Picture map of Europe with pins indicating European capital cities

Open Access research with a European policy impact...

The Strathprints institutional repository is a digital archive of University of Strathclyde's Open Access research outputs. Strathprints provides access to thousands of Open Access research papers by Strathclyde researchers, including by researchers from the European Policies Research Centre (EPRC).

EPRC is a leading institute in Europe for comparative research on public policy, with a particular focus on regional development policies. Spanning 30 European countries, EPRC research programmes have a strong emphasis on applied research and knowledge exchange, including the provision of policy advice to EU institutions and national and sub-national government authorities throughout Europe.

Explore research outputs by the European Policies Research Centre...

Wind turbine condition assessment through power curve copula modeling

Gill, Simon and Stephen, Bruce and Galloway, Stuart (2012) Wind turbine condition assessment through power curve copula modeling. IEEE Transactions on Sustainable Energy, 3 (1). pp. 94-101. ISSN 1949-3029

[img]
Preview
Text (Gill-etal-TSE2012-wind-turbine-condition-assessment-through-power-curve-copula-modeling)
Gill_etal_TSE2012_wind_turbine_condition_assessment_through_power_curve_copula_modeling.pdf - Accepted Author Manuscript

Download (1MB) | Preview

Abstract

Power curves constructed from wind speed and active power output measurements provide an established method of analyzing wind turbine performance. In this paper it is proposed that operational data from wind turbines are used to estimate bivariate probability distribution functions representing the power curve of existing turbines so that deviations from expected behavior can be detected. Owing to the complex form of dependency between active power and wind speed, which no classical parameterized distribution can approximate, the application of empirical copulas is proposed; the statistical theory of copulas allows the distribution form of marginal distributions of wind speed and power to be expressed separately from information about the dependency between them. Copula analysis is discussed in terms of its likely usefulness in wind turbine condition monitoring, particularly in early recognition of incipient faults such as blade degradation, yaw and pitch errors.