A Review of Approaches for the Detection and Treatment of Outliers in Processing Wind Turbine and Wind Farm Measurements

Mingzhe Zou and Sasa Z. Djokic
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Mingzhe Zou: School of Engineering, the University of Edinburgh, Edinburgh EH9 3DW, UK
Sasa Z. Djokic: School of Engineering, the University of Edinburgh, Edinburgh EH9 3DW, UK

Energies, 2020, vol. 13, issue 16, 1-30

Abstract: Due to the significant increase of the number of wind-based electricity generation systems, it is important to have accurate information on their operational characteristics, which are typically obtained by processing large amounts of measurements from the individual wind turbines (WTs) and from the whole wind farms (WFs). For further processing of these measurements, it is important to identify and remove bad quality or abnormal data, as otherwise obtained WT and WF models may be biased, or even inaccurate. There are wide ranges of both causes and manifestations of these bad/abnormal data, which are often denoted with the common general term “outlier”. This paper reviews approaches for the detection and treatment of outliers in processing WT and WF measurements, starting from the discussion of the commonly measured parameters, variables and resolutions, as well as the corresponding requirements and recommendations in related standards. Afterwards, characteristics and causes of outliers reported in existing literature are discussed and illustrated, as well as the requirements for the data rejection in related standard. Next, outlier identification methods are reviewed, followed by a review of approaches for testing the success of outlier removal procedures, with a discussion of their potential negative effects and impact on the WT and WF models. Finally, the paper indicates some issues and concerns that could be of interests for the further research on the detection and treatment of outliers in processing WT and WF measurements.

Keywords: measurement data; outlier; wind turbine; wind farm (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: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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