Use of Birnbaum-Saunders distribution for estimating wind speed and wind power probability distributions: A review

A knowledge of wind speed and wind power probability distributions is important for several reasons such as assessing wind resources, planning wind farms and minimizing the uncertainties for wind power development. In this study, application of the two parameter Birnbaum-Saunders (BS) distribution is introduced and reviewed for characterizing the wind speed and wind power density distributions. For this work, a long-term time series of measured wind speed data for ten stations distributed in the Ontario province of Canada has been utilized for a case study. The suitability of the BS distribution was evaluated against nine earlier used one-component distributions. The results showed that BS distribution performed very favorably at all selected stations. It outperformed the other distributions at six stations while in the remaining four stations ranked either third or fourth. It was also found that, although the Weibull distribution was the second best function to estimate the wind power density distribution, it was not able to give adequate description of the frequency of wind speed data at all sites. In summary, the study results demonstrated the generalization capability, precision, and effectiveness of the BS distribution for characterizing wind speed and wind power distribution. (C) 2017 Elsevier Ltd. All rights reserved.