Spatial variation-based dynamic double-Gaussian wind turbine wake flow speed calculation method

Abstract

The invention discloses a spatial variation-based dynamic double-Gaussian wind turbine wake flow speed calculation method. The method comprises the following steps: determining a runner diameter and a thrust coefficient of a wind turbine, and calculating an initial wake flow radius; collecting an incoming flow wind speed of the wind turbine, determining an initial wake flow expansion coefficient, an exponent sign, and a radial distance between a wake flow wind speed minimum value point and a hub center line , and calculating an effective runner diameter; dividing a wake flow area of the wind turbine into a wake flow area close to a runner, a near wake flow area, and a far wake flow area, determining a corresponding wake flow expansion coefficient and an exponent sign, and calculating wake flow radius distribution in combination with the initial wake flow radius; establishing a wake flow unilateral Gaussian profile distribution function on the two sides of the center line of the hub, and calculating a wake flow double Gaussian distribution profile; calculating maximum normalized speed attenuation by combining an average momentum flow equation flowing through the runner and a thrust calculation formula, further calculating speed attenuation of the wake flow area, and determining speed distribution of the wake flow area. According to the invention, the accuracy of calculating wake flow wind speed distribution in a full wake flow area is improved.

Description

technical field [0001] The invention belongs to the technical field of wake flow calculation of wind turbines, and in particular relates to a method for calculating wake velocity of a dynamic double Gaussian wind turbine based on spatial variation. Background technique [0002] With the development of the field of wind power generation, the construction of wind farms is often accompanied by the placement of as many wind turbines as possible within a limited construction area. The influence of the wake flow will bring disadvantages to the power generation efficiency of wind farms. In view of this problem, it is necessary to study the wake effect in the wind farm and the countermeasures for the wake effect. The use of a simple and reliable engineering wake model can quickly and accurately predict the velocity distribution in the wake region, providing a guarantee for the performance optimization of wind farms. However, to use the engineering wake model to accurately calculat...

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Problems solved by technology

[0003] The wake models reported in the above literature all believe that the wake distribution is symmetrical at any downstream distance, but the CFD wake simulation results and actual measurement results show that the misalignment of the rotor surface of the wind turbine and the incoming wind, the pitch of the wind turbine or the wind force Due to factors such as the rotation of the rotor and the tower shadow effect, the wind speed loss on both sides of the wake center is uneven, which makes the wind speed distribution near the wake area present an asymmetrical double Gaussian distribution.

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