Eco Wave Power has completed the first phase of an AI-enabled digital twin for its onshore wave energy technology in partnership with Germany’s AI engineering GmbH.
The first phase focused on how ocean waves interact with Eco Wave Power’s floaters. The partners developed initial machine-learning tools to forecast power output and loads, and assessed how the model could be adapted to sites with different wave conditions.
“Our goal is to create a physics-based digital representation of Eco Wave Power’s system that links high-fidelity simulation with operational data,” said Stefan Adami, co-founder and general manager of AI engineering GmbH.
The proposed second phase would extend the model to the hydraulic and mechanical systems that convert floater motion into electricity. A third phase would bring in operational sensor readings, environmental measurements and actual generation data. A fourth would expand the use of machine learning to forecast output, predict system behaviour and optimise operation.
“Phase 1 gave us the digital foundation. The next stages are about connecting that foundation to our full energy-conversion system, real-world data and ultimately AI-driven operation,” said Inna Braverman, founder and CEO of Eco Wave Power.
Eco Wave Power’s US operation and AI engineering are both members of NVIDIA’s Inception programme. The partners are using and evaluating NVIDIA Omniverse and Warp for visualisation and simulation, alongside accelerated computing for modelling and machine-learning development. NVIDIA Networking has provided a letter of support for a related research proposal submitted to the Israel Innovation Authority. Any assistance would depend on the proposal securing funding and the companies reaching a written agreement.
Eco Wave Power said it is in discussions with data centre developers and infrastructure partners about supplying wave-generated electricity to coastal and nearshore facilities. It is also developing technology to connect its generating systems to data centre infrastructure and to measure, verify and settle electricity deliveries. In a potential application of the digital twin, wave power forecasts could be used alongside demand, storage and grid availability data to help schedule computing workloads around expected generation.
