ES 
FR Cutting-edge expertise and digital research on wind systems
In addition to WindDATA, WindDEEP and WindCAST, Zelya Digital Energy Management also offers a wide range of tailored services.
These services enable the leveraging of the best of the latest digital technologies to deeply explore the functioning of your wind farms and integrate them into the management of your other energy assets.
Our fields of expertise
Data aggregation & Development of Customized Interfaces
Based on your internal energy flows and external available data (wholesale power prices, wind predictions, network capacity...), we help you build coherent data bases, with 3 key objectives:
facilitate further integration of additional data
draw up simple and comprehensive web interface to monitor and analyze this data
enable AI analysis based on this data
DeepScada: Centralized Analysis of All Your Facilities
We harmonize your various data sources, whether they come from solar, hydroelectric, or battery assets, by cross-referencing with your key information.
Homogenization of existing SCADA systems at no additional cost, on cloud or dedicated server
Integration of balancing data, spot prices, and weather data
Intuitive economic and technical analysis of past and future operations
Data exportation & APIs for optimized integration into other corporate tools
Machine Learning, Deep Learning, Genetic Algorithm modeling
We leverage our expertise in algorithms, neural networks, and technical audits of wind farms to make sense of data, facilitate analysis and decision-making.
Treatment, homogenization and AI analysis models based on real time data
development of modules for forecasting, predicting and optimizing maintenance and operation in function of modeling of past and actual data using AI models
AI and Digital Twins to Optimize Energy Management
WindDeep participates in Europe’s most prestigious research programs, collaborating with industry leaders such as the ITN Institute of the Paris School of Mines, to advance the digitalization of wind energy. For the past two years, we have been dedicated to designing digital twins, virtual models that replicate wind turbines in real time, enabling a better understanding of their behavior, interactions with the environment, and connected systems.
Thanks to artificial intelligence and deep learning, we analyze massive datasets to predict failures before they occur, reduce downtime, and boost energy efficiency by up to 10%. Our goal is clear: to transform wind farm management with predictive solutions that maximize performance and sustainability.