Research on Anomaly Detection of Wind Farm SCADA Wind Speed Data

Wu Wen, Yubao Liu (), Rongfu Sun and Yuewei Liu
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Wu Wen: School of Computer Science, Chengdu University of Information Technology, Chengdu 610225, China
Yubao Liu: Precision Regional Earth Modeling and Information Center, Nanjing University of Information Science and Technology, Nanjing 210044, China
Rongfu Sun: Electric Power Dispatch Center, Jibei Electric Power Company, Beijing 100083, China
Yuewei Liu: Research Applications Laboratory of National Center for Atmospheric Research, Boulder, CO 80305, USA

Energies, 2022, vol. 15, issue 16, 1-18

Abstract: Supervisory control and data acquisition (SCADA) systems are critical for wind power grid integration and wind farm operation and maintenance. However, wind turbines are affected by regulation, severe weather factors, and mechanical failures, resulting in abnormal SCADA data that seriously affect the usage of SCADA systems. Thus, strict and effective data quality control of the SCADA data are crucial. The traditional anomaly detection methods based on either “power curve” or statistical evaluation cannot comprehensively detect abnormal data. In this study, a multi-approach based abnormal data detection method for SCADA wind speed data quality control is developed. It is mainly composed of the EEMD (Ensemble Empirical Mode Decomposition)-BiLSTM network model, wind speed correlation between adjacent wind turbines, and the deviation detection model based on dynamic power curve fitting. The proposed abnormal data detection method is tested on SCADA data from a real wind farm, and statistical analysis of the results verifies that this method can effectively detect abnormal SCADA wind data. The proposed method can be readily applied for real-time operation to support an effective use of SCADA data for wind turbine control and wind power prediction.

Keywords: SCADA data anomaly detection; EEMD-BiLSTM; correlation detection; dynamic power curve detection (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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