171 results about "Wind resource" 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 relates to the technical field of wind power generation, and discloses a cross-scale wind power plant wind resource evaluation method based on a numerical mode, comprising the following steps: step 1, acquiring multi-source observation data of a target area; step 2, screening a WRF optimal configuration scheme adaptive to the regional terrain; step 3, through a WRF power downscaling method, generating annual scale wind resource data as initial wind resource data; 4, performing partition correction on the initial wind resource data to obtain wind measurement data; step 5, constructing a WRF-WFP model coupling the WRF mode and the wind power plant parameterized model; step 6, optimizing WRF lower boundary conditions; 7, simulating the atmospheric flow of the target area, and quantifying the wake flow evolution characteristics of the wind power plant; 8, constructing a wake flow analysis model; and step 9, formulating a collaborative productivity plan of the wind power plant group. The power generation capacity of the wind power plant to be developed can be accurately predicted, and a reliable basis is provided for scientific decision-making of resource distribution development and planning of the million-kilowatt wind power plant.

The invention belongs to the technical field of wind power generation, and discloses a wind driven generator multi-drive variable pitch control method based on big data, which comprises the following steps of: constructing a multi-source data acquisition network covering an environment, a unit, a power grid and a driver, and combining preprocessing means such as denoising and standardization and feature extraction methods such as principal component analysis; high-quality input is provided for a short-term prediction model; the model can accurately pre-judge wind conditions and power requirements in the future 10-30 minutes, and is matched with a global optimization algorithm to dynamically adjust a variable pitch strategy, so that the wind driven generator can still keep stable power output under complex working conditions of gust, power grid fluctuation and the like, and particularly has outstanding performance in areas with unstable wind resources. According to mechanical coupling characteristics of the multi-drive variable pitch system, mechanical parameters such as a gear transmission gap and shafting rigidity are fully included in global optimization, and power output, mechanical fatigue and load distribution are balanced through a multi-objective optimization algorithm.

The invention relates to the technical field of wind energy resource evaluation, in particular to a method and a system for calculating a hydrodynamics wind field numerical value based on high-precision landform, and the method comprises the steps: generating a three-dimensional unstructured grid for CFD wind field simulation based on high-precision landform data; analyzing an atmospheric boundary layer structure, and establishing a turbulence calculation model; according to the turbulence calculation model, the influence of atmospheric stability on the mountain flowing wind acceleration factor is researched, and a mountain flowing model is developed; performing CFD wind field simulation according to the three-dimensional unstructured grid and the mountain flow model, and correcting parameters of the mountain flow model; a refined grid is made through terrain elevation data; and according to the refined grid, driving the corrected mountain flow model to carry out numerical simulation, and carrying out wind power plant wind resource evaluation. Through the method, the complex characteristics of the wind field can be reflected more comprehensively, the precision and the calculation efficiency of wind resource evaluation are remarkably improved, and the efficiency and the accuracy of numerical simulation of the complex terrain wind field are improved.

The invention relates to a wind resource prediction method based on quality control assimilation of multi-source observation data, and the method comprises the steps: integrating the multi-source observation data, including a multi-band radar reflectivity factor, a radial speed, a ground observation station, and wind profile radar data; quality control processing such as mottle removal, data filling, speed folding removal and discontinuous data removal is carried out, so that the accuracy and continuity of the data are improved; then, through lattice point interpolation and three-dimensional variation assimilation technologies, the processed observation data are fused into an initial background field, and an analysis field closer to the actual atmospheric state is generated, so that the reliability of severe convective weather risk assessment is remarkably improved, and the accuracy of wind energy prediction is also enhanced; and more comprehensive, detailed and stable information support is provided for weather forecast and energy management.

The invention discloses a CFD (computational fluid dynamics) analogue simulation-based wind power plant wind resource evaluation method and a CFD analogue simulation-based wind power plant wind resource evaluation device. The evaluation method comprises the following steps: collecting and processing landform and meteorological data of a wind power plant site; establishing a three-dimensional CFD simulation model of the wind power plant according to the processed landform and meteorological data of the wind power plant site, performing grid division on a wind power plant area, and setting simulation boundary conditions; performing numerical simulation on the three-dimensional CFD simulation model of the wind power plant, and analyzing wind speed field distribution information of each position in the wind power plant; and according to the wind speed distribution information, calculating and evaluating the wind resource condition of the wind power plant to obtain a wind resource evaluation result. According to the technical scheme, through the three-dimensional simulation-evaluation-optimization closed loop with the CFD as the core, the wind speed and turbulence can be accurately quantified in the design stage, so that unit model selection, tower height, blade length and machine position layout are matched with a real wind field, key parameters can be determined at a time, the design period can be shortened, and the operation and maintenance and grid connection cost can be reduced.

