For the past 3 years, the Data department has been investing in R&D for condition-based maintenance, to detect temperature anomalies and production under-performance.
This year, this work led to the implementation of an automatic underperformance detection algorithm for the entire fleet.
VALEMO has set up a new internal platform, a “data lake”. This innovative system is capable of bringing together heterogeneous data from wind farms in a variety of formats and architectures. While this algorithm works easily with recent fleets, our aim is now to extend this data collection to older fleets, whose technology is much more heterogeneous.
To achieve this, we have invested heavily in the installation of data loggers at around ten sites, enabling us to acquire data directly and bring it into line with our standards. As far as photovoltaics is concerned, we have set up our own data acquisition system to guarantee total control of the data, from its origin to the dashboard.
Our algorithms for detecting under-performance and temperature anomalies enable us to guarantee our customers complete control over the data, enabling them to maximize profits and optimize park production. Our operations managers, in close collaboration with our data analysts, can thus anticipate future breakdowns and suggest corrections to machine operation (realignment of blades, nacelle, adjustment of clamps, etc.)
This modernization of data collection represents a major step forward in our quest for efficiency and operational excellence. By enabling our customers to make the most of their assets, we are actively contributing to the transition to more sustainable and efficient energy production.
