title: A nonlinear dynamics approach for incorporating wind-speed patterns into wind-power project evaluation.
abstract: Wind-energy production may be expanded beyond regions with high-average wind speeds (such as the Midwest U.S.A.) to sites with lower-average speeds (such as the Southeast U.S.A.) by locating favorable regional matches between natural wind-speed and energy-demand patterns. A critical component of wind-power evaluation is to incorporate wind-speed dynamics reflecting documented diurnal and seasonal behavioral patterns. Conventional probabilistic approaches remove patterns from wind-speed data. These patterns must be restored synthetically before they can be matched with energy-demand patterns. How to accurately restore wind-speed patterns is a vexing problem spurring an expanding line of papers. We propose a paradigm shift in wind power evaluation that employs signal-detection and nonlinear-dynamics techniques to empirically diagnose whether synthetic pattern restoration can be avoided altogether. If the complex behavior of observed wind-speed records is due to nonlinear, low-dimensional, and deterministic system dynamics, then nonlinear dynamics techniques can reconstruct wind-speed dynamics from observed wind-speed data without recourse to conventional probabilistic approaches. In the first study of its kind, we test a nonlinear dynamics approach in an application to Sugarland Wind-the first utility-scale wind project proposed in Florida, USA. We find empirical evidence of a low-dimensional and nonlinear wind-speed attractor characterized by strong temporal patterns that match up well with regular daily and seasonal electricity demand patterns.
authors.affiliation: Agricultural and Biological Engineering Department, University of Florida, Gainesville, Florida, United States of America.
authors.forename: Ray
authors.initials: R
authors.lastname: Huffaker
authors.affiliation: Department of Agricultural Sciences, University of Bologna, Bologna, Italy.
authors.forename: Marco
authors.initials: M
authors.lastname: Bittelli
mesh_terms: D002940:Circadian Rhythm; D004736:Energy-Generating Resources; D017711:Nonlinear Dynamics; D012621:Seasons; D014919:Wind