The invention discloses a wind power plant micro-siting assessment method based on spatial analysis and climate adaptability, relates to the technical field of wind power plant siting, and solves the problems that in the prior art, spatial analysis depends on static topographic data, climate adaptability assessment uses dynamic meteorological data, and the static topographic data and the dynamic meteorological data lack a space-time synchronization mechanism; and a prediction result has a large deviation. The method comprises the following steps: firstly, acquiring multi-source data and fusing to realize time-space synchronization of the data; then, constructing and solving an objective function to obtain a candidate point set, and screening out an optimized point distribution scheme of which the prevailing wind direction coverage is greater than a set threshold value; and finally, inputting prediction data of various extreme climates into the cost-per-kilowatt-hour model, introducing extreme climate toughness parameters into calculation to carry out climate adaptability data correction, and calculating return on investment cycles under different carbon emission scenes. Through the steps, the limitation that only static wind resources are concerned on traditional site selection is broken through, and combined evaluation of the regional climate adaptability and the complex terrain adaptability is achieved.

The invention provides a wind power plant equipment modeling and operation and maintenance management and control method and device based on digital twinning, and the method comprises the steps: restoring a fan entity based on a 1: 1 three-dimensional modeling technology, integrating multi-source data, including equipment sensor, video monitoring and GIS topographic data, and achieving the real-time mapping of a physical field and a virtual field through the construction of a high-precision digital twinning model. And the intelligent decision support module predicts wind resource distribution by using a dynamic boundary layer model, optimizes a grid-connected control strategy in combination with a virtual inertia simulation technology, and guarantees the transient stability of the power grid in a new energy fluctuation scene. And the full-life-cycle management platform supports full-process management from site selection planning, operation monitoring to fault diagnosis, and realizes multi-service data fusion display and interactive operation and maintenance strategy verification through a three-dimensional visual large screen.

The invention discloses a photovoltaic power station wind field evaluation method and system, electronic equipment and a storage medium, and relates to the technical field of photovoltaic power station engineering. The method comprises the following steps: carrying out classification processing on original point clouds, generating DEM data by using Delaunay triangulation in combination with a natural neighborhood interpolation method, and carrying out correction through ground control points and least square adjustment; and constructing a three-dimensional terrain model according to the corrected data and image data, determining a computational domain size and a boundary condition, performing terrain optimization, executing LES solution after applying near-surface turbulence inlet disturbance synthesized by PRFG3, and comparing and evaluating the obtained transient wind field data with field actually measured wind speed data. According to the method, accurate capture of complex terrain wind field features and dynamic adaptive correction of the model are realized, so that the evaluation period is shortened, the surveying and mapping cost is reduced, the precision and reliability of wind field evaluation are remarkably improved, and the demand of wind resource evaluation of a large-scale photovoltaic power station is met.

The invention discloses a wind power plant arrangement optimization method and device, equipment and a storage medium, and relates to the technical field of wind power plant design and optimization, and the method comprises the steps: obtaining environment turbulence intensity and a fan thrust coefficient, and constructing an omnidirectional wind resource map; inputting the environmental turbulence intensity and the fan thrust coefficient into a TurbOPark wake flow model, calculating wake flow loss and obtaining the inflow wind speed of each fan under each wind direction and wind speed combination; taking the wind frequency in the omnidirectional wind resource map as a weight, and carrying out weighted summation processing on single-machine power obtained by converting the inflow wind speed through a power curve to obtain a target function of maximizing the total power generation of the whole field; and by taking the boundary polygon coordinates and the minimum spacing requirement as constraints, randomly disturbing the fan coordinates and comparing the target function before and after disturbance to iteratively update the fan position, the target fan coordinates and the whole-field total generating capacity corresponding to the target fan coordinates are obtained, and the optimization precision and the engineering efficiency are remarkably improved.

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.

