chlorine leakage source positioning are improved, and support is provided for safe emergency disposal.

The invention discloses a method for evaluating the EEDI contribution of a wing-shaped sail based on actual ship sea trials, and relates to the technical field of ships. The method comprises: conducting actual ship performance tests on ships equipped with sails to obtain main engine power required to maintain a target speed when the sails are in different operating states at various relative wind direction angles; obtaining a net thrust test coefficient of the sail at various relative wind direction angles at the target speed based on the main engine power; obtaining a net thrust simulation coefficient curve of the sail at various relative wind direction angles at the target speed based on a four-degree-of-freedom motion model of the ship; comparing the net thrust simulation coefficient curve of the sail with the net thrust test coefficient of the sail to establish a revised four-degree-of-freedom motion model of the ship in a sail-raising operating state; and calculating sail thrust matrix elements and sail EEDI contribution corresponding to a reference speed and any combination of wind field conditions based on the four-degree-of-freedom motion model of the ship in the sail-raising operating state and the four-degree-of-freedom motion model of the ship without sails. The method has the characteristics of being objective, realistic, and operational.

The utility model provides a wind direction and wind speed measuring device and a steel structure tower device. The wind direction and wind speed measuring device comprises a sampling main body, the sampling main body comprises a plurality of air inlets and at least two air channels, the plurality of air inlets are correspondingly communicated with the at least two air channels, openings of the plurality of air inlets face at least two different directions, and the at least two air channels are mutually independent and extend in different directions; the first temperature detection assemblies are arranged in the air ducts and used for collecting temperature information of at least two different positions in the extending direction of the air ducts. The second temperature detection assembly is arranged inside or outside the air duct and used for collecting environment temperature information. The humidity detection assembly is arranged inside or outside the air duct and used for collecting environment humidity information. The controller is used for calculating wind power data according to the temperature information and the humidity information, and the wind power data comprises wind direction and wind speed. The 360-degree omni-directional wind speed and wind direction measuring device is beneficial to measuring 360-degree omni-directional wind speed and wind direction, wide in measuring range, high in reliability, easy to maintain and high in measuring precision.

The invention relates to the technical field of photovoltaic supports, in particular to a photovoltaic panel support with an adjustable installation angle. The invention aims to solve the problems that a photovoltaic bracket in the prior art is easy to damage when being impacted by strong wind, and a photovoltaic panel is rotated to be in a horizontal state when the photovoltaic bracket faces a strong wind environment, so that the sunlight receiving efficiency of the photovoltaic bracket is obviously reduced. Comprising an adjusting frame and further comprises a detection mechanism, and the detection mechanism is arranged on the upper side of the adjusting frame. Through the design of the detection mechanism, when strong wind impacts the detection box, the detection box can rotate with the connecting position of the frame as the circle center according to the wind direction of the strong wind, so that the first air guide frame moves, and the detection mechanism can make the locking mechanism move according to the detection result, so that a gap is generated between the rectangular frame and the frame; strong wind passes through the gap between the rectangular frame and the frame, so that the frame and the rectangular frame are prevented from being impacted by the strong wind to greatly shake or directly crack, and the wind resistance strength of the photovoltaic panel support is effectively improved.

The invention discloses a cabin type laser radar wind field detection method and system based on multi-beam expansion. The cabin type laser radar wind field detection method and system are low in cost, high in sampling density, small in fitting error and high in measurement precision. The method comprises the following steps: transmitting a plurality of groups of uniformly distributed radial detection wave beams through a cabin type wind measurement laser radar, and carrying out omnibearing scanning on a target wind field; collecting radial wind speed observation data of each group of beams, performing nonlinear fitting processing on the observation data based on a cosine fitting model, and determining a mapping relation between fitting parameters and azimuth angles; the real wind speed and wind direction of the target wind field are calculated through the fitting model; the system comprises a transmitting module (1), a receiving module (2), a fitting calculation module (3) and an output module (4). The method is applied to the technical field of wind measurement laser radars.

