Advanced Discretisation and Visualisation Methods for Performance Profiling of Wind Turbines

Michiel Dhont, Elena Tsiporkova and Veselka Boeva
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Michiel Dhont: EluciDATA Lab of Sirris, Bd A. Reyerslaan 80, 1030 Brussels, Belgium
Elena Tsiporkova: EluciDATA Lab of Sirris, Bd A. Reyerslaan 80, 1030 Brussels, Belgium
Veselka Boeva: Blekinge Institute of Technology, Blekinge Tekniska Högskola, 371 79 Karlskrona, Sweden

Energies, 2021, vol. 14, issue 19, 1-30

Abstract: Wind turbines are typically organised as a fleet in a wind park, subject to similar, but varying, environmental conditions. This makes it possible to assess and benchmark a turbine’s output performance by comparing it to the other assets in the fleet. However, such a comparison cannot be performed straightforwardly on time series production data since the performance of a wind turbine is affected by a diverse set of factors (e.g., weather conditions). All these factors also produce a continuous stream of data, which, if discretised in an appropriate fashion, might allow us to uncover relevant insights into the turbine’s operations and behaviour. In this paper, we exploit the outcome of two inherently different discretisation approaches by statistical and visual analytics. As the first discretisation method, a complex layered integration approach is used. The DNA-like outcome allows us to apply advanced visual analytics, facilitating insightful operating mode monitoring. The second discretisation approach is applying a novel circular binning approach, capitalising on the circular nature of the angular variables. The resulting bins are then used to construct circular power maps and extract prototypical profiles via non-negative matrix factorisation, enabling us to detect anomalies and perform production forecasts.

Keywords: wind turbine; operating mode labelling; multi-source data; performance monitoring; non-negative matrix factorisation; circular binning (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: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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