Using AI to improve wave energy efficiency
CorPower Ocean is developing AI modelling for wave energy, which aims to enhance offshore renewable efficiency through improved control and greater autonomy in energy production.
The Wave energy AI-based Control Enhancement (WACE) project, created in partnership with the marine engineering institution NTNU and supported by Sweden’s Vinnova, aims to optimise wave energy performance using AI-driven control systems.
“AI-based methods have large potential to improve operating strategies,” said Gabriel Forstner, WACE Project lead and CorPower Ocean control engineer.
“The optimal operation of wave energy converters is key to lowering the levelised cost of energy (LCOE), making it an attractive part of the future clean energy mix.”
Commercialisation focus
The initiative, running until November 2025, builds on CorPower Ocean’s recent €32m Series B funding to commercialise its wave energy converters (WECs).
The project employs a model-based design framework, integrating AI with predictive control to refine performance.
By analysing vast datasets from WEC arrays, CorPower Ocean aims to enhance energy capture while ensuring resilience against extreme weather conditions. This innovation mirrors wind turbine technology, where blade pitch adjustments optimise power generation and storm resistance.
Wave farm projects already utilising CorPower Ocean’s technology are advancing along the Atlantic Arc, including in Scotland, Ireland, Portugal and Norway.
One flagship initiative, Ireland’s Saoirse Wave project, has secured €39.4m in EU Innovation Fund co-funding, underscoring the growing momentum behind AI-driven wave energy solutions.
Related Articles
ELECTRICAL SYSTEMS
ENVIRONMENT
ENVIRONMENT