Presentations

Abstract

Wind developers today rely almost exclusively on measured and modelled historical weather data at site to predict future energy yield. This approach becomes problematic in the face of a changing climate, as there is no guarantee that future wind resource patterns and met-ocean conditions will mimic historical conditions. Despite this, there is currently no standard methodology for incorporating climate projections into energy yield assessments. This study offers a proposed framework for addressing this gap. Using the sixth Coupled Model Intercomparison Project (CMIP6) ensemble of climate models, we analyze four Shared Socioeconomic Pathway (SSP) scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5) to explore a range of possible futures. The selection of models used have been preconfigured for a consistent spatial and temporal resolution by ClimateScale. Statistical multivariate downscaling and bias-correction is applied to refine the global climate projections to localized wind and met-ocean conditions relevant to individual offshore wind farms. The performance of each corrected climate model is evaluated against historical observations – comprised of site measurements and long-term reanalysis data – on the basis of distribution similarity, interannual variability, seasonality, and rolling 20-year anomalies. We demonstrate a method for processing specific climate variables of interest and generating projections, with uncertainty ranges, for a selection of key outputs, such as annual energy production. The methodology was developed and tested on Ørsted’s entire operational offshore portfolio, spanning Northern Europe, the U.S. East Coast, and Taiwan, revealing projected differences across regions and scenarios. By offering a structured approach to assessing the impact of climate change on energy yield assessments, this study provides a foundation for developers to better understand and plan for an uncertain future.