When our recent report, "Optimizing Wind Energy in Turkiye: Performance, Trends and Financial Insights," (get your copy) was first released during the week of WindEurope 2025, investors were particularly intrigued by how significantly annual capacity factors could vary, stemming from changing wind regimes and directly impacting the financial outcomes of their assets.
The average capacity factor nationwide in 2023 dipped to 32.64% with a 3.17% drop from 2022, and gained most of the loss back in 2024 with a 2.29% lift to 34.93%. The drop in 2023 was as high as 6.09% in the Aegean region (the western part of Turkiye), aligning with the wind slowdown of 0.46 m/s on the regional average (the plot below displays the case in other regions with a strong wind energy footprint).
The wind drought observed in 2023 fueled concerns over the predictability of returns from wind energy investments, hence the interest from readers of our report. Because everyone in the wind energy industry values data-backed insights to better understand the factors that impact their financials, this raises the question: How predictable are the year-to-year variations in wind, and what do we understand about its dynamics?
Interannual Variability In The Wind Regime
Wind isn't random, but it's definitely complicated. Variability arises from large-scale climatic interactions, such as the North Atlantic Oscillation (NAO), which drives storm tracks and affects wind intensities across Europe. For example, in Northern Europe, annual wind energy density can fluctuate by more than ±25%, meaning "windy" years can be drastically different from "calm" ones (Pryor et al., 2006).
An analysis spanning from 1957 to 2011 showed wind speeds in the UK could swing around ±4% annually. That might sound modest, but it translates directly into about ±7% variation in capacity factors (Watson et al., 2015).
Across the Atlantic, the US faces even more pronounced variability. Climatic phenomena like El Niño and the Southern Oscillation (ENSO) can cause wind speeds at individual locations to vary by up to 30%, significantly affecting wind regimes (Hamlington et al., 2015)
What Can Investors Do About It?
Although advanced meteorological models do exist to help map out the uncertainties in regional interannual changes with wind regimes and their effect on capacity factors, site-specific predictions still remain a challenge due to the additional complexity brought by environmental conditions such as topography or localized weather dynamics.
Our report highlighted that wind speeds from different farms even in the same region can be quite different, as displayed in the correlation matrix below— amber colored cells indicate farms exhibiting no correlation, even slightly negative correlation (values closer to 0 represent weak or no correlation).
The study from the UK found that interannual variability is very localized, even among relatively close sites (some as little as 200 km apart).
Yes, in the renewables industry, we have the ‘luxury’ that no other industry has: investors don't pay for the resource. But that does not mean it comes at no cost. With this much stochasticity—which is the actual cost of wind energy—relying on financial gains from wind regimes would not be the best choice for most investors.
Therefore, gaining extra production from identified performance drops in turbines and preventing downtimes should remain the number one priority in wind energy operations. As the famous Epictetus quote reminds us:
"Make the best use of what is in your power, and take the rest as it happens."
References:
Hamlington, B. D., Hamlington, P. E., Collins, S. G., Alexander, S. R., & Kim, K.-Y. (2015). Effects of climate oscillations on wind resource variability in the United States. Geophysical Research Letters, 42(1), 145-152. https://doi.org/10.1002/2014GL062370
Watson, S. J., Kritharas, P., & Hodgson, G. J. (2015). Wind speed variability across the UK between 1957 and 2011. Wind Energy, 18(1), 21-42. https://doi.org/10.1002/we.1679
Pryor, S. C., Barthelmie, R. J., & Schoof, J. T. (2006). Inter-annual variability of wind indices across Europe. Wind Energy, 9(1-2), 27-38. https://doi.org/10.1002/we.178
Image credit: NOAA
