The spatial organization of wind turbine wakes

Abstract

Wind turbine wakes play a central role in determining wind farm performance, yet their spatial organization remains only partially understood. Here, we apply a spatially localized multifractal analysis to quantify the strength of dependencies (local roughness) and extreme velocity fluctuations (local intermittency) in turbine wakes, and relate these properties to established metrics in wind energy research. Using two-dimensional nacelle-mounted LiDAR plan-position-indicator scans, we extract scale-invariant features that enable systematic comparisons across the wake without requiring time-resolved data. Designed to robustly handle irregular sampling, our analysis yields four main findings: i.) Four distinct wake zones are identified, each exhibiting unique patterns of roughness and intermittency. ii.) Coherent, strongly correlated patches emerge 2 to 5 rotor diameters D downstream, with intermittency strengthening periodically at multiple D positions and along the wake-free-flow interface. iii.) The classical "intermittency ring" is consequently redefined as a set of localized "intermittency bubbles", iv.) which interact dynamically with the ambient atmosphere through an inverse energy cascade, transferring energy from small to large scales. These findings, supported by concurrent cup anemometer observations under free-inflow conditions, demonstrate that local multifractal analysis provides a robust and cost-effective diagnostic framework for wake characterization and wake-model validation, with direct relevance for wind-farm design and control.