Wind energy assessment considering a truncated distribution of probabilistic turbulence power spectral parameters

Yun Liu, Hao Wang, Zidong Xu and Jianxiao Mao

Renewable Energy, 2024, vol. 223, issue C

Abstract: Accurate probabilistic wind spectra are beneficial to reproducing or predicting wind speeds, then assessing wind energy. The non-truncated distribution is widely-used for fitting spectral parameters. However, it is not consistent with the bounded measured parameters. Therefore, the truncated distribution, firstly, is proposed in modelling three spectral parameters in the Ma'anshan Yangtze River (MYR) Bridge. The distribution parameters conditional to wind velocities are determined through estimated extreme values under a given recurrence period, which is derived from the established joint distribution of extreme spectral parameter and wind velocities. The fitness of the truncated distribution on measured values shows better performance than the non-truncated distribution. The dimension-reduction (DR) expression of stochastic wind fields is represented by considering probability-truncated wind spectra. The simulation of stochastic wind fields at the MYR Bridge is realized based on the proposed DR scheme. The comparisons of wind velocities and wind power densities are implemented between truncated and non-truncated distributions. Results shows the feasibility of the proposed method to exhibit probability of local wind fields. Meanwhile, wind speeds and wind power densities are more significant in the truncated distribution.

Keywords: Wind energy; Wind speed; Non-deterministic wind spectra; Truncated-probability distribution; Extreme value distribution; Dimension-reduction representation (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:223:y:2024:i:c:s0960148124000107

DOI: 10.1016/j.renene.2024.119945

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