CFD Techniques for Reducing Wind Turbine Noise

Characterizing vortex wake losses in wind turbine blades using an effective energy analysis method. The method involves simulating flow through the blades to calculate the effective energy balance. By tracking the effective energy throughout the system, losses due to irreversible processes like vortex shedding can be quantified. This provides a more comprehensive analysis of blade energy losses compared to just measuring power output or blade forces.

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Method, equipment, and computer program for analyzing wind farm noise more accurately by considering the external environment impact on blade noise. It involves modeling and analyzing the entire wind farm instead of just individual blades. This allows accounting for factors like terrain, wind speed, vegetation that affect noise propagation. The method obtains virtual models and wind farm data for blades, determines the calculation domain, and solves numerically to obtain surface noise distribution. This improves blade noise analysis accuracy compared to single blade simulations.

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Representing rotating blade noise in a wind turbine using computer simulations to optimize blade design and reduce noise levels without expensive blade prototyping. The method involves importing 3D blade geometry, extracting blade parameters, computing airflow using blade momentum theory, and repeating simulations at multiple rotations to capture blade passage effects. The noise is calculated in the blade rotation frame of reference using scale-resolved CFD simulations covering a small fraction of a revolution. This allows statistical convergence by compensating for accurate noise signals over multiple rotations. The noise is then combined, corrected, and applied ground reflection/absorption/atmospheric absorption to represent rotating blade noise in the wind turbine.

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Computer method for accurately representing wind turbine blade noise using 2.5D simulations and blending to create realistic audio tracks. The method involves extracting blade geometry parameters and sectional flow data, simulating airflow past sections, computing noise spectra, blending spectra over a rotor revolution, synthesizing audio signals, and applying Doppler correction and absorption effects. This allows recovering blade noise over multiple revolutions by using 2.5D simulations covering a small portion of the rotor and blade.

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Optimal design method for wind turbine blades with high aerodynamic efficiency and low noise levels. It involves using a dual-objective optimization approach to find wind turbine blade airfoils with both high lift-to-drag ratios and low noise levels. The optimization targets are the maximum lift-to-drag ratio and total noise pressure level. Constraints ensure the airfoil meets other important aerodynamic requirements like lift coefficient, maximum lift coefficient, stall characteristics, and roughness stability.

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Aerodynamic optimization method for wind turbine airfoils that considers the effect of high turbulent free flow. The optimization aims to find airfoils with lower sensitivity to free flow turbulence, which is important for wind turbines operating in turbulent environments. The method involves iterative optimization using CFD simulation to find airfoils with lower sensitivity to high turbulence levels compared to low turbulence. It considers the relative change in aerodynamic coefficients between high and low turbulence conditions as a sensitivity metric.

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Design method for improving aerodynamic performance of wind turbine blades with thick airfoils that stall easily. The method involves optimizing the suction side profile of the airfoil using a simulated annealing multi-objective evolutionary algorithm to find a profile that improves lift-to-drag ratio both before and after stall compared to the original airfoil. The algorithm calculates aerodynamic performance using fluid simulation software like Fluent. The optimized airfoil, named WT-E-300, was found to have better stall characteristics compared to the standard DU97-W-300 airfoil.

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Quasi-three-dimensional linear calculation method for interference single-tone noise of turbine blade rows to improve turbine noise prediction capabilities for aeroengine design. The method involves segmenting the blade rows to account for large turning angles, linearizing the calculation by treating the segments as separate blades, using modified wake models for turbine blades, and applying pipe acoustics theory for propagation and cutoff. This allows applying aeroengine design tools like strip theory to turbine noise analysis.

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Method to design wind turbine blades for strong winds using numerical simulation. The method involves using existing aircraft airfoil data for wind turbine blades due to lack of specialized wind turbine airfoil data. The simulation involves selecting appropriate grid types, grid densities, time-space dispersion, numerical formats, algorithms, iterations, turbulence models, calculation domains, and rotation domains to accurately model wind turbine blades under strong winds. The simulation aims to optimize blade shape for reduced damage and improved performance in high wind conditions.

