WIND TURBINE ANOMALY DETECTION BASED ON VARIATIONAL GRAPH AUTO-ENCODING OF SCADA PARAMETER COUPLING NETWORK

Liu Xiaofeng; Li Junfeng; Bo Lin

doi:10.19912/j.0254-0096.tynxb.2024-0138

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Acta Energiae Solaris Sinica ›› 2025, Vol. 46 ›› Issue (5) : 567-576. DOI: 10.19912/j.0254-0096.tynxb.2024-0138

WIND TURBINE ANOMALY DETECTION BASED ON VARIATIONAL GRAPH AUTO-ENCODING OF SCADA PARAMETER COUPLING NETWORK

Liu Xiaofeng, Li Junfeng, Bo Lin

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Abstract

By utilizing the numerical information of the wind turbine SCADA data monitoring parameters and their mutual coupling correlation, a wind turbine anomaly detection method based on variational graph auto-coding of multi-parameter coupling relationship is proposed. In this method, the adaptive symbolic transfer entropy of time series is used to construct a parameter coupling correlation network for SCADA data. A variational graph auto-encoding-recoding model is established to encode and reconstruct the parameter coupling correlation network. Combined with the coding reconstruction error of the SCADA parameter coupling correlation network, the health state assessment index of the wind turbine is constructed, and the support vector regression iterative updating method is applied to adaptively set the real-time health threshold of the wind turbine. The proposed method is verified using the SCADA monitoring data of wind turbines in two wind farms. The analysis results showed that this method can effectively extract the numerical information and the internal coupling correlation information from SCADA multivariable time series, which can effectively improve the accuracy of wind turbine anomaly detection and has good robustness to environmental interferences.

Key words

wind turbines / multiple parameters coupling / variational graph auto-encoding / health index construction / anomaly detection

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Liu Xiaofeng, Li Junfeng, Bo Lin. WIND TURBINE ANOMALY DETECTION BASED ON VARIATIONAL GRAPH AUTO-ENCODING OF SCADA PARAMETER COUPLING NETWORK[J]. Acta Energiae Solaris Sinica. 2025, 46(5): 567-576 https://doi.org/10.19912/j.0254-0096.tynxb.2024-0138

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