The invention relates to the technical field of wind driven generator blades, and discloses a power increasing and deicing method for wind driven generator blades, which comprises the following steps: S1, analyzing field wind resources and calculating parameters: collecting long-term data by using meteorological data and wind field measurement equipment, analyzing the wind resources, and analyzing and calculating key parameters based on the wind resources; s2, load comparison and strength evaluation: simulating stress conditions of the extended blade at different wind speeds, calculating new load distribution, and comparing a calculation result with an original design load of a unit; s3, on-site blade extension technical improvement is implemented, specifically, the blade tip of an original blade is cut, temperature and flow monitoring equipment is installed at the position of the blade tip, and a blade tip extension section is firmly bonded with the blade root and the blade tip; s4, blade rotation positioning is conducted, specifically, the blades are subjected to pitch changing till the blades are parallel to the ground, the SS faces are downward, and after pitch changing is completed, the blades and the impeller are locked; and S5, polishing and mounting position marking: marking the mounting position of the air guide pipe, and polishing the mounting positions of the air blower and the heater.

The invention discloses an offshore high-power wind power plant rapid prediction system and method based on wind resource refined evaluation and field network integration. The system comprises a wind resource fine evaluation module used for comprehensively considering wind speed, wind direction, turbulence intensity, atmospheric stability and marine environment parameters to obtain spatial and temporal distribution of wind energy resources; the high-power wind turbine comprehensive modeling module is used for establishing a wind power plant unit power output model in combination with the power curve and a Jensen wake flow model; the neural network prediction module is used for realizing rapid prediction of future power; and the field network integrated rapid solution and grid connection module combines the predicted power with the power grid constraint condition, and outputs the adjusted power curve and power grid operation characteristics by adopting a rapid solution and optimization method. According to the method, the impact of wind power fluctuation on the power grid can be effectively reduced, the wind power grid-connected friend performance and the power grid stability are improved, rapid solving and dispatching optimization of the generating capacity of the high-power wind power plant in the deep and far sea are achieved, and the method has high engineering application value.

The invention provides a blade root load calibration data monitoring method, system and device and a medium, and belongs to the technical field of wind turbine generator control, and the method comprises the steps: carrying out the iteration of a generator set load according to a wind resource parameter and an IEC load calculation standard, and obtaining a maximum design value of the blade root load of the generator set; carrying out coordinate transformation on the load and carrying out moving mean filtering processing on the load signal; the mean value of the blade root loads of the three blades and the difference between the blade root load of each blade and the mean value of the blade root loads of the three blades are calculated; comparing and judging the difference value with a theoretical maximum value of the blade root flapping direction load, and judging whether the difference value is greater than a load deviation alarm threshold value or not; if yes, a fan fault alarm is given out, and variable pitch optimization action is executed according to the load deviation checking pitch angle limit table. According to the method, the blade root load calibration data can be monitored, the running state of the fan can be continuously optimized, the load deviation is reduced, and the safety and stability of the fan are improved.

The invention discloses a distributed wind power site selection and optimization method, system and device and a medium, and the method comprises the steps: obtaining wind resource data of a candidate wind power plant region, and building a multi-factor physical model; constructing a multi-factor wind field site selection model, and calculating optimal solutions of total power generation power maximization and total power generation cost minimization; and determining an optimal site selection scheme by combining the model optimal solution, wind resource distribution and topographic conditions. By improving the reserved suboptimal solution of the NSGA2 algorithm and dynamically adjusting the crossover and mutation probability, the population diversity is effectively maintained, the global search ability is enhanced, and a decision maker is supported to select the optimal layout; wind resource characteristics are comprehensively quantified through a multi-factor physical model, and the physical accuracy of site selection analysis is improved; through model hypothesis, the model complexity is reduced on the premise of ensuring the reliability, and the calculation efficiency is improved; the balance between economical efficiency and power generation efficiency is realized by taking minimization of power generation cost and maximization of power generation power as targets through a multi-factor wind field site selection model.

The invention discloses an island surrounding wave light wind resource comprehensive development suitability evaluation method and device and a medium, and relates to the field of resource development and evaluation, and the method comprises the steps: taking a suitability evaluation criterion as a criterion layer, taking an influence index as an index layer, and constructing a comprehensive development evaluation index system of a hierarchical structure; performing normalization processing on indexes in the index layer; adopting an analytic hierarchy process and a CRITIC method to determine the weight of the criterion layer based on the indexes in the index layer, and obtaining the weight; combining the two weights to obtain a combined weight of the criterion layer; and determining the suitability value of each spatial point in the peripheral area of the island based on the combination weight and the normalization result, and taking the spatial points with the suitability values higher than a set threshold value as a comprehensive development area suitable for collaborative complementation of waves, wind and photovoltaic resources. According to the method, various ocean renewable energy sources can be scientifically evaluated and reasonably optimized, and the scientificity and the accuracy of comprehensive development suitability evaluation of wave light and wind resources around an island are improved.

