Failure Analysis of Wind Turbines by Probability Density Evolution Method

The aim of this study is to present an efficient and accurate method for estimation of the failure probability of wind turbine structures which work under turbulent wind load. The classical method for this is to fit one of the extreme value probability distribution functions to the extracted maxima of the response of wind turbine. However this approach may contain high amount of uncertainty due to the arbitrariness of the data and the distributions chosen. Therefore less uncertain methods are meaningful in this direction. The most natural approach in this respect is Monte Carlo (MC) simulation. This is not practical due to its excessive computational load. This problem can alternatively be tackled if the evolution of the probability density function (PDF) of the response process can be realized. The evolutionary PDF can then be integrated on the boundaries of the
problem. For this reason we propose to use the Probability Density Evolution Method (PDEM). PDEM can alternatively be used to obtain the distribution of the extreme values of the response process by simulation. This approach requires less computational effort than integrating the evolution of the PDF; but may be less accurate. In this paper we present the results of failure probability
estimation using PDEM. The results will then be compared to extrapolated values obtained from extreme value distribution fits to the sample response values. The results approve the feasibility of this approach for reliability analysis of wind turbines however they convey the potential for improving accuracy of the method in low probability areas