A copula post-processing method for wind power projections under climate change

Abstract

Wind energy plays a pivotal role in the ongoing effort to reduce carbon emissions in the energy sector. With the increasing evidence of climate change, there is a growing concern regarding the planning and operation of wind energy resources. Accurate forecasts are essential to understand the frequency distribution of wind speed data in a given area and, consequently, to estimate energy production. This paper aims to analyze the wind resources under climate change, assess their potential, and create zoning maps for wind energy production in the island of Ireland. For this objective, wind speed data from 31 general circulation models (GCMs) and two climate change scenarios were utilized for both hindcast and forecast periods in 1981–2010 and 2021–2050, respectively. The GCM outputs were first bias-corrected and then post-processed using various (non–)parametric statistical distributions and 3 Copula families. The results indicate an expected decrease in the average wind speed in the region up to ∼ 21 % by 2050, contingent on the climate scenarios under consideration and the target point. Ultimately, this study concludes by presenting wind power density maps specifically to the study region, offering valuable insights for sustainable energy planning.