Light TouchBig Impact
Reoptimize Systems combine turbine performance data with simulation modelling and machine learning to optimise renewables assets for stronger energy output, longer asset lifespans and lower maintenance costs.
Higher Output, Longer Lifespan
— Optimised for Success
Our patented Global Loss Minimisation algorithm represents a paradigm shift in the sector — an end-to-end, zero intervention route to increased performance, lower maintenance expenditure and reduced shutdown time.
The continuously learning algorithm threads together real performance data from your asset(s) and 'digital twin' models to identify the optimal control settings based on all the distinct environmental and mechanical factors at play.
These adjustments can have a significantly positive impact on the amount of energy produced by your assets and the profitability of your operations.
Increased
Output
Recalibrated control parameters enable enhanced performance and more consistent output.
Reduced
Downtime
Shutdowns due to excess loadings, vibrations or maintenance issues are reduced thanks to key control adjustments.
Lower
Loadings
New parameters based on the environmental conditions of your asset — minimising instability, vibrations and excessive pitch action.
Built in Academia, Backed by Industry
Control Parameters Shaped by Real World Data
The Reoptimize Systems Process
We work with each customer on an individual basis — optimising the turbine system as a whole — but on most projects our process can be broadly mapped out into the following stages:
1.
SCADA DATA COLLECTION
2.
GLOBAL LOSS MINIMISATION ALGORITHM
3.
OPTIMISATION OF CONTROL PARAMETERS
4.
TURBINE OPTIMISATION VERIFICATION WITH NEWLY ADJUSTED PARAMETERS
How we optimise
turbine systems
Discover how Reoptimize Systems has been tested and proven delivery in a live environment.
Implementation downtime
0hrs
Typical AEP increase
0%
Max reduction in tower loads
0%
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.
Download
Built in Academia,
Backed by Industry
Our core technology was developed during Co-Founder Juan Pablo Echenique's PhD studies at The University of Edinburgh, Scotland — across several years of R&D work in wind and tidal energy systems.
Since then, we have worked with major organisations such as Siemens and GE on concept and project work. You can browse some examples of our recent work on the Projects page.
