A theoretical limit for the energy extraction of offshore wind farms has been suggested by Simão Ferreira et al. (2026) based on a simple model of an infinite wind farm and an ad hoc method to correct the model for application to finite wind farms. In this work, we discuss a number of concerns and we conclude that the limit proposed in Simão Ferreira et al. (2026) is not a theoretical limit but rather a limit supported by the non-reproducible finite wind farm correction.

Floating wind turbines move with waves and wind, surging back and forth. Using wind tunnel experiments, we show that this motion can help the wake (the disturbed air trailing the turbine) recover faster, so downwind turbines receive more wind. This effect is strong when the turbine pulls hard on the wind, known as high thrust. We also discovered a new effect: recovery improves when the surging is just slightly slower than the blades' spin. This could make floating wind farms more efficient.

This study examines strategic deployment of distributed wind (DW) energy in high-energy-burden areas by evaluating spatial, technical, and economic factors. It highlights locations where installing DW turbines could potentially help to alleviate energy hardship. The findings offer insights for decision-makers and developers to optimize DW deployment and potentially contribute to economic relief.

Rain erosion of wind turbine blades degrades power production and causes high repair costs. During erosion the surface material disintegrates due to fatigue cracking. Experimental fracture mechanics are applied to quantify the properties governing fatigue cracking. This approach offers a paradigm shift to assessment of blade erosion and facilitates a systematic development of future protective materials needed to eliminate the costs and uncertainties related to blade erosion.

We researched how to improve wind speed estimates for wind resource assessments in the Andes mountains of Ecuador. Instead of relying only on near-ground data from a global reanalysis dataset, we tested wind speeds from higher levels in the atmosphere and combined them with masts measurements through a machine learning model. This strongly improved accuracy and reduced energy calculation errors, offering a more reliable and affordable way to obtain data for planning wind power in complex terrain.

Accurate fatigue damage estimation is central to deciding whether an ageing wind turbine can safely remain in service. The most reliable approach processes continuous high-frequency strain measurements, but the resulting data volumes and costs make it impractical across large fleets. Using 6 months of strain data from an onshore turbine, we show that strongly compressed stress representations recover almost all of the fatigue damage, enabling accurate, data-efficient monitoring at fleet scale.

Wind turbines age unevenly within a farm because of site conditions and the influence of surrounding turbines. We present an approach to set lower power under certain winds to reduce fatigue loads while keeping energy high. On a nine‑turbine example farm, this added 2 to 5 years of life with small energy losses of less than 1% and increased net present value. The method is scalable to any wind farm and delivers simple look-up tables for usage in operational planning and control.

Designing inter-array cable networks is a key challenge in wind farm development. This work proposes a methodology that combines graph-based routing with mixed-integer optimisation to determine cable routes and conductor sizes while accounting for spatial constraints and electrical limits. Two strategies are investigated: an integrated optimisation and a sequential approach. The method is tested on routes from existing offshore and onshore wind farms.

To plan a reliable United States power grid, engineers need continuous weather data. Because the previous standard record ended in 2013, we created a new, easy-to-use weather database by repackaging complex weather forecasting models onto the same historical grid. We compared our data against real-world observations nationwide, finding it is highly accurate. This provides a seamless, reliable new standard to help plan the future of our national energy system.