Method and device for identifying frequency and damping ratio of main components of wind power generator

Abstract

The invention discloses a method and device for identifying frequency and damping ratio of main components of wind power generator. The method comprises the following steps of: obtaining the input data and output data of the main components of a wind power generator system, and using the input and output data respectively as the input and output of a fan model established by nonlinear system identification; calculating the model parameters of the fan model and a transfer function of the main components; calculating the pole of the transfer function, obtaining a first frequency range, performing power spectrum analysis on the output data of the main components, obtaining a second frequency range, and narrowing the range of the first frequency range by using the second frequency range to obtain the frequency iteration range; calculating the amplitude corresponding to each frequency in the frequency iteration range, and obtaining the maximum amplitude, the target frequency corresponding to the maximum amplitude and the target pole p, calculating the damping ratio of the main components by formula as shown in the specification. The above technical solution disclosed in the present application can improve the accuracy of frequency and damping ratio identification of main components, and the identification method is simple and easy to operate.

Description

technical field [0001] The present invention relates to the technical field of wind power generation, and more specifically, to a method, device, equipment and computer-readable storage medium for identifying the frequency and damping ratio of main components of a wind power generating set. Background technique [0002] The wind turbine system consists of multiple components, the main components include blades, towers, drive chains, gearboxes, pitch systems, etc. When building a wind turbine simulation model, the precise setting of the main component parameters is crucial for model simulation. In addition, before a major fault occurs in the wind turbine, the frequency and damping ratio of the main components will change. Accurate monitoring and identification of the frequency and damping ratio of the main components of the wind turbine can predict the fault in advance, so that it is convenient for wind power generation in advance. The unit is inspected to reduce the failure...

AI Technical Summary

Problems solved by technology

Since the data model obtained by this method has been simplified, there will be a relatively large gap between it and the actual model, which will reduce the accuracy of identification, and this method is complex to operate and requires a large amount of calculation.

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