Determination of extreme wind values using the Gumbel distribution

Abstract

An investigation of what types of extreme wind values are the most suitable for the Gumbel distribution was conducted on Jeju Island, South Korea. Three measurements and reference sites that have different topographical conditions were selected to clarify the influence of the topographical conditions on extreme wind values. Because long-term wind data are required to estimate extreme wind speeds with a higher degree of confidence, the MCP (Measure-Correlate-Predict) technique was applied to generate ten-year wind data from one-year measurements. Extreme wind values were sampled from the ten-year wind data based on periodic maximum wind speeds and the wind speeds above a threshold, which were divided into three types each. The six types of extremes were examined to determine which type was more suitable for the Gumbel distribution under the assumption that the Gringorten formula is the best plotting position method for the Gumbel distribution. In addition, we predicted the appropriate wind turbine class for the measurement sites in compliance with IEC international standards. As a result, daily maximum wind speeds were the best extreme wind values for the Gumbel distribution in the six types irrespective of the topographical conditions. The site that has a higher average wind speed was estimated to have a higher extreme wind speed, indicating that a higher wind turbine class was needed at the site.