One of the main renewable sources of energy is wind speed. In this study trends in wind speed series of Iran analyzed using four different versions of the Mann-Kendall method: i) Conventional Mann-Kendall method (MK1); ii) Mann-Kendall method following removing the effect of significant lag-1 auto-correlation (MK2); iii) Mann-Kendall method after the removing the effect of all significant auto-correlation coefficients (MK3); and iv) Mann-Kendall method with considering the Hurst coefficient (MK4). However, Interpretation of results accomplished according the MK4. Data used here were wind speed records in 10 m height and the period of study is1966-2005. For this purpose, 22 synoptic weather stations were selected from different points of Iran. Non-parametric Thiel –Sen’s Approach (TSA) was used for estimation of slopes of wind speed trend lines. Results showed that application of MK4 instead of MK1 reduced the value of Z statistics for almost all cases. In annual time scale, twelve out of the 22 stations showed significant negative and positive trends using MK1. This is reduced to five using MK4. Similarly, in monthly time scale, 129 out of 264 cases showed significant negative and positive trends using MK1. This is reduced to 82 using MK4. Result showed that although a combination of positive and negative trends observed in both monthly and annual time scales, however, the number of negative trends were more than that of the positive trends. In the annual time scale, the steepest negative trend line slope was -0.038 ms⁻¹year⁻¹ belonged to Shiraz station, and the steepest positive trend line slope was 0.074 ms⁻¹year⁻¹ belonged to Zabol station. In monthly time scale, the steepest negative trend line slope was -1.7 ms⁻¹ per four decades observed at Ghazvin (July), Fassa (November), and Kerman (April). In contrast, the steepest positive trend line slope was +3.6 ms⁻¹ per four decades observed at Zabol (July). Results showed that the median of the trend line slopes for all months (except February and November) was negative. It can be concluded that negative trends more pronounced than the positive trends for wind speed series of Iran.