A wavelet transform based stationary transformation method for estimating the extreme value of the non-stationary wind speeds

The rational estimation of extreme wind speeds is crucial. As reported, in the Chinese area, the measured wind speed variation from different meteorological observatories shows a general non-stationary trend in the past 40 years due to urbanization factors or temperature variation. Thus, the non-stationary extreme value analysis (TNGEV) of the measured wind speed is required. However, TNGEV is relatively complicated. Under such a background, in this paper, a novel simplified wavelet transform-based stationary transformation method (PNGEV) is proposed for the extreme value analysis of the non-stationary wind speeds. This paper firstly derives the proposed time-varying extreme value distribution parameter form, combining the wavelet transform and moving average. Secondly, a case study is provided to illustrate and verify this proposed method (PNGEV), using the 40-year daily maximum wind speeds recorded from 1981 to 2020 in Baoshan District Shanghai, China. The effectiveness of the proposed method (PNGEV) is verified by comparing it with TNGEV in the return period and the risk of failure. By comparison, it can be figured out that the proposed PNGEV is practicable and outperforms TNGEV in the stability of the return period calculation, as well as the time-varying extreme value distribution establishment.