A Data-Driven Maintenance Support System for Wind Energy Conversion Systems

2014 ◽  
Vol 47 (3) ◽  
pp. 11470-11475 ◽  
Author(s):  
Minjia Krueger ◽  
Adel Haghani ◽  
Steven X. Ding ◽  
Torsten Jeinsch ◽  
Peter Engel
2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
T. Li ◽  
A. J. Feng ◽  
L. Zhao

Due to the uncertainty of wind and because wind energy conversion systems (WECSs) have strong nonlinear characteristics, accurate model of the WECS is difficult to be built. To solve this problem, data-driven control technology is selected and data-driven controller for the WECS is designed based on the Markov model. The neural networks are designed to optimize the output of the system based on the data-driven control system model. In order to improve the efficiency of the neural network training, three different learning rules are compared. Analysis results and SCADA data of the wind farm are compared, and it is shown that the method effectively reduces fluctuations of the generator speed, the safety of the wind turbines can be enhanced, the accuracy of the WECS output is improved, and more wind energy is captured.


2015 ◽  
Vol 48 (21) ◽  
pp. 633-638 ◽  
Author(s):  
Adel Haghani ◽  
Minjia Krueger ◽  
Torsten Jeinsch ◽  
Steven X. Ding ◽  
Peter Engel

2021 ◽  
Vol 13 (1) ◽  
pp. 013304
Author(s):  
İrfan Yazıcı ◽  
Ersagun Kürşat Yaylacı ◽  
Barış Cevher ◽  
Faruk Yalçın ◽  
Can Yüzkollar

2013 ◽  
Vol 28 (3) ◽  
pp. 756-767 ◽  
Author(s):  
Zakariya M. Dalala ◽  
Zaka Ullah Zahid ◽  
Wensong Yu ◽  
Younghoon Cho ◽  
Jih-Sheng Lai

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