Insights / Field note · Wind16 June 2026

When a power curve falls, is the turbine really ageing?

A measured power curve that drops over the years looks like ageing. Several other causes produce the same shift, and only one is real degradation.

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It is tempting to read a falling power curve as a turbine wearing out. Sometimes it is, however often this may be only part of the cause. This note looks at 10 years of operating data from one wind farm and asks what a power curve can, and cannot, tell us on its own using the turbine's own anemometer.

Measured power curve by calendar year. Mean power against density-adjusted wind speed, filtered to normal operation. The curve drifts down over the decade, mostly in the mid-curve.

What the curve shows

Recorded power per measured wind speed bin drops over the 10 years.
The largest change is in the mid-curve.
That is the steepest part of the curve, so any sideways shift shows as a large vertical gap.

A cleaner view, the power coefficient

The same data as a power coefficient, Cp, normalises power by wind speed cubed. It gives a tidier view of aerodynamic efficiency.

Cp falls too, most visibly near its peak around 7 to 8 m/s.
A drop near the Cp peak points more directly at blade aerodynamics, erosion or soiling.
But Cp still uses nacelle wind speed, so it carries the same measurement caveats as the power curve.

Power coefficient by calendar year. Cp peaks near 7 to 8 m/s and falls over time, but is still referenced to nacelle wind speed.

Why a drop is not proof of lost performance

Several causes produce the same downward shift. Only one is real degradation.

Blade leading-edge erosion or surface soiling. The one cause that is genuine degradation.
Nacelle wind measurement. The sensor sits behind the rotor and relies on a transfer function that can change and the calibration of the anemometer can drift, so the x-axis itself can move.
Control changes, operational changes and turbine upgrades over the period.
Year to year differences in conditions beyond wind speed and density.
Filtering bias, for example curtailment removing certain wind sectors.

There is also what the curve leaves out. This data is filtered to normal running only. So it does not capture how other losses, such as downtime and curtailment, change over time. Those often move annual energy more than the filtered curve does.

In short

A measured power curve is a good first indicator of how a turbine ages. It is a poor final answer. Confirming a real change needs an independent wind speed reference, such as a met mast or LiDAR, and loss accounting that includes downtime and curtailment. The skill is in not overreading it.

Charts and analysis by PowerVeritas. Where open datasets are used, sources are credited on the attributions page.