Wind resource variation over time is the main cause of the variation of the production output of a wind farm.

Wind energy indexes allow to quantify the variation of the wind resource on a given period and thus constitute an efficient tool to get an overview of the behavior of a wind farm portfolio for a competitive cost. Using wind energy indexes as a macro scale tool can be considered as the first step before deciding or not to carry out a deep analysis of SCADA data per turbine.

irec indexes are mainly based on data issued from ERA5 reanalysis.
ERA5 is a climate reanalysis dataset, covering the period 1950 to today, which is developed through the Copernicus Climate Change Service (C3S). ERA5 is the fifth major global reanalysis produced by ECMWF. Data from ERA5 cover the Earth on a 0.25° grid and on an hourly time step.
These data have been converted into production data to ensure that irec indexes are directly comparable to your wind farm production output.

Year-to-date indexes provide the ratio between the wind energy available over a given period and the long-term average for the same period.

As an example, an index of 95% for January to March 2026 means that in the region considered, the production expected for this first quarter should be 5% below what can be expected for the period January-March on the long-term average.

Accessing monthly indexes will allow to get a clear overview of the production capacity of your wind assets, and follow it over time.

A feedback experience on more than 200 operational wind farms around the world (especially across Europe) allowed to validate the reliability of irec indexes. The average correlation coefficient between irec indexes and actual production data is about 97.5% prior to any filtering, and it exceeds 94% for 9 out of 10 wind farms tested..
The lowest correlation levels encountered are often in quite complex areas subject to quick variation in space of the wind regime (small predefined regions).

Let’s keep in mind that the level of uncertainty month by month remains quite high. This uncertainty is inherent in wind energy indexes themselves (not made from on-site wind measurements) but could also be linked to each wind farm specificities (unusual wake effects due to a particular monthly wind rose…) . Thus, a conclusion cannot be drawn from a single month. However, a trend analysis or a look at cumulated periods can lead to a quite finer analysis.

Globally, the use of wind energy indexes can allow to ensure the stability of the production capacity of a farm within a ± 3 % range while considering cumulative production periods. A drift in performance can thus be suspected outside this range (more details on the poster presented in the WindEurope Technology Workshop).

Learn more about this topic attending Windex training sessions.

First of all, did you make sure of the following points?
1- Is your wind farm inside the predefined region?
Use the tool on the left-hand menu to make sure, ask for a customized index if not.
2- Are your production data adjusted to 100% availability (Ideal production)?
Wind energy indexes reflect the wind resource that can be harnessed by a wind farm with no availability issues. That is why the production output should be corrected from production losses encountered by the wind farm. All causes of downtime, except for lack of wind should be taken into account.
3- Is your wind farm submitted to a significant curtailment?
If yes, corresponding production losses should be accounted for.

Once ruled out these causes, note that all modelled data as ERA5 are subject to uncertainties, especially in complex areas and/or in areas with a very local wind regime. Such uncertainty on modelled data can lead to lower correlation levels in a few cases.

Need further clarifications? This topic will be discussed in Windex training sessions.

The predefined regions cover areas with the highest density of operating wind farms worldwide.

For onshore wind farms, these areas are primarily delineated by circles on the maps, representing zones of varying sizes where the wind regime remains consistent over time (e.g., similar wind resource patterns).

For offshore wind farms, a dedicated pictogram is used to indicate specific maritime zones along European coasts, where significant offshore wind power capacity is operational.

On the online indexes, regions are color-coded based on the year-to-date index value.

	Energy index < 97% (wind resource on the period lower than on average for the same period)
	Energy index 97%-103% (wind resource on the period close to the average for the same period)
	Energy index > 103% (wind resource on the period higher than on average for the same period)

See the list of predefined regions

Regions presented as dots on the map (“+” sign) correspond to areas with very local wind regimes, with a high probability of variation over short distances.
On the opposite, big predefined regions reflect the fact that the wind regime is similar on large areas.

Predefined regions correspond to circles as far as possible in the interest of simplification. However, in several areas the wind regime did not permit to define circles, and ellipses were favored to match the specificity of the wind resource.

Use the dedicated tool of the desktop version of the website.

Predefined regions delimited by circles corresponds to onshore areas. Predefined regions for offshore areas are marked with a dedicated pictogram and correspond to restricted areas located all around European shores.

If your Offshore wind farm is not located on these predefined areas, customized index can be generated on demand.

If a location of interest is not covered by our predefined regions, indexes can be ordered and generated on demand for customized locations, no matter where in the world. Our customized indexes take into account the actual location of the wind farm and upon request the specific power curve of your wind farm, a specific long-term reference period, a specific calibration on you farm production. Ordering indexes on customized locations in addition to other predefined indexes will allow you to get a complete solution, delivered in a single format, for your entire wind farm portfolio.
Be careful if you are outside predefined regions, especially small ones. The wind regimes can vary on very short distances in some places.

All irec indexes on predefined area take into account the period January 2011-December 2020 (10 years) as the long-term reference period. In the wind industry, a decade is a standard reference period, and not going far back in time allow to limit the risk of inconsistency of the data over time. More than the duration of the reference period, one of the key issues when comparing indexes year after year is the stability of this reference period. Thus, in order to maintain values comparable between each other from one year to another, this reference period will remain constant for upcoming years.
Each new year a conversion factor can be provided to allow a translation of the energy indexes from the fixed long term reference period to the most recent decade.
Note that indexes on customized locations can allow you to get indexes on the long term reference period of your choice.

irec indexes can be generated for the production monitoring of your PV plants. Solar indexes are provided under the same format and are generated for each plant specifically. Contact us for more information.

Eoltech provides training sessions designed to help asset managers and investors to make the most of wind energy indexes. Both short 2-hour online sessions and full-day in-person workshops are available.

Such sessions can allow you to answer to the following questions:
• How to explain the production variations of my wind farm?
• What are the main applications for wind energy indexes?
• How to use an annual / a monthly index?
• How to check the stability of my production capacity?

Get pratical information about the one-day sessions here: Windex, a training session proposed by Eoltech

Any other question? Contact us