09 Feb Computing Development Update: Are your Renewable Assets Smart?
Drive train components are causing significant production losses and are often underestimated, Saroen’s AI and computational algorithms allows owners to predict performance deviations.
Renewable energy company Saroen Global is continuously developing computing tools that combine leading wind industry expertise, data science and machine learning to quantify and provide actionable insights to help mitigate the lost energy production caused by drive train components failures.
“To maximize production, wind farms owners need the ability to proactively monitor and understand the lost energy impact of inappropriate control parameters and drive train components faults in their wind turbines. The tools available on the market have been discouraging for wind farm owners. We’ve seen many of our clients ignoring the issues as they didn’t have the tools to monitor or understand them, and it’s costing them significant amounts of money.” said Alberto Buey, CEO of Saroen.
Smart renewable assets should taking to account these kind of topics:
- Development of computational models oriented to machine learning
- Diagnostics based on the CMS – Condition Monitoring System
- Forecast from vibration spectrum data
- Constant evaluation of failure trends
- Early detection of error trends
- Smart scheduling of stops
About Saroen: Saroen is a renewable energy advanced advisory 4.0. that combines deep knowledge of wind and solar energy market with cutting-edge technologies to deliver agile, digital, online and smart renewables assets management.