Determining the ideal length of wind speed series for wind speed distribution and resource assessment

Abstract. Accurate wind resource assessment depends on wind speed data that capture local wind conditions, crucial for energy estimates and site selection. The International Electrotechnical Commission (IEC) recommends at least one year of data collection, yet this duration may not fully account for interannual variability. While studies often maximize data length, guidance on the minimum duration required for reliable wind speed and power estimates remains limited. To address this gap, we propose a method to quantify the errors introduced by using wind speed series of different lengths for wind speed distributions fitting, relative to long-term data. This allows us to determine the minimum number of hourly observations needed to for a given accuracy level. We apply our method to in-situ weather station observations and ERA5 reanalysis data at 10-meter and 100-meter heights. Our results show that key parameters, including mean, standard deviation, and Weibull parameters, stabilize with relatively short records (~1 month of hourly data), whereas skewness requires at least 1.6 years, and kurtosis requires 88.6 years to stabilize. ERA5 data stabilize with fewer observations but differ from in-situ measurements, requiring careful use. Moreover, combining available hourly data for distribution fitting produces parameters comparable to those obtained when controlling for diurnal and seasonal effects, suggesting discontinuous data can be viable under certain conditions. These findings offer a practical framework for optimizing data collection in wind resource assessments, balancing accuracy and cost-effectiveness.