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 logoORCID: https://orcid.org/0000-0001-7502-8129 and McMillan, David ORCID logoORCID: https://orcid.org/0000-0003-3030-4702;
CORE (COnnecting REpositories)