What We Do

Transforming the Future of Wind Turbine Efficiency

Reoptimize Systems offer the elegant, data-driven way to optimise renewables assets for stronger performance, longer life and lower costs.

Utilising machine learning and analysis of high resolution data, Reoptimize Systems’ patented Global Loss Minimisation algorithm represents a paradigm shift in the wind energy sector — offering improved energy output, reduced downtime, extended asset lifespan and a reduction in maintenance/repair costs.

Backed by years of research and experience in academia and the field, the Reoptimize Systems team are adept at seeing these vital operational efficiencies — in high resolution — and delivering with accuracy.

The Optimised Power Curve

We tailor the control parameters of each turbine to guarantee the best possible power curve for each individual turbine and its inflow wind conditions.

In most cases, this involves an improved cut-in behaviour at the bottom of the curve, an increased overall Cp at medium winds, a significant power uplift when transitioning to rated power, and never going beyond the rated power design.


The Results


Average improved energy yield — the new power curve will result in a higher AEP compared to baseline conditions.


Average reduction in Damage Equivalent Loads — the new control parameters will minimise turbine instability, tower vibrations, and excessive pitch action.

Example Case Study

Tested and proven delivery in a live environment from a recent project in Germany.

AEP Improvement



Turbine noise-curtailed, at least 3 alarms of over-speed per year before optimisation. Regular power de-rating due to excessive vibrations.

Peak Damage Loads Reduction



  • Energy availability estimated to be increased by at least 2%
  • AEP + 2%
  • Unwanted shutdown due to over-speed and vibrations completely eliminated.
Implementation Downtime

0 hrs

TURBINE: SWT2.3-93 (variable speed)

2022 White Paper

We recently published a white paper providing more details on our approach and a pilot optimisation project on a Siemens 2.3 MW turbine.

If you're interested to learn more about what we do for customers, this will provide a succinct overview for consideration.