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After two years of research, CT has successfully developed a Deep Learning-based control model that addresses the dynamic challenges of autonomous AWE system operations. In collaboration with Carlos III University of Madrid, CT showcased the results of the latest validation tests in a simulation environment for the AWES control system at the European AWES Congress, AWEC2024, in Madrid, demonstrating precise wind alignment and optimal energy generation trajectories.
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“AWE systems, a new technology that is revolutionizing the generation of wind energy”. An article by Agustín Arjonilla, AWES manager.
Read more“Ecomobility presents significant challenges, but also a great opportunity to deploy the best digital technology for managing the autonomous capabilities of vehicles, integrated into current traffic management. This is an opportunity to make cities more agile, less congested, and where local transport and delivery services can operate more smoothly.” An article by Santiago Ferrer Jover, Project Manager.
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