Reliability assessment of the wind power density using uncertainty analysis

Abstract Evaluation of the wind energy potential in different climates includes high level of uncertainties. To address the uncertainties, this study performs reliability analysis by defining a limit state function for the wind power density (WPD) to determine failure or success of the system in the probabilistic framework. The probability distributions of the variables including wind speed and air density simulated by the Weather Research and Forecasting (WRF) model with 2 km resolution are used in the limit state function to form a nondeterministic model in southwest of Iran. Given significant correlation between air density and wind speed in most of the pixels, Nataf transformation is applied to produce uncorrelated variables. Results show the probability of each success in which the WPD exceeds the average value in the region. The greater probability of the success in the pixels can specify promising locations where stronger wind speed occurs. Reliability analysis shows that, on average, probability of having WPD larger than average value is about 0.6 and 0.7 in southwest and offshore areas of selected domains, respectively. This reliability framework can be used to build a decision model for wind energy assessment, which is robust to different climate conditions.