Wind droughts, or prolonged periods of low wind speeds, pose challenges for electricity systems largely reliant on wind generation. Using weather reanalysis data, we analyzed the global distribution of and trends in wind droughts using an energy deficit metric that integrates the depth and duration of wind droughts. We identified regions with high power densities, low seasonal variability, and limited weather fluctuations that favor wind power generation, such as the American Midwest, Australia, the Sahara, Argentina, Central Asia, and Southern Africa. Northwestern Europe has high power densities but experiences more frequent and prolonged wind droughts due to higher weather variability. We found little evidence for strong trends in wind droughts over recent decades in most places. Rather, the most severe wind droughts in many places occurred before wind power substantially penetrated power systems, which suggests that historical weather data can be useful in designing reliable wind-reliant electricity systems.

When wind turbines are arranged in clusters, their performance is mutually affected, and their energy generation is reduced relative to what it would be if they were widely separated. Land-area power densities of small wind farms can exceed 10 W/m², and wakes are several rotor diameters in length. In contrast, large-scale wind farms have an upper-limit power density in the order of 1 W/m² and wakes that can extend several tens of kilometers. Here, we address two important questions: 1) How large can a wind farm be before its generation reaches energy replenishment limits and 2) How far apart must large wind farms be spaced to avoid inter–wind-farm interference? We characterize controls on these spatial and temporal scales by running a set of idealized atmospheric simulations using the Weather and Research Forecasting model. Power generation and wind speed within and over the wind farm show that a timescale inversely proportional to the Coriolis parameter governs such transition, and the corresponding length scale is obtained by multiplying the timescale by the geostrophic wind speed. A geostrophic wind of 8 m/s and a Coriolis parameter of 1.05 × 10⁻⁴ rad/s (latitude of ∼46°) would give a transitional scale of about 30 km. Wind farms smaller than this result in greater power densities and shorter wakes. Larger wind farms result instead in power densities that asymptotically reach their minimum and wakes that reach their maximum extent. Significance Wind comprised 6.1% of worldwide electricity generation in 2020. If this share is to substantially grow to decarbonize electricity systems, the size of future wind farms may extend far beyond that of current installations. The spatial scale of a wind farm affects both its mean generation per unit of land and the extension of wake shadowing on neighboring plants. As spatial scales increase, mean generation decreases and wake extension increases. Here, we characterize spatial constraints in the large-scale expansion of wind power plants to address the following: 1) How large a wind farm can be before its generation reaches energy replenishment limits, and 2) How far apart large wind farms must be spaced to avoid inter–wind-farm interference.