SVR-based method for estimating effective wind speed of low-wind-speed section of wind power generating unit

Abstract

The invention discloses an SVR-based method for estimating an effective wind speed of a low-wind-speed section of a wind power generating unit. The method comprises the two steps of SVR model training and model online use. In the SVR model training process, a sensor is used to obtain a training characteristic set and a target set; the characteristic set is normalized to obtain an SVR training set; a PSO algorithm is used to select a penalty parameter and a kernel function parameter; and a trained effective wind speed estimation model is obtained. In the model online use process, output data of the unit is obtained in real time and is normalized and input to a trained SVR model, and after the data passes through a low-pass filter, a final effective wind speed estimation value is obtained. According to the method, the output data of the unit is fully utilized; effective wind speed estimation can be performed for the wind power unit of the low-wind-speed section; the design process is simple and easy to implement; and the obtained effective wind speed estimation value can be used for increasing wind energy utilization rate of the unit and reducing mechanical loads of the unit and wind resource assessment of a wind power plant, so that the economic benefits of the wind power plant are improved.

Description

technical field [0001] The invention relates to the technical field of control of wind power generators, in particular to the effective wind speed estimation in the low wind speed section of the wind power generators. Background technique [0002] Wind energy is a clean, low-cost renewable energy with great commercial potential. Wind power technology has developed by leaps and bounds in recent years. The World Wind Energy Association pointed out in the 2015 World Wind Energy Report that by 2020, the global installed capacity of wind power will reach 792.1GW. However, the development of wind power technology still faces challenges such as high operation and maintenance costs of large-scale units, low utilization rate of wind energy, and difficulty in connecting large-scale wind power to the grid. Therefore, it is of great practical significance to develop a method for estimating the effective wind speed of wind turbines to reduce the operating load of wind turbines and impro...

AI Technical Summary

Problems solved by technology

[0006] In order to make full use of the output data of wind turbines and solve the problem that the wind speed estimation method of the existing wind turbines has a large estimation error and cannot be used in practice due to the lack of corresponding control strategies for the wind turbines, the present invention provides a simple The method for estimating the effective wind speed of a wind turbine that is easy to implement and does not require the use of a system mathematical model can make full use of the output data of the unit and more accurately establish the nonlinear relationship between the output data of the unit and the effective wind speed, and the estimated value of the effective wind speed can be obtained as The maximum wind energy capture of the unit provides the control target, which can be applied to reduce the mechanical load of the unit and the wind resource assessment of the wind farm

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