RESEARCH ON DATA PROCESSING METHODS FOR "WIND SPEED-POWER" IN WIND TURBINE SCADA SYSTEMS

Liu Yuan; Li Zhonghu; Wang Jinming; Yang Liqing; Zhang Xinyu

doi:10.19912/j.0254-0096.tynxb.2024-0383

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Acta Energiae Solaris Sinica ›› 2025, Vol. 46 ›› Issue (7) : 353-360. DOI: 10.19912/j.0254-0096.tynxb.2024-0383

Special Topics of Academic Papers at the 62th Annual Meeting of the China Association for Science and Technology

RESEARCH ON DATA PROCESSING METHODS FOR "WIND SPEED-POWER" IN WIND TURBINE SCADA SYSTEMS

Liu Yuan¹, Li Zhonghu¹, Wang Jinming¹, Yang Liqing¹, Zhang Xinyu²

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Abstract

In the SCADA system data of wind turbines, if the density of noise data is too high, it may mistakenly clean the rated power data during the preprocessing process. To address this issue, the DBSCAN clustering algorithm can be used to remove noise data points near the rated power data, ensuring that only normal rated power data is retained. Then, on the wind speed-power curve, identify the boundary between the rated power data and other data, and temporarily store the upper part. For the lower part, apply a combination of Chauvenet's criterion and Box-Cox transformation to handle it. Finally, merge the two parts of the data. This approach can effectively reduce the problem of mistakenly cleaning rated power data due to high noise data density during the preprocessing of wind turbine SCADA data.

Key words

wind turbines / SCADA systems / data processling / rated power data / DBSCAN clustering algorithm / Chauvenet criterion

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Liu Yuan, Li Zhonghu, Wang Jinming, Yang Liqing, Zhang Xinyu. RESEARCH ON DATA PROCESSING METHODS FOR "WIND SPEED-POWER" IN WIND TURBINE SCADA SYSTEMS[J]. Acta Energiae Solaris Sinica. 2025, 46(7): 353-360 https://doi.org/10.19912/j.0254-0096.tynxb.2024-0383

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