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Method for improving prediction precision of Gaussian wake flow model on wind turbine wake flow field

A wake model and prediction accuracy technology, which is applied in computer-aided design, special data processing applications, instruments, etc., can solve the problem that the Gaussian wake model has a greater impact on the velocity prediction accuracy in the wake area and the lack of universality of the initial standard deviation coefficient. question

Inactive Publication Date: 2021-04-09
CHINA THREE GORGES CORPORATION
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Problems solved by technology

[0004] The purpose of the present invention is to start from improving the universality of the initial standard deviation coefficient, by improving the acquisition means of the initial standard deviation coefficient, thereby improving the accuracy of the initial standard deviation coefficient obtained, and solving the initial standard deviation caused by adopting conventional methods. The lack of generality of the deviation coefficient will greatly affect the technical problem of the prediction accuracy of the Gaussian wake model on the velocity of the wake area in different environments

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  • Method for improving prediction precision of Gaussian wake flow model on wind turbine wake flow field
  • Method for improving prediction precision of Gaussian wake flow model on wind turbine wake flow field
  • Method for improving prediction precision of Gaussian wake flow model on wind turbine wake flow field

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Embodiment

[0094] Take a numerically simulated wind turbine as an example, such as Figure 2 to Figure 4 shown;

[0095] 1) Extract the thrust coefficient C of the wind turbine T ;

[0096] For a certain wind turbine, its thrust coefficient is set to C T =0.8;

[0097] 2) Calculate the proportional coefficient β;

[0098] Calculate the proportional coefficient β according to formula (7), and obtain β=1.618;

[0099] 3) Calculate the initial standard deviation coefficient ε;

[0100] Calculate the initial standard deviation coefficient ε according to formula (12), and obtain ε=0.2465;

[0101] 4) Calculate the standard deviation σ;

[0102] The diameter of the rotor of the wind turbine is D 0 =80m, standard deviation diffusion coefficient k B =0.055, flow direction distance x / D 0 The value range of is 2 to 15, and the standard deviation σ is calculated according to formula (13), and the calculation result is as follows figure 2 shown. In addition, the standard deviation and n...

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Abstract

The invention discloses a method for improving the prediction precision of a Gaussian wake flow model on a wind turbine wake flow field. The method comprises the following steps: step 1) obtaining a thrust coefficient of a wind turbine; 2) obtaining a proportionality coefficient; 3) obtaining an initial standard deviation coefficient; 4) acquiring standard deviation; step 5) combining a Gaussian wake flow model to obtain the speed loss of a wake flow area; the invention aims to improve the precision of the obtained initial standard deviation coefficient by improving the obtaining means of the initial standard deviation coefficient from the aspect of improving the universality of the initial standard deviation coefficient, and solves the problems that the universality of the initial standard deviation coefficient obtained by adopting a conventional method is insufficient, therefore, the technical problem that the Gaussian wake flow model has great influence on the prediction precision of the wake flow area speed in different environments is solved.

Description

technical field [0001] The invention relates to the technical field of wind power generation, in particular to a method for improving the prediction accuracy of a Gaussian wake model for a wind turbine wake field, which can be used in wind farm wake evaluation and microscopic site selection. Background technique [0002] In the field of wind power generation, after the free flow flows through the wind turbine, because the wind turbine absorbs a part of the energy of the incoming flow, the wind speed will decrease and the turbulence degree will increase downstream of the wind turbine. The area where this phenomenon occurs is called wake area. Due to the decrease of wind speed and the increase of turbulence in the wake area, the power generation of wind turbines in the wake area decreases, and the fatigue load increases, which seriously affects the investment income of wind farms. Therefore, wake assessment is one of the most important links in wind farm micro-site selection ...

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Application Information

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IPC IPC(8): G06F30/17G06F30/20G06F113/06G06F119/14
CPCG06F30/17G06F30/20G06F2113/06G06F2119/14
Inventor 张子良易侃张皓王浩
Owner CHINA THREE GORGES CORPORATION
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