A health condition assessment method of wind turbine generator system based on multiple turbines cooperation
Author(s) -
Hu Yaogang,
Shi Pingping,
Fang Chao,
Wang Yong,
Liu Chuanliang,
Ding Gang,
Sun Meng
Publication year - 2021
Publication title -
iet renewable power generation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.005
H-Index - 76
eISSN - 1752-1424
pISSN - 1752-1416
DOI - 10.1049/rpg2.12291
Subject(s) - wind power , turbine , generator (circuit theory) , marine engineering , doubly fed electric machine , steam turbine , induction generator , computer science , environmental science , control engineering , automotive engineering , engineering , aerospace engineering , electrical engineering , power (physics) , ac power , mechanical engineering , physics , quantum mechanics , voltage
To improve the reliability and optimize the maintenance strategy of a large‐scale wind farm, a health condition assessment method of wind turbine generator system (WTGS) based on multiple turbines cooperation is presented in this paper. First, a health condition assessment framework is established by analyzing the existing monitoring characteristics of SCADA system. Second, to quantify the health condition of a WTGS, the concept of synthetic degradation factor is introduced and calculated using variable weight of assessment indices. Third, in order to acquire the health level of a WTGS effectively, based on the idea of multiple turbines cooperation, the health condition assessment model is proposed by utilizing the moving average method and quantile algorithm. Finally, by using SCADA monitoring data of a wind farm with 33 × 1.5 MW WTGSs including temperature, pressure, vibration, and so on; the processes of condition assessment are performed, and the effectiveness is also compared to a traditional assessment method with the fixed threshold. The results show that the condition assessment that utilizes the proposed method can acquire the change of health conditions and has a better coherence with real health conditions.
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