An optimal control strategy for reactive power in wind farms consisting of VSCF DFIG wind turbine generator systems

2011 ◽  
Author(s):  
Jingmei Fang ◽  
Gengyin Li ◽  
Xuefeng Liang ◽  
Ming Zhou
Keyword(s):  
Optimal Control ◽  
Wind Turbine ◽  
Control Strategy ◽  
Reactive Power ◽  
Wind Farms ◽  
Optimal Control Strategy ◽  
Turbine Generator ◽  
Wind Turbine Generator

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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