Disclosed is a wind turbine layout optimization method combining with a dispatching strategy for the wind farm. In the wind farm micro-siting stage, the installed wind turbines number and the arrangement positions are optimized. In this method, the dispatching strategy of wind turbines is considered during the layout optimization of wind turbines, and the axial induction factor of each wind turbine is introduced into the layout optimization variables. The dispatching strategy of maximizing the wind farm power generation is combined with the layout optimization of wind turbines in the construction stage of the wind farm, so that the wake effect is effectively reduced and the capacity cost is reduced, which meet the requirement of actual wind farm. A hybrid optimization algorithm is proposed in this method, with a greedy algorithm to optimize the turbine number and a particle swarm optimization (PSO) algorithm to refine the turbine layout scheme.

Disclosed is a wind turbine layout optimization method combining with a dispatching strategy for the wind farm. In the wind farm micro-siting stage, the installed wind turbines number and the arrangement positions are optimized. In this method, the dispatching strategy of wind turbines is considered during the layout optimization of wind turbines, and the axial induction factor of each wind turbine is introduced into the layout optimization variables. The dispatching strategy of maximizing the wind farm power generation is combined with the layout optimization of wind turbines in the construction stage of the wind farm, so that the wake effect is effectively reduced and the capacity cost is reduced, which meet the requirement of actual wind farm. A hybrid optimization algorithm is proposed in this method, with a greedy algorithm to optimize the turbine number and a particle swarm optimization (PSO) algorithm to refine the turbine layout scheme.

A method of modeling an equivalent wind turbine generator (WTG) system for a wind farm having a plurality of WTG units includes determining an impact factor of each WTG unit of the plurality of WTG units, determining an equivalent single WTG unit model parameters of the wind farm based on the impact factor of each WTG unit, and determining an effective wind speed of the wind farm to use as the equivalent WTG input wind speed. The method produces a model of static and/or dynamic wind farm behavior. Additionally, a software configured to execute a method of modeling an equivalent wind turbine generator (WTG) system for a wind farm having a plurality of WTG units.

Disclosed is a digital twinning method for monitoring an operation state of a tower of a wind turbine generator system online. The method includes: 1) constructing a simplified model of the tower of the wind turbine generator system, and discretizing the simplified model according to a finite element method to obtain a finite element model; 2) reducing an order of the finite element model of the tower according to proper orthogonal decomposition, analyzing precision of a reduced-order model under different orders, and selecting the reduced-order model having a smallest reduced order as a final reduced-order model on the premise that the precision satisfies actual engineering requirements; and 3) programming upper computer software in a computer, deploying the reduced-order model to the upper computer software, further building a physical entity of the tower, and monitoring a stress and a strain of the physical entity online through the reduced-order model.

A method and apparatus for evaluating vulnerability of monopile foundations of offshore wind turbines are provided. The method includes collecting offshore wind farm location data and wind-wave characteristic data, and simulating a wind-wave time course according to the offshore wind farm location data and the wind-wave characteristic data; determining a wind-wave dynamic load based on the wind-wave course; obtaining lateral soil resistance data of monopile foundations with a plurality of rock-soil strength parameters, and inputting the wind-wave dynamic load into a 3D finite element model; using the lateral soil resistance data of monopile foundations with a plurality of rock-soil strength parameters as boundary conditions of the 3D finite element model; and giving a limit state of monopile foundations, and determining vulnerability of monopile foundations on basis of the dynamic response result of the monopile foundations and the limit state of monopile foundations.

The disclosure discloses a numerical simulation method of an influence of a polytetrafluoroethylene (PTFE)-based membrane on an aerodynamic characteristic of a wind turbine blade, and relates to the technical field of polymer composites. The simulation method comprises the following steps: selecting a wind turbine generator, a blade airfoil and a PTFE-based nano functional membrane; setting a numerical simulation computation network and a computation area of a wind energy capture area; determining main computation parameters and a Reynolds number for aerodynamic characteristic computation; establishing a geometrical model whose airfoil boundary extends by 0.26 mm (membrane thickness) along a normal direction to obtain a new computational geometry; computing by using a hydrodynamic computation method and a finite volume method; and obtaining an influence number simulation computation result.

Techniques for conducting an air flow simulation for a wind turbine include importing a file containing a digitized representation of a three-dimensional blade geometry, extracting from the file, blade constructive parameters, and calculating a low-order air flow past a wind-turbine that includes the blade, based on a Blade Element Momentum Theory (BEMT) to determine sectional angle of attack and free-stream velocity, boundary layer transition, and acoustic noise results. The techniques also include performing air flow simulation for a given number of blade sections, and generating virtual microphone rings. The process also includes computing noise spectra at the virtual microphone rings and blending the noise spectra generated and generating synthetic noise signals from each section by inverse Fourier transform of the noise spectra and converting the noise spectra into an audio track.