System identification method of wind power generating set based on rbf neural network technology
A technology for identification of wind turbines and systems, which is applied to wind turbines, neural learning methods, and control of wind turbines. It can solve the problems of complex operation, slow calculation speed, and poor stability of identification methods, and achieve low calculation and simple algorithms. , the effect of good running speed
Active Publication Date: 2019-03-05
ZHEJIANG WINDEY +2
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[0004] In order to overcome the deficiencies of the existing wind turbine system identification method, such as complicated operation, large amount of calculation, slow operation speed, and poor stability, the present invention provides a method that simplifies operation, has good operation speed and low calculation amount , better stability wind turbine system identification method based on RBF (Radical Basis Function) neural network technology
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[0062] The present invention will be further described below in conjunction with the accompanying drawings.
[0063] refer to Figure 1 ~ Figure 3 , a system identification method for wind power generators based on RBF neural network technology, said method comprising the following steps:
[0064] Step 1. Acquisition of data required for system identification:
[0065] According to the characteristics of the wind turbine system, the input data and output data required for identification are obtained; the sampling time is selected from the internal sampling time of the system; the input signal for torque loop identification is the generator torque T g , when the pitch ring is identified, the input signal is the blade pitch angle β, and the output data is the generator speed Ω;
[0066] Step 2. System identification based on RBF technology:
[0067] The wind turbine system is described as follows:
[0068] y(t)=G(p,q -1 )u(t)+v(t) (1)
[0069] in, G is the transfer funct...
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The invention provides a wind generating set system identification method based on the radial basis function (RBF) neural network technique. The wind generating set system identification method comprises the following steps that 1, data required by system identification are obtained, specifically, the input data and the output data which are required by identification are obtained according to the characteristics of a wind generating set system, the sampling time selects the system internal sampling time, an input signal is the generator torque Tg during torque loop identification and is the paddle pitch angle beta during propeller pitch loop identification, and the output data are the generator rotation speed omega; and 2, system identification is conducted based on the RBF technique, specifically, the wind generating set system is described, a torque loop or a propeller pitch loop is set as a nonlinear SISO system, a nonlinear extension autoregressive East China average model NARMAX is adopted for conducting describing, and the RBF neural network training process comprises the following steps that when a signal is forwards propagated, RBF neural network output is calculated, and when an error is reversely propagated, the weights among various layers of an RBF network are adjusted by adopting the delta learning algorithm. The wind generating set system identification method based on the RBF neural network technique has good operation speed, low calculation amount and good stability.
Description
technical field [0001] The invention relates to the technical fields of wind power generation, nonlinear system identification and intelligent control, in particular to a system identification method based on RBF neural network technology. Background technique [0002] The wind turbine system is a complex nonlinear time-varying system, and it is difficult to obtain an accurate mathematical model of the system. When the working conditions of the system change, the control effect of the conventional linear model control system will be reduced, and even affect the normal operation of the entire system. Therefore, it is of great significance to establish an accurate model of the system to provide a theoretical basis for optimizing wind turbines. [0003] To establish a wind turbine system model, the solution is to use a mechanism modeling method and a nonlinear system identification method. The mechanism modeling method is used, that is, various mathematical equations are used...
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IPC IPC(8): F03D7/02F03D7/04G06N3/08
CPCF03D7/0224F03D7/0276F03D7/046G06N3/084Y02E10/72
Inventor 马灵芝孙勇应有王杭烽
Owner ZHEJIANG WINDEY