The invention discloses an air conditioner control method, device and equipment in a sleep application scenario and a medium, and the air conditioner control method in the sleep application scenario comprises the steps that point cloud data of a user sleep area is continuously obtained through a millimeter wave radar, and the covering states of covering objects of all parts of a body are accurately recognized; the defects that a traditional infrared or temperature and humidity sensor cannot penetrate through the fabric, and local exposure is difficult to judge are overcome. Based on the recognition result, the system generates wind direction, wind speed and other wind feeling adjusting instructions in real time, air supply of the air conditioner is prevented from directly blowing exposed parts, and the thermal comfort is improved. The self-adaptive optimization of the strategy is realized by continuously monitoring the body movement frequency and the turn-over times of the user before and after adjustment, evaluating the adjustment effect and carrying out positive or negative weight adjustment on the control rule. The problems that in the prior art, due to the fact that the coverage state cannot be accurately perceived, air supply is uncomfortable, cold catching is likely to happen, and adjustment lags are solved, and the air conditioner use experience in the sleep scene is remarkably improved.

A temporary shade structure system includes a weather and UV radiation resistant shade sail, at least three connection poles suitable for the installation environment, and weather and UV radiation resistant ropes or lines. The shade sail is connected to the poles using the ropes or lines. The system is adjustable to accommodate changes in sun location and wind direction. The system is designed to withstand different environmental conditions such as high winds, heavy rains, or extreme temperatures. A method for erecting the shade structure over a dock or deck is also disclosed, which involves identifying suitable structures for attaching the shade sail system, measuring the area for the sail, ordering the sail based on the measurements, and installing and adjusting the sail.

The invention relates to the field of wind driven generators, and particularly discloses a floating type vertical axis wind turbine multi-partition variable pitch control strategy which comprises the steps that S1, basic parameters and operating condition parameters of a unit are obtained; s2, establishing an aerodynamic model based on a double-disk multi-flow management theory and a superposition wind speed method; s3, measuring parameters through a sensor, and calculating a theoretical attack angle of the blade; s4, establishing a multi-partition pitch angle change function based on the theoretical attack angle; s5, constructing an NSGA-II multi-target optimization model, and taking maximization of an average power coefficient and minimization of a blade thrust standard deviation as targets; s6, substituting a function to obtain an optimal variable pitch control factor and an optimal pitch angle; and S7, the optimal pitch angle is converted into a variable pitch actuator instruction. The problems that an existing strategy is limited in partition, the wind direction influence is ignored, and optimal parameters for working condition adaptation are lacked are solved, the wind energy capture efficiency is improved, the load fluctuation is reduced, and the variable pitch control accuracy is improved.

An offshore wind-resistant photovoltaic platform supporting structure belongs to the technical field of offshore photovoltaic equipment installation, and comprises an installation seat and a photovoltaic panel, the interior of the installation seat is slidably connected with a rotating ring, the inner wall of the rotating ring is provided with an inclination angle adaptation mechanism, and a downward movement pressure reduction mechanism is arranged above the installation seat. The dip angle adaptation mechanism comprises a movable block arranged above the rotating ring, when the photovoltaic panel is subjected to weak wind, the movable block moves in a small range to buffer instantaneous sea wind pressure, when the photovoltaic panel is subjected to strong wind, the movable block drives the long edge of the photovoltaic panel to rotate to directly face the wind direction, and the wind load is reduced to prevent the structure from being damaged due to instantaneous impact of the strong wind. A rotary wind-resistant mechanism is arranged above the movable block, the rotary wind-resistant mechanism comprises a sliding disc arranged at the top of the movable block, and the sliding disc is extruded to move when the photovoltaic panel is subjected to the wind pressure of sea wind, so that the photovoltaic panel changes the pitch angle around the horizontal axis of the photovoltaic panel to parallel the wind direction, and the stability is enhanced while the wind area and the wind pressure of the photovoltaic panel are reduced.

The invention discloses a control method and device for the yaw angle of a wind driven generator and a medium. The method comprises the steps that meteorological data are obtained, wind direction change information is determined according to the meteorological data, a wind direction change angle is determined according to the wind direction change information, and the wind direction change angle is compared with a preset angle threshold value; if the wind direction change angle is larger than the angle threshold value, the predicted yaw angle of the wind driven generator is determined according to the wind direction change information; and adjusting the wind driven generator according to the wind direction change information and the predicted yaw angle. Through multi-dimensional data processing and dynamic monitoring, the change point is accurately determined, the yaw angle is predicted, the adjustment strategy is optimized, invalid rotation loss is reduced, the power generation efficiency is improved, flexible adjustment can be conducted according to the real-time situation, and efficient and stable operation of wind power generation is ensured.