Uncertainties in climate projections and the economics of wind farm portfolios

Abstract

The deployment of low carbon affordable energy generation technologies plays a crucial role to achieve the Paris Agreement long-term goal to reduce global greenhouse gas emissions to limit global temperature increase well below 2ºC above pre-industrial levels, and pursue efforts to limit it to 1.5º C above pre-industrial levels. In particular wind power installed capacity is projected to increase exponentially over the next few decades. Wind power generation is, however, weather-dependent. Therefore, understanding the variability of wind, how it might be affected by climate change, and how this affects the economics of wind projects seems vital as countries continue to invest in wind energy. At the global level, the last IPCC report (IPCC AR6 WGIII, 2022) states that the climate change impact on future wind resources will be limited. Regional studies, however, show that wind resources are projected to increase for instance over Northern Europe and decrease over Southern Europe. In North America, various studies have low agreement for the changes on future resources, in part because the inter-annual variability is larger than the projected changes due to climate change. For South America, some studies find increases in wind resources in windy areas. In general, the compounding of the anthropogenic climate change signal with high spatial and temporal wind variability can lead to large uncertainties in the projected impacts of climate change on wind resources, and as a result, on the economics of a project.  In this study we showcase a methodology to analyze the impact of climate change on the economic indicators of a portfolio of wind farm projects across Europe. Projections of changes in wind resources are obtained using an ensemble of Coupled Model Intercomparison Project 6 (CMIP6) global climate models statistically downscaled to correct biases and increase the spatial resolution. Uncertainties in climate projections are taken into account by considering an ensemble of climate models and different emissions scenarios as represented by the Shared Socioeconomic Pathways (SSPs) . A series of assumptions about the features of a representative wind farm and its key economic parameters (e.g. capital expenditures and operational costs) are made to compute two common economic indicators: the Internal Rate of Return (IRR) and the Levelized Cost of Energy (LCOE). By varying the production following the different climate scenarios, we analyze the impacts of climate change on the economics of the portfolios for different time horizons in the future. We find that the effect of changes of resource on IRR and LCOE depend on the region, emissions scenario and projection period. In the short term, changes are often masked by the internal variability of the resource on the site. We also discuss, from the point of view of our role as climate services provider for the wind industry, the limitations of the data provided in the CMIP6 experiment, and some of the data needs we have identified.