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Method for increasing power generation of high-altitude wind turbines by optimizing blade design and tip speed ratios. The method involves using optimization algorithms to find the best blade tip speed ratios for each wind turbine in a high-altitude wind farm. This maximizes wind energy capture and power generation at lower air densities found at high altitudes. By optimizing the tip speed ratios, it allows the blades to capture more wind energy at lower speeds where air density is lower, compared to sea level conditions. This compensates for the reduced aerodynamic performance due to lower air density at high altitude.

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Determining structural parameters of airfoils for wind turbine blades that have lower sensitivity to leading edge roughness. The method involves optimizing airfoil geometry using a design objective function that includes roughness sensitivity metrics along with constraints like stall point. Iterative optimization determines the target airfoil geometry to improve smooth surface performance while reducing roughness sensitivity compared to the initial airfoil. This provides an airfoil with better aerodynamics and noise when the blade surface is rough, like at wear prone outer sections.

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Rapid method for predicting aerodynamic noise of wind turbines that provides a faster and more accurate way to calculate wind turbine noise compared to traditional methods. The method involves breaking down the wind turbine blade into elements along the span direction. It calculates the effective incoming wind speed and angle of attack for each element using blade element momentum theory and models. This data is then used to calculate the wall pressure spectrum and boundary layer parameters using a software tool. The airfoil trailing edge noise model and turbulent incoming flow noise are applied to each element to calculate the sound pressure level or power level. Superimposing the results from all elements gives the overall wind turbine noise.

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Optimizing power generation of wind turbines operating in low air density environments by strategically placing vortex generators on the blades. The method involves using numerical simulation and optimal control algorithms to determine the best vortex generator shape and position that maximizes power output. The optimization considers factors like blade deformation, yaw effects, and dynamic inflow conditions to balance lift coefficient, tip speed ratio, and stability. The goal is to maintain optimal power generation after installing vortex generators on blades operating in low density air.

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Simulating wind turbine wake distributions for wind farms with high accuracy, efficiency, and timeliness using CFD pre-calculation. Instead of running CFD simulations for each wind speed in real-time, the method involves pre-calculating the wake distributions at multiple wind speeds using CFD. These calculated wake distributions are stored in a database. To simulate the wake for a specific wind speed, the database is interpolated using the known wind speed as input. This allows fast, accurate wake simulation by avoiding repetitive CFD calculations for each wind speed.

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A method for designing low-noise wind turbine blades that balances power output and noise levels. The method involves optimizing chord length and twist distribution to increase power while reducing blade noise. The optimization uses a blade noise model, turbulence model, and load constraints. It calculates noise and power for each blade section, then iteratively adjusts chord and twist to maximize power-to-noise ratio.

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Optimizing the design of wind turbine blades to improve aerodynamic performance and reduce noise in low wind speed regions. The optimization method aims to achieve high lift-to-drag ratio and low noise levels for wind turbine blades operating in areas with low wind speeds. The optimization involves using a dual-objective, multi-condition optimization algorithm to find the optimal airfoil shape. The objectives are maximizing lift-to-drag ratio and minimizing total noise pressure level. Constraints include limiting the design lift coefficient, maximum lift coefficient, and stability parameters to ensure other important aerodynamic characteristics like stall behavior and sensitivity to roughness and turbulence.

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A 25% thick airfoil design for wind turbine blades that provides higher lift and better performance compared to conventional airfoils. The airfoil has a relative thickness of 0.25 chord, maximum thickness of 0.325 chord, and trailing edge thickness of 0.09 chord. It was designed using computational fluid dynamics (CFD) and advanced airfoil parameterization methods. The thicker airfoil allows shorter blade lengths or higher lift for the same length, improving wind energy capture. The high thickness and lift also have better characteristics at high Reynolds numbers. The airfoil has insensitive lift at coarse sugar contents.

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