A comparative analysis on the variability of temperature thresholds through time for wind turbine generators using normal behaviour modelling

Turnbull, Alan and Carroll, James and McDonald, Alasdair (2022) A comparative analysis on the variability of temperature thresholds through time for wind turbine generators using normal behaviour modelling. Energies, 15 (14). 5298. ISSN 1996-1073 (https://doi.org/10.3390/en15145298)

[thumbnail of Turnbull-etal-Energies-2022-A-comparative-analysis-on-the-variability-of-temperature-thresholds-through-time]
Preview
 Text. Filename: Turnbull_etal_Energies_2022_A_comparative_analysis_on_the_variability_of_temperature_thresholds_through_time.pdf
Final Published Version
License: Creative Commons Attribution 4.0 logo
Download (3MB)| Preview

Abstract

Data-driven normal behaviour models have gained traction over the last few years as a convenient way of modelling turbine operational health to detect anomalies. By leveraging high-dimensional operational relationships, temperature thresholds can be automatically calculated based on each individual turbine unique operating envelope, in theory minimising false alarms and providing more reliable diagnostics. The aim of this work is to provide further insight into practical uses and limitations of implementing normal behaviour temperature models in practice, to inform practitioners, as well as assist in improving wind turbine generator fault detection systems. Results suggest that, on average, as little as two months of data are adequate to produce stable temperature alarm thresholds, with the worst case example requiring approximately 200–290 days of data depending on the component and desired convergence criteria.

ORCID iDs

Turnbull, Alan, Carroll, James ORCID logoORCID: https://orcid.org/0000-0002-1510-1416 and McDonald, Alasdair;
CORE (COnnecting REpositories)