Wake flow calculation method and device based on bivariate Gaussian function and storage medium

A technology of Gaussian function and calculation method, which is applied in the field of wind turbine wake calculation, which can solve the problem of inconsistent Gaussian distribution assumptions, and achieve the effect of accurate calculation results.

Pending Publication Date: 2021-10-22
HUANENG NEW ENERGY CO LTD +1
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Problems solved by technology

However, the results of high-precision numerical simulations show that the recovery speed of the velocity loss in the two directions

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  • Wake flow calculation method and device based on bivariate Gaussian function and storage medium
  • Wake flow calculation method and device based on bivariate Gaussian function and storage medium
  • Wake flow calculation method and device based on bivariate Gaussian function and storage medium

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Embodiment Construction

[0031] The present invention will be further described in detail with the accompanying drawings and specific embodiments below, which are explanations rather than limitations of the present invention.

[0032] The wake calculation method based on the bivariate Gaussian function of the present invention includes:

[0033] S1: Obtain the incoming flow velocity U in front of the wind turbine according to the field measurement data ∞ , spanwise turbulence intensity I y , vertical turbulence intensity I z , the hub height z of the wind turbine h , impeller diameter D and thrust coefficient C t .

[0034] S2: Assuming that the dimensionless wake velocity deficit is a bivariate Gaussian function, calculate the wake expansion coefficient k in the bivariate Gaussian function y and k z , wake expansion coefficient k y = γ y I y , k z = γ z I z , where γ y and gamma z is the empirical coefficient, generally, 0.2≤γ y ≤1, 0.2≤γ z ≤1.

[0035] S3: Calculate the initial wake...

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Abstract

The invention discloses a wake flow calculation method and device based on a bivariate Gaussian function and a storage medium, and belongs to the technical field of wind turbine generator wake flow calculation. The method comprises the following steps: according to field measurement data, obtaining incoming flow speed, spanwise turbulence intensity and vertical turbulence intensity in front of the wind turbine generator, and hub height, impeller diameter and thrust coefficient of the wind turbine generator; calculating to obtain a wake flow expansion coefficient; calculating an initial wake flow radius according to the wake flow expansion coefficient; according to the obtained wake flow expansion coefficient and the initial wake flow radius, calculating the spanwise and vertical wake flow radiuses; and according to the obtained wake flow radiuses in the spanwise direction and the vertical direction, obtaining the speed loss of the wake flow area. The hypothesis adopted by the method is closer to the actual development characteristic than the hypothesis of a traditional wake flow calculation method, so that the wake flow calculation method provided by the invention can better predict the speed of the wake flow center point, and the spanwise and normal wake flow speed evolution laws can be given.

Description

technical field [0001] The invention belongs to the technical field of wind turbine wake calculation, and in particular relates to a wake calculation method, device and storage medium based on a bivariate Gaussian function. Background technique [0002] In recent years, wind power technology has made great progress, and the cost of power generation has been reduced rapidly. At present, it has reached the level of competition with conventional thermal power technology. Low-cost green energy such as wind power will gradually replace traditional fossil energy and occupy a more central position in the energy system. In order to achieve larger-scale power generation, wind power planning is moving towards an intensive and base-based development path, which leads to more significant wake effects of wind turbines, affecting the power generation of the entire wind farm and the fatigue load of each unit. However, from the perspective of scientific research and engineering application...

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Application Information

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IPC IPC(8): G06F30/17G06F30/28G06F113/06G06F113/08G06F119/14
CPCG06F30/17G06F30/28G06F2113/06G06F2113/08G06F2119/14
Inventor 程瑜郭辰李芊邵振州张庆张国曾利华李家川冯笑丹李东辉刘铭冯翔宇王森许社忠
Owner HUANENG NEW ENERGY CO LTD
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