The invention relates to the technical field of wind resource assessment, and discloses an offshore wind power plant site selection method based on development scene feature representation classification, which comprises the following steps: acquiring data of multiple dimensions such as a wind resource development environment, a construction environment and an operation and maintenance environment, and classifying initial development scenes of an offshore wind power plant in combination with a feature representation method; the defect that a traditional method depends on a single index is overcome; a multi-layer perceptron model is utilized and combined with multi-dimensional data, comprehensive prediction of the wind power plant development environment is achieved, and prediction deviation caused by traditional subjective experience is avoided. Meanwhile, by predicting the productivity and the cost in advance, the development risk and the cost caused by incomplete consideration of environmental factors are avoided. Furthermore, a multi-objective decision-making method is adopted for scoring based on a prediction result, so that multi-objective conflicts such as productivity, cost and risk are comprehensively balanced, site selection one-sidedness caused by a single index in a traditional method is avoided, scientificity and objectivity of decision making are improved, and development risk and cost are reduced.

The invention discloses a wind and light storage cooperative power system suitable for a Sagomean area with deficient wind resources. The wind and light storage cooperative power system comprises a photovoltaic power generation unit, a floating type high-altitude wind power generation unit, a large-scale electrochemical energy storage unit and a central control module. The photovoltaic power generation unit serves as a basic power source, the wind power generation unit captures high-altitude stable wind energy through the floating technology to achieve complementary power supply, and the energy storage unit solves the problems of wind and light output fluctuation and load demand imbalance. And the central control module realizes efficient utilization of energy and stable operation of the system through a wind power prediction module, a multi-target collaborative scheduling module and a system operation optimization module in combination with an equipment health state evaluation and preventive maintenance strategy. The system breaks through the limitation of ground wind resources, improves the absorption capability of renewable energy sources, adapts to extreme environments, and guarantees the reliable supply of power in the Saggob area.

This invention discloses a PIDNN-SO-based method for optimizing the layout of offshore wind farms, belonging to the field of wind farm optimization design technology. The method first inputs wind farm, turbine, and wind resource parameters, sets constraints on turbine spacing, boundaries, and wake overlap rate, and constructs a high-precision wake flow field physical model based on actuator disk theory, Navier-Stokes equations, and a weighted quadratic wake superposition model. Secondly, it builds a physical information dual neural network (PIDNN) with dual encoders, integrating physical equation loss and data loss to train the model, achieving rapid and accurate prediction of wake wind speed. Then, it uses the snake optimization algorithm (SO) to optimize the environmental evolution factor, completing an efficient search for turbine layout. Finally, it constructs a PIDNN-SO collaborative optimization framework, trains a PIDNN surrogate model through initial sampling, and outputs the optimal layout that maximizes annual power generation. This invention can effectively reduce wake loss and significantly improve the power generation efficiency of offshore wind farms.

The invention discloses a wind resource assessment method based on multi-source data fusion, a medium and a system. The method comprises the following steps: S1, acquiring project basic information and multi-source data of a wind power project; the project basic information comprises a project name, a geographic position and topographic information; the multi-source data comprises anemometer tower data, mesoscale data and CFD data; s2, preprocessing the anemometer tower data to generate corrected anemometer data; s3, performing multi-source data fusion on the corrected wind measurement data, mesoscale data and CFD data, and performing wind resource parameter analysis to obtain a machine site wind resource evaluation result; s4, performing reduction and uncertainty analysis based on the wind resource evaluation result of the machine site, and calculating the generating capacity; and S5, generating a wind resource assessment report according to the power generation amount calculation result and the project basic information. According to the method, the wind resource state of each machine site in the wind field can be evaluated more accurately.

The invention discloses a yaw control method based on data driving and multi-objective optimization, and the method comprises the steps: dividing a wind speed interval: according to the wind resource characteristics, yaw behavior, wind direction distribution characteristics, wind speed frequency distribution, turbulence intensity in different wind speed intervals, and the influence of a yaw deviation angle on output power in different wind speed intervals of a mountain wind power plant, determining the wind speed interval of the mountain wind power plant; the wind speed range below the rated wind speed is divided into a low-speed stable interval of 3-6 m / s, a medium-speed optimization interval of 6-8 m / s and a high-speed balance interval of 8-11 m / s. A data driving and multi-objective optimization algorithm is adopted, so that the yaw system can flexibly adjust yaw control parameters in real time according to dynamic changes of the wind speed, the wind direction and the turbulence intensity. No matter whether the wind direction changes suddenly or the turbulence intensity fluctuates, the yaw system can make a response rapidly, and it is ensured that the wind turbine generator is in the best windward state all the time.

