Wake flow calculation method considering local environmental factors of wind power plant

Abstract

The invention discloses a wake flow calculation method considering local environmental factors of a wind power plant, and belongs to the technical field of wind turbine generator wake flow calculation. Firstly, local environment parameters of a wind power plant are obtained according to the local environment of the wind power plant, then an atmospheric stability function of the environment where the wind power plant is located is calculated, the obtained atmospheric stability function serves as input, and the earth surface friction speed is calculated through the MoninObukhov similarity theory. Then sequentially calculating to obtain the flow velocity pulsation of the near-stratum, the flow turbulence intensity of the near-stratum and the spanwise turbulence intensity of the near-stratum,and establishing a direct proportion relationship between the spanwise turbulence intensity of the hub height and the spanwise turbulence intensity of the near-stratum to obtain the spanwise turbulence intensity of the hub height; sequentially calculating to obtain a wake flow expansion coefficient, an initial wake flow radius and a wake flow radius, calculating a wake flow region speed loss thickness, and finally obtaining the speed distribution of the wake flow region. According to the method, the application range of the wake flow calculation method is greatly expanded, and the accuracy ofa calculation result 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 wake calculation method considering local environmental factors of a wind farm. Background technique [0002] At present, the most widely used wind turbine wake calculation method in engineering is the linear wake model developed by Jensen et al. The model is based on the following two assumptions, one is that the width of the wake increases linearly with the distance from the downstream of the wind turbine, and the other is that the velocity in the plane of the wake perpendicular to the axis of the wind turbine is uniformly distributed (Top-hat assumption). Pena et al. compared the Jensen model with the measured data of Sexbierum and the CFD simulation results, and found that there was a large gap between the speed predicted by the Jensen model and the actual situation. They believed that a more advanced wake model should be developed...

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Problems solved by technology

[0003] From the above analysis, it can be seen that the wake expansion radius in the Gaussian wake model needs to be determined by empirical formulas. It is generally believed that the model parameters included in the wake expansion radius are related to the flow turbulence intensity, while the wind turbine wake is mainly in the vertical direction. direction and lateral expansion, so it is not reasonable to relate model parameters to flow direction turbulence intensity

In addition, it is very difficult to obtain accurate turbulence intensity in actual wind farms. Errors in calculating turbulence intensity usually lead to inaccurate calculation of model parameters, resulting in inaccurate prediction of wake velocity deficit

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