Eco Wave Power has partnered with AI engineering GmbH to develop an artificial intelligence-powered digital twin platform that models how ocean waves interact with wave energy systems, potentially unlocking a new renewable energy source for data centers. The collaboration combines physics-based simulation, machine learning, and real-world operational data to make wave energy technology more predictable, scalable, and efficient across different coastal locations.

Why Are Data Centers Looking to Ocean Waves for Power?

The global AI boom is creating an unprecedented energy crisis. McKinsey forecasts nearly $7 trillion in data center investment globally by 2030, and with it comes a staggering appetite for electricity. Bank of America estimates that power consumption per AI rack could climb to more than 1.5 megawatts by the end of 2030, nearly 100 times that of a conventional server rack. This explosive demand has forced companies to explore unconventional power sources beyond traditional grids, including nuclear reactors, renewable energy, and now, ocean waves.

Eco Wave Power believes artificial intelligence presents two complementary opportunities: making wave energy technology increasingly intelligent and predictive, and positioning wave energy as a renewable source for the rapidly growing electricity demands of AI infrastructure and data centers. The company currently operates projects across the United States, Europe, and Asia, including a grid-connected facility at Jaffa Port in Israel and a pilot station at the Port of Los Angeles.

How Does the AI-Powered Digital Twin Work?

The partnership between Eco Wave Power and AI engineering GmbH focuses on Phase 1 of what they call the "Eco Wave Power Digital Twin and Energy-Aware Computing" project. The initial phase will digitally model how ocean waves interact with Eco Wave Power's proprietary floaters using AI engineering's PAMICS simulation technology, a particle-based multiphysics simulation framework designed for complex fluid dynamics applications.

The collaboration will evaluate several critical factors:

• Floater Behavior: Understanding how the company's wave-capturing devices respond to different ocean conditions and wave patterns.
• Structural Loads: Modeling the physical stresses and forces that the equipment experiences under various sea states.
• Theoretical Energy Input: Calculating how much electricity can be generated from waves under different conditions.
• Machine Learning Forecasting: Developing predictive capabilities for energy yield and system loads based on real-world sensor data.

The companies will compare simulated results with real-world sensor measurements to validate their models and refine their predictions. Both organizations are members