Estimation of spatial, temporal and sectoral turbulence intensity and the power-law exponent influence on the wind energy: A case study

Wind speed (WS), turbulence intensity (TI) and power-law exponent (PLE) are three of the most important parameters influencing wind potential and the design of wind turbine structures. The effect of these parameters varies depending on the season, period of day, and direction of the wind. They can significantly impact electricity generation and cause faults in wind turbine components due to changes in WS and atmospheric instability. In this study, a multi-dimensional classification approach is implemented to analyze meteorological data according to season, diurnal variation, and wind direction (WD). The TI and PLE were determined using data collected over four years (2017–2020) from two locations in Nouakchott, Mauritania. The results showed that the dry season had the highest mean WS and power density (PD), as well as the highest PLE, and the lowest TI. However, the rainy season was characterized by the lowest mean WS, PD, and PLE. On the other hand, the TI was the highest. Different periods of the daytime and nighttime, as well as different sectors, were considered. According to the TI and PLE distribution results, the atmosphere was nearly stable, stable, and strongly stable for more than 70% of the time at a height of 90 m at both sites. Furthermore, the actual TI was compared with that defined by the Normal Turbulence Model (NTM) in the International Electrotechnical Commission (IEC) standard. The results show that the NTM overestimates the actual TI at different heights in the two locations. The site-specific empirical findings from this study provide a valuable benchmark for operating and managing wind turbines, as well as providing crucial baseline information for understanding the performance of wind systems and their implications throughout the turbines’ lifespans in coastal desert environments.