Wind power potential and intermittency issues in the context of climate change

Abstract

International audienceWind power is developing rapidly because of its potential to provide renewable electricity and the largereduction in installation costs during the past decade. However, the high temporal variability of the wind powersource is an obstacle to a high penetration in the electricity mix as it makes difficult to balance electricity supplyand demand. There is therefore a need to quantify the variability of wind power and also to analyze how thisvariability decreases through spatial aggregation. In the context of climate change, it is also necessary to analyzehow the wind power potential and its variability may change in the future. One difficulty for such objective is thelarge biases in the modeled winds, and the difficulty to derive a reliable power curve. In this paper, we proposean Empirical Parametric Power Curve Function (EPPCF) model to calibrate a power curve function for a realisticestimate of wind power from weather and climate model data at the regional or national scale. We use this modelto analyze the wind power potential, with France as an example, considering the future wind turbine evolution,both onshore and offshore, with a focus on the production intermittency and the impact of spatial decorrelations. We also analyze the impact of climate change.We show that the biases in the modeled wind vary from region to region, and must be corrected for a validevaluation of the wind power potential. For onshore wind, we quantify the potential increase of the load factorlinked to the wind turbine evolution (from a current 23% to 30% under optimistic hypothesis). For offshore, ourestimate of the load factor is smaller for the French coast than is currently observed for installed wind farms thatare further north (around 35% versus 39%). However, the estimates vary significantly with the atmosphericmodel used, with a large spatial gradient with the distance from the coast. The improvement potential appearssmaller than over land. The temporal variability of wind power is large, with variations of 100% of the averagewithin 3–10 h at the regional scale and 14 h at the national scale. A better spatial distribution of the wind farmscould further reduce the temporal variability by around 20% at the national scale, although it would remain highwith respect to that of the demand. The impact of climate change on the wind power resource is insignificant(from +2.7% to − 8.4% for national annual mean load factor) and even its direction varies among models