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Journal of North China Electric Power University(Natural Science Edition). Core
(Accepted Version) Online First Publishing Date: 2023-08-29 15:58:28

Anomaly Warning of Wind Turbine Based on LOF-DBSCAN and Optuna Optimized XGBoostChinese Full TextEnglish Full Text (MT)

Ma Liangyu;Duan Xiaochong;Hu Jingchen;Huang Rihao;

Abstract: Aiming at the problem of frequent failure of wind turbines due to long-term exposure to harsh environments， a data cleaning method combining local outlier factor （LOF） with density-based spatial clustering algorithm （DBSCAN）， and an anomaly warning method based on optimized extreme gradient boosting （XGBoost） algorithm are proposed. Firstly， the LOF algorithm and DBSCAN algorithm are used jointly to preprocess the abnormal operating data in the supervisory control and data acquisition （SCADA） sy... More
Keywords：

Wind turbines; LOF; DBSACN; Optuna; XGBoost; Anomaly warning;

  • Series：

    (C) Architecture/ Energy/ Traffic/ Electromechanics, etc

  • Subject：

    Electric Power Industry

  • Classification Code：

    TM315

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