Wind turbine performance assessment & power curve outlier rejection using copula modelling
Zorzi, Giorgio and Stephen, Bruce and McMillan, David (2018) Wind turbine performance assessment & power curve outlier rejection using copula modelling. In: 2018 Global Offshore Wind, 2018-06-19 - 2018-06-20, Manchester Central.
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Abstract
The conventional means of assessing performance of a wind turbine is through consideration of its power curve. However, this representation fails to capture plausibility of measurement and cannot provide anomaly detection capabilities, which may assist in the detection of plant degradation. Although the probabilistic form of the power curve is complex, Copula models are presented here as a means of expressing the operational power curve as a joint distribution of wind speed and power output. This probabilistic model is demonstrated as an efficient way to remove outliers from operational SCADA data, simplifying and accelerating the process of identifying plant maloperation.
ORCID iDs
Zorzi, Giorgio, Stephen, Bruce ORCID: https://orcid.org/0000-0001-7502-8129 and McMillan, David ORCID: https://orcid.org/0000-0003-3030-4702;-
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Item type: Conference or Workshop Item(Poster) ID code: 67832 Dates: DateEvent19 June 2018Published2018SubmittedSubjects: Technology > Electrical engineering. Electronics Nuclear engineering Department: Faculty of Engineering > Electronic and Electrical Engineering
Strategic Research Themes > EnergyDepositing user: Pure Administrator Date deposited: 14 May 2019 14:00 Last modified: 09 Oct 2024 00:45 URI: https://strathprints.strath.ac.uk/id/eprint/67832