26 Jan Using Machine Learning in the Wind Energy Sector
The measurement of various indicators and an advanced analysis of them, allows anticipate an error even before it shows obvious signs of it.
These scientific tools developed by Saroen to predict when a wind turbine may fail, will automatically give you the opportunity to take actions to mitigate the impact into its expected production level.
Early detection according to behavior patterns allows us to plan situations such as:
- The purchasing or stock of spare parts
- The transport of components to the park
- The scheduling of the optimal timing for a down time
To use this technics to avoid loss of production and increase return on investment is known as smart management of wind assets
To know more about how machine learning con increase return on investment of renewable assets visit our Trend Diagnosis Page.