Wedoany.com Report-Mar 28, CorPower Ocean has secured financial backing from Vinnova, Sweden’s national innovation agency, to adopt AI and test its ability to drive performance and control in wave energy technology.
The WACE (Wave energy AI-based Control Enhancement) Project is now underway and is set to run until November 2025. CorPower Ocean is being supported by project partner NTNU (Norwegian University of Science and Technology) – known for education, research, and innovation for engineering systems in the marine environment.
It comes shortly after the Swedish tech developer secured EUR 32 million ($34.5 million) Series B funding to support the commercial roll out of its technology meant to move wave energy towards a bankable mainstream energy source. The investment followed CorPower Ocean’s commercial scale C4 device surviving the “largest Atlantic storms on record” while efficiently generating power in regular ocean conditions.
WACE Project Lead and CorPower Ocean Control Engineer Gabriel Forstner said wave energy converters have gained widespread attention for decades, and AI-based methods have large potential to improve operating strategies. “The optimal operation of wave energy converters is one of the key factors to lower the levelized cost of energy (LCOE) ultimately making it an attractive part of the future clean energy mix. The main goal of the WACE Project is to combine AI methods with optimal control to enhance our existing operating strategy and further improve the performance of our point absorber type wave energy converter.”
A model-based design framework will be used in the WACE project. After establishing requirements for the closed-loop control system, an AI-based optimal control strategy is being designed along with a hardware-in-the-loop (HIL) test setup.
CorPower Ocean anticipates that their WECs are operated in arrays or farms which will generate large amounts of data. This project also aims for utilizing the available data to enhance an existing model-predictive control strategy combining optimal model-based control with AI.
This combination is meant to allow the exploration of more performant control schemes while keeping the WEC in its feasible operating region. The performance of the developed algorithm will be validated using HIL testing, providing a realistic real-time environment while using the existing operating strategy as a baseline.
A key feature of CorPower Ocean’s technology is its ability to tune and detune according to ocean conditions, limiting the response to storms and amplifying the motion and power capture in normal waves. The company argues this has been demonstrated during the C4’s operational period in Aguçadoura. The tuning and detuning feature of CorPower Ocean’s WECs can be compared to wind turbines, where all modern turbines have a function to pitch the blades to alter the response to the wind conditions, limiting loads in storms while optimizing yield in regular conditions.
Commenting on anticipated results from the WACE Project, Forstner added that numerical models are commonly utilized to develop an optimization-based control strategy for wave energy converters (WECs). “The idea of this project is to utilize an existing control algorithm for WECs and combine it with AI-based methods to improve the performance of the overall closed-loop control scheme,” he said. “This approach is not limited to WECs and can be extended to improve existing control algorithms in a wide range of industrial applications.”
Wave farm projects are being developed by customers using CorPower Ocean’s technology along the Atlantic Arc, including sites in Scotland, Ireland, Portugal and Norway. One project is being developed by Ireland’s state-owned energy supplier, ESB, off the coast of County Clare, following two decades of investigating a wide variety of technologies. The pre-commercial phase of the Saoirse Wave project, will involve CorPower Ocean WECs (Wave Energy Converters) as part of a CorPack cluster.
