In this paper we use risk management techniques to evaluate the effects of some risk factors that affect the energy production of a wind farm. We focus our attention on three major risks: wind speed variability, wind turbine failures and correlations between produced energy. As a first contribution, we show that the Weibull distribution, commonly used to fit recorded wind speed data, underestimates rare events. Therefore, in order to achieve a better estimation of the tail of the wind speed distribution, we advance a Generalized Pareto distribution. We considered one aspect of the wind turbines reliability by modeling their failure events as a compound Poisson process. Finally, the use of Copula enables us to consider the correlation between wind turbines that compose the wind farm. Once this procedure is set up, we show a sensitivity analysis and we also compare the results from the proposed procedure with a simplistic energy prediction using the Weibull distribution.
|Titolo:||Wind speed prediction for wind farm applications by Extreme Value Theory and Copulas|
|Data di pubblicazione:||2015|
|Tipologia:||1.1 Articolo in rivista|