Protection algorithm for a wind turbine generator in a large wind farm

2011 ◽  
Author(s):  
T. Y. Zheng ◽  
Y. H. Kim ◽  
P. A. Crossley ◽  
Y. C. Kang
Keyword(s):  
Wind Turbine ◽  
Wind Farm ◽  
Turbine Generator ◽  
Wind Turbine Generator ◽  
Large Wind

scholarly journals Protection for a Wind Turbine Generator in a Large Wind Farm

2011 ◽  
Vol 6 (4) ◽  
pp. 466-473 ◽  
Author(s):  
Tai-Ying Zheng ◽  
Yeon-Hee Kim ◽  
Yong-Cheol Kang
Keyword(s):  
Wind Turbine ◽  
Wind Farm ◽  
Turbine Generator ◽  
Wind Turbine Generator ◽  
Large Wind

Grid Tripping and Re-connection: Full-scale Experimental Validation of a Dynamic Wind Turbine Model

2003 ◽  
Vol 27 (3) ◽  
pp. 205-213 ◽  
Author(s):  
Niels Raben ◽  
Martin Heyman Donovan ◽  
Erik Jørgensen ◽  
Jan Thisted ◽  
Vladislav Akhmatov
Keyword(s):  
Wind Turbine ◽  
Wind Power ◽  
Wind Farm ◽  
Power Grid ◽  
System Stability ◽  
Turbine Generator ◽  
Wind Turbine Generator ◽  
Shaft System ◽  
The Impact ◽  
Turbine Model

An experiment with tripping and re-connecting a MW wind turbine generator was carried out at the Nøjsomheds Odde wind farm in Denmark. The experimental results are used primarily to validate the shaft system representation of a dynamic wind turbine model. The dynamic wind turbine model is applied in investigations of power system stability with relation to incorporation of large amounts of wind power into the Danish power grid. The simulations and the measurements are found to agree. The experiment was part of a large R&D program started in Denmark to investigate the impact of the increasing capacity of wind power fed into the Danish power grid.

scholarly journals Fault Diagnosis Strategy for Wind Turbine Generator Based on the Gaussian Process Metamodel

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Dongmei Zhang ◽  
Jun Yuan ◽  
Jiang Zhu ◽  
Qingchang Ji ◽  
Xintong Zhang ◽  
...  
Keyword(s):  
Gaussian Process ◽  
Wind Turbine ◽  
Industrial Development ◽  
Wind Farm ◽  
Wind Farms ◽  
Maintenance Cost ◽  
Key Factors ◽  
Turbine Generator ◽  
System Availability ◽  
Wind Turbine Generator

To facilitate continuous development of the wind power industry, maintaining technological innovation and reducing cost per kilowatt hour of the electricity generated by the wind turbine generator system (WTGS) are effective measures to facilitate the industrial development. Therefore, the improvement of the system availability for wind farms becomes an important issue which can significantly reduce the operational cost. To improve the system availability, it is necessary to diagnose the system fault for the wind turbine generator so as to find the key factors that influence the system performance and further reduce the maintenance cost. In this paper, a wind farm with 200 MW installed capacity in eastern coastal plain in China is chosen as the research object. A prediction model of wind farm’s faults is constructed based on the Gaussian process metamodel. By comparing with actual observation results, the constructed model is proved able to predict failure events of the wind turbine generator accurately. The developed model is further used to analyze the key factors that influence the system failure. These are conducive to increase the running and maintenance efficiency in wind farms, shorten downtime caused by failure, and increase earnings of wind farms.

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