The invention belongs to the technical field of wind power plants, and discloses a point location information determination method and device, equipment, a storage medium and a product. The method comprises the following steps: clustering a plurality of to-be-queried point locations in an available land parcel of a wind power plant to obtain a target clustering center, then constructing a triangulation network by taking the target clustering center as a vertex, and determining an affiliation relationship between the plurality of to-be-queried point locations and triangles in the triangulation network; and determining wind speed and wind direction information corresponding to the plurality of to-be-queried point locations according to the target wind speed and wind direction information corresponding to the target clustering center and the affiliation relationship. The multiple to-be-queried points are clustered, the number of the points needing to be queried through the wind resource interface is reduced, then the wind speed and wind direction information corresponding to the multiple to-be-queried points is determined according to the target wind speed and wind direction information corresponding to the target clustering center and the affiliation relation, and therefore under the condition that the number of query times of the wind resource interface is limited, the query efficiency of the wind resource interface is improved. The wind speed and wind direction information of a large number of to-be-queried point locations in available plots is effectively and accurately determined through a clustering center query method.

The invention belongs to the technical field of power distribution cabinets, and particularly relates to a novel industrial energy-saving low-voltage intelligent power distribution cabinet based on an intelligent power grid, the novel industrial energy-saving low-voltage intelligent power distribution cabinet comprises a cabinet body, a heat dissipation assembly, a wind power detection assembly and an adjusting assembly, the heat dissipation assembly comprises a fan, and the adjusting assembly comprises a controller arranged in the cabinet body and electrically connected with the fan; the first rod is arranged in the cabinet body; the square rod is installed on the cabinet body in a sliding mode, a pressure sensor is arranged on the square rod, the pressure sensor is located between the square rod and the first rod and connected with the controller, the wind power detection assembly is used for sensing external wind power and converting the external wind power into mechanical displacement so as to drive the square rod to move, and the movement amount of the wind power detection assembly is related to the wind power; through cooperation of the wind power detection assembly and the pressure sensor, the rotating speed of the fan can be dynamically adjusted according to the strength of external natural wind power, abundant natural wind resources in coastal areas are utilized to assist heat dissipation to the maximum extent, and invalid energy consumption of the fan is remarkably reduced under the condition that the heat dissipation effect is not changed.

A small breeze capturing power generation device comprises a transmission vertical rod, a power generation mechanism and a plurality of fan blades, the fan blades are detachably installed at the upper end of the transmission vertical rod, the lower end of the transmission vertical rod is in transmission connection with the power generation mechanism, and the periphery of the transmission vertical rod is concentrically sleeved with a plurality of wind gathering ring covers from top to bottom in the axial direction of the transmission vertical rod. The diameters of the multiple air gathering ring covers are gradually reduced from top to bottom, the multiple air gathering ring covers are connected at intervals through multiple connecting inclined plates distributed in the circumferential direction of the multiple air gathering ring covers, and the multiple air gathering ring covers are each in a horn shape with the opening large end distributed downwards. The wind power generation device is convenient to install, can generate power by utilizing breeze resources, and improves the power generation efficiency.

The invention discloses a wind resource prediction method based on multi-scale spatio-temporal feature fusion, and belongs to the technical field of wind resource prediction, and the method comprises the steps: converting a historical wind speed and wind direction sequence of a target fan from a one-dimensional time sequence into a multi-scale two-dimensional time sequence through employing a constructed short-term wind resource prediction model, extracting intra-period-week time characteristics of the two-dimensional time sequence to obtain an initial wind speed prediction result and a final wind direction prediction result of the target fan; and on the basis of the initial wind speed prediction result, selecting an upstream wind turbine advanced sequence section of the target wind turbine according to the geographic position and the real-time wind direction of the wind turbine, and further optimizing the initial wind speed prediction result to obtain a final wind speed prediction result. The method has important practical significance for formulating a wind energy capturing strategy of the wind turbine generator and dispatching and operating a power grid, and is suitable for future power system operation and other practical applications.

