2025/03/21 by Ruben Borgers, Joaquim G. Pinto, Nicole Van Lipzig · 1 voice
Engineering · Environmental Science · #Energy Load and Power Forecasting #Climate variability and models
paper · pdf · doi:10.1175/jamc-d-24-0116.1
openalex publication_date 2025/03/21 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/31
Abstract The increasing importance of wind energy in the electricity mix underscores the need for accurate estimation of wind energy production in the coming decades. Here, we present a new statistical–dynamical downscaling approach to quantify the energy production of wind farms in an ensemble of future climate projections. This approach relies on two reanalysis-driven regional climate model simulations, one of which includes a wind farm parameterization to account for wind farm–atmosphere interactions and wake losses. We then apply this method to a projected, 92-GW offshore wind farm distribution in the North Sea and compare the energy production between the wind climate of 1985–2014 and 38 projections for the wind climate of 2025–54. The ensemble mean difference in 30-yr energy production is −5% for JJA, −2.5% for SON, and near zero for DJF and MAM. However, these 30-yr differences have a large ensemble spread, with an interquartile range (IQR) of around 8% and a range of around 15%. Furthermore, the ensemble probability distribution of decadal energy production is different compared to the reference period. For winter, 16% of future decades fall below the 5th percentile (P5) of the historical period and 12% of future decades exceed the 95th percentile (P95). Finally, we demonstrate the importance of considering the secondary effect by which wind climate changes increase or reduce wake losses, as long-term changes can differ strongly when these effects are not included. The potential changes in energy production discussed here should be considered alongside other effects, such as near-future increases in interfarm wake losses and technological advancements to optimally constrain the uncertainty in near-future wind energy production. Significance Statement Wind energy is playing an increasingly significant role in the electricity mix, making it essential to quantify the uncertainty in near-future wind energy production for developing secure energy infrastructure. In this context, we introduce a novel approach that combines future climate projections with high-resolution regional climate model simulations to quantify the uncertainty in future energy production in a cost-effective way. Improving upon existing methods, this approach also considers the two-way interactions between wind farm clusters and the atmosphere.