2026-05-28 沖縄科学技術大学院大学（OIST）
© David Iliff via Wikimedia Commons (CC-BY-SA)
＜関連情報＞
- https://www.oist.jp/ja/news-center/news/2026/5/28/risk-renewable-power-fluctuations-made-predictable
- https://journals.aps.org/prxenergy/abstract/10.1103/vms3-ng8z
風力発電相関の集団的かつ非線形な構造 Collective and Nonlinear Structure of Wind-Power Correlations
Samy E. Lakhal1,*, J.E. Sardonia2, and M.M. Bandi
PRX Energy Published 28 May, 2026
DOI: https://doi.org/10.1103/vms3-ng8z
Abstract
We describe the correlation structure of wind-power fluctuations in a farm of 80 turbines, sampled over 5 years. We report the presence of universal, collective, and nonlinear correlations, responsible for the excess persistency and intermittency of farm-aggregated power output. A first cross-correlation analysis of turbine production reveals a dynamical scaling transition (à la Family-Vicszek) from local decoherence to large-scale turbulence-driven scaling, and responsible for the geographical smoothing effect, previously reported beyond farm scale [M. M. Bandi, Spectrum of wind-power fluctuations, Phys. Rev. Lett. 118, 028301 (2017)]. A second bivariate analysis shows the long-range correlation of non-Gaussian features, responsible for their amplification in total farm output. These findings provide important insights into wind energy, the variability of which directly results from atmospheric turbulent forcing. By characterizing the multivariate and intermittent structure of fluctuations, our results advance the current understanding of wind-power variability and provide valuable priors for grid management and storage optimization, thereby supporting improved integration of wind energy into modern power systems.
