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Intelligent control method for windmill generator yaw system

A wind turbine and yaw system technology, applied in the control of wind turbines, wind turbines, wind power generation, etc., can solve the problems of not having the learning function, unable to process and describe fuzzy information, etc.

Active Publication Date: 2009-12-09
CHINA ELECTRIC POWER RES INST +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Fuzzy control has the ability to process fuzzy language information, but does not have the learning function; artificial neural network, on the contrary, has the learning function, but cannot process and describe fuzzy information

Method used

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  • Intelligent control method for windmill generator yaw system
  • Intelligent control method for windmill generator yaw system
  • Intelligent control method for windmill generator yaw system

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Experimental program
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Embodiment Construction

[0042] An artificial neuron is equivalent to a multi-input single-output nonlinear threshold device, which has three basic elements:

[0043] ① A set of connection weights, corresponding to the synapses of biological neurons;

[0044] ②A summation unit, used to obtain the weighted sum of each input information;

[0045] ③ A nonlinear activation function, which acts as a nonlinear mapping and limits the neuron output within a certain range.

[0046] In addition, there is a threshold θ j , the input-output relationship of a single neuron is:

[0047] I j = Σ p = 1 n w jp x p - θ ...

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Abstract

The invention combines fuzzy control with neural network, and provides an intelligent control method for a windmill generator yaw system. By using the fuzzy control, the windmill generating yaw system is controlled with better dynamic performance and robustness by effectively compositing the experience and knowledge of experts without precious mathematic models. In addition, the self-learning function of neuron algorithm is used for automatically extracting the fuzzy rules of fuzzy control and optimizing membership function. The method organically combines the fuzzy control theory and neural network and has the advantages of making the best of each other and effectively improving the control capability of the yaw system.

Description

technical field [0001] The invention belongs to the field of automatic control of wind power generation, and in particular relates to an intelligent wind power generation yaw control based on fuzzy control and neuron algorithm. Background technique [0002] Large and medium-sized wind turbines generally use electric servos or steering motors to adjust the wind rotor and align it with the wind direction. The yaw system generally includes a wind vane that senses the wind direction, a yaw motor, a yaw planetary gear reducer, a large gear of the gyratory body, etc. The yaw system uses the wind vane as the sensing element to transmit the electrical signal of the change of wind direction to the control circuit of the yaw motor. After comparison, the processor sends a clockwise or counterclockwise yaw command to the yaw motor to drive the wind wheel to yaw. Against the wind, when the wind is completed, the wind vane loses the electrical signal, the motor stops working, and the yaw...

Claims

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Application Information

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IPC IPC(8): F03D7/00
CPCY02E10/723Y02E10/72
Inventor 王志凯宋洁
Owner CHINA ELECTRIC POWER RES INST
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