Individual pitch control of wind turbine based on RBF neural network

2016 ◽  
Author(s):  
Zhongpeng Liu ◽  
Feng Huo ◽  
Shuowen Xiao ◽  
Xuesong Zhang ◽  
Shilong Zhu ◽  
...  
Keyword(s):  
Neural Network ◽  
Wind Turbine ◽  
Rbf Neural Network ◽  
Pitch Control ◽  
Individual Pitch Control

scholarly journals Based on RBF neural-network for individual pitch control of wind turbine

2015 ◽  
Vol 46 (3) ◽  
pp. 248-255 ◽  
Author(s):  
Hao CHEN ◽  
NingFeng DENG ◽  
LaWu ZHOU ◽  
Meng TIAN ◽  
Bing HAN
Keyword(s):  
Neural Network ◽  
Wind Turbine ◽  
Rbf Neural Network ◽  
Pitch Control ◽  
Individual Pitch Control

scholarly journals Pitch control of wind turbine based on deep neural network

2020 ◽  
Vol 619 ◽  
pp. 012034
Author(s):  
Wei Jie ◽  
Chu Jingchun ◽  
Yuan Lin ◽  
Wang Wenliang ◽  
Dong Jian
Keyword(s):  
Neural Network ◽  
Wind Turbine ◽  
Deep Neural Network ◽  
Pitch Control

Optimal tuning of multivariable disturbance‐observer‐based control for flicker mitigation using individual pitch control of wind turbine

2016 ◽  
Vol 11 (8) ◽  
pp. 1121-1128 ◽  
Author(s):  
Raja Muhammad Imran ◽  
Dil Muhammad Akbar Hussain ◽  
Mohsen Soltani ◽  
Raja Muhammad Rafaq
Keyword(s):  
Wind Turbine ◽  
Disturbance Observer ◽  
Pitch Control ◽  
Optimal Tuning ◽  
Individual Pitch Control

Field testing of multi-variable individual pitch control on a utility-scale wind turbine

2021 ◽  
Vol 170 ◽  
pp. 1245-1256
Author(s):  
Daniel Ossmann ◽  
Peter Seiler ◽  
Christopher Milliren ◽  
Alan Danker
Keyword(s):  
Wind Turbine ◽  
Field Testing ◽  
Pitch Control ◽  
Utility Scale ◽  
Individual Pitch Control

scholarly journals Lookup Table and Neural Network Hybrid Strategy for Wind Turbine Pitch Control

2021 ◽  
Vol 13 (6) ◽  
pp. 3235
Author(s):  
J. Enrique Sierra-García ◽  
Matilde Santos
Keyword(s):  
Neural Network ◽  
Wind Turbine ◽  
Control Strategy ◽  
Neural Control ◽  
Mapping Function ◽  
Energy System ◽  
Lookup Table ◽  
Hybrid Strategy ◽  
Pitch Control ◽  
The Neural Network

Wind energy plays a key role in the sustainability of the worldwide energy system. It is forecasted to be the main source of energy supply by 2050. However, for this prediction to become reality, there are still technological challenges to be addressed. One of them is the control of the wind turbine in order to improve its energy efficiency. In this work, a new hybrid pitch-control strategy is proposed that combines a lookup table and a neural network. The table and the RBF neural network complement each other. The neural network learns to compensate for the errors in the mapping function implemented by the lookup table, and in turn, the table facilitates the learning of the neural network. This synergy of techniques provides better results than if the techniques were applied individually. Furthermore, it is shown how the neural network is able to control the pitch even if the lookup table is poorly designed. The operation of the proposed control strategy is compared with the neural control without the table, with a PID regulator, and with the combination of the PID and the lookup table. In all cases, the proposed hybrid control strategy achieves better results in terms of output power error.

The Study of Individual Pitch Control on Reducing The Load Fluctuation of Tower Shadow

2011 ◽  
Vol 347-353 ◽  
pp. 2260-2267
Author(s):  
Wei Li ◽  
Hong Li Sun ◽  
Zuo Xia Xing ◽  
Lei Chen
Keyword(s):  
Wind Turbine ◽  
Linear Time ◽  
Pitch Control ◽  
Linear Time Invariant ◽  
Load Fluctuation ◽  
Pitch System ◽  
The Individual ◽  
Time Invariant ◽  
Individual Pitch Control ◽  
Tower Shadow

Load fluctuation of wind turbine under tower shadow was researched，introducing individual pitch control. First，establish the linear time-varying model of the rotor，make it into the linear time invariant model through Coleman transformation. Then，based on this model，achieving the design of individual pitch system with PID controller. Comparing the loads of wind turbine under tower shadow between individual pitch control and collective pitch control and analysing the fatigue damage of wind turbine through rainflow cycle counting.The result shows that load fluctuation of wind turbine using the individual pitch control under tower shadow has better effect and reduces the effect of tower shadow，extend the working life of wind turbine.

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