Large wind turbine variable pitch system identification method based on optimized RBF neural network

Abstract

The invention discloses a large wind turbine variable pitch system identification method based on an optimized RBF neural network. The method comprises the following steps that firstly, dynamic optimization improvement is carried out on a network structure by adopting an output sensitivity method on the basis of the traditional neural network identification algorithm technology, simulation software is adopted to control simulation to obtain experimental data by adopting a Bladed wind turbine from a great Britain company named Grarrad Hassan Partners, the wind speed v and the pitch angle beta are used as input signals, and the power generation power P serves as an output signal. Further, according to the system identification principle, a model and related measurement information are used for building an identification system framework. Secondly, the RBF is used for identifying the algorithm due to the strong nonlinear mapping capability of the neural network, under the excitation of asystem input signal, the identification system infinitely and approximately outputs the actual power output of the system. Finally, the problem that the network learning speed rate is difficult to select is solved, a gradient descent method and an optimization algorithm are provided, and the optimal learning speed rate of the network structure is derived. The method has high self-adaptive capacityand anti-interference capability, and has a certain practical value.

Description

technical field [0001] The invention belongs to the field of wind turbine pitch control and system identification, and specifically relates to an identification method for a wind turbine pitch nonlinear system. The method is an identification method for a large wind turbine pitch system based on an optimized RBF neural network. Background technique [0002] The pitch control of the wind turbine stabilizes the output power of the fan by changing the pitch angle to obtain wind energy to a greater extent. Compared with the fixed pitch, the variable pitch control can not only obtain wind energy to a greater extent, but also stabilize the power. output. The variable pitch execution system is an important part of the wind turbine. When the wind speed exceeds the rated wind speed of the wind turbine, the pitch system adjusts the captured wind energy by changing the pitch angle, so as to stabilize the output power of the wind turbine and maintain it around the rated value[ 1-2]. H...

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Problems solved by technology

A large-scale wind turbine pitch system identification method based on optimized RBF neural network is proposed, which has real-time adaptability and strong self-correction function, and effectively solves the influence of improper learning rate selection on the identification effect.

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