The application discloses a kind of wind power resource drought degree evaluation method and related equipment.The method comprises: obtaining the hourly wind speed data of target area in history and evaluation period, and determining hourly wind power output sequence in combination with wind turbine power curve;Based on historical wind power output sequence sample, determine reliable output reference value and recharge threshold value for each duration t based on the statistical distribution of historical sample of each duration t;Calculate the equivalent energy buffer capacity of system in the evaluation window for resisting wind power underproduction;Based on reliable output reference value and recharge threshold value, calculate power gap and power surplus hour by hour;According to the reliable reference gap power that is not satisfied by energy storage and energy storage energy state, calculate operating deficit;Based on equivalent energy buffer capacity and operating deficit, calculate wind power resource drought index.Can solve the problem of the shortcomings of the existing method for quantifying and analyzing wind power resource drought, including fixed threshold method, relative anomaly method and standardized index method.

The invention discloses a wind resource micro-siting method and system based on economy, and the method comprises the steps: obtaining the spatial geographic information and long-sequence meteorological data of a target wind power plant, and the geographic constraint information of a wind power prohibited construction region, and constructing a high-resolution three-dimensional geographic information system platform; based on the three-dimensional geographic information system platform, wind resource refined evaluation is carried out, whole-field wind energy distribution parameters and single-station theoretical wind energy parameters are obtained, and the wind energy distribution parameters at least comprise wind speed Weibull distribution parameters and a wind direction rose diagram; an optimization objective function of micro-siting is defined, and compliance risks are avoided from the source by taking a construction forbidding area as a rigid constraint to be embedded in an optimization model; and high-precision terrain and meteorological data are fused in a three-dimensional geographic information platform, and wind field high-resolution numerical simulation based on a computational fluid mechanics principle is performed, so that the precision of wind resource space-time distribution evaluation in a complex terrain is remarkably improved.

The embodiment of the invention provides a wind driven generator array cooperative yaw scheduling method, electronic equipment and a system. The wind driven generator array cooperative yaw scheduling method comprises the following steps: acquiring arrangement parameters of a wind driven generator array; the real-time wind condition of the area where the wind driven generator array is located is obtained; based on the arrangement parameters of the wind driven generator array and the real-time wind condition of the area where the wind driven generator array is located, clustering the wind driven generator array in real time; by taking maximization of the total generated power in the real-time cluster of the wind driven generator as a target, obtaining a real-time optimal yaw angle of each single wind driven generator in the real-time cluster of the wind driven generator; and based on the real-time optimal yaw angle of each wind driven generator monomer in the wind driven generator real-time cluster, controlling each wind driven generator monomer to execute yaw action. According to the method, the overall generating capacity of the wind driven generator array can be effectively improved, and the utilization efficiency of wind resources and the economical efficiency of a wind power plant are improved.

The present application provides a turbulence intensity calculation method, model training method, device, equipment, and medium, relating to the field of wind power generation. The turbulence intensity calculation method includes: obtaining measured geographic data and measured wind resource data from a remote sensing wind sensing device; inputting the measured geographic data and measured wind resource data into a pre-established wind speed standard deviation conversion model to obtain the target wind speed standard deviation of the wind tower; and calculating the turbulence intensity at the location of the remote sensing wind sensing device based on the target wind speed standard deviation of the wind tower. Utilizing the technical solution of the present application can improve the accuracy of executing business operations using turbulence intensity obtained from a remote sensing wind sensing device.

The present application belongs to the technical field of new energy distribution network planning and operation optimization, and discloses a kind of energy storage multi-point site selection and capacity determination and operation collaborative optimization method for island high proportion new energy distribution network, which combines island area coastal wind resource characteristics, photovoltaic output characteristics, island area load spatial distribution characteristics and actual network frame constraint conditions of distribution network, constructs multi-representative day source network load scene of target year, carries out energy storage multi-point site selection and capacity determination on two layers of candidate positions of node level and station level, and carries out operation evaluation on different energy storage configuration schemes through daily scheduling model with network frame constraint, simultaneously introduces key load supply guarantee evaluation under power failure scene, realizes the collaborative optimization of conventional operation economy, new energy consumption capacity and power supply resilience. It can obtain the optimal configuration scheme of energy storage meeting the network frame constraint according to the localization characteristics of new energy output and load demand in island area, effectively reduce system purchase power and surplus new energy sending pressure, and improve the key load guarantee capacity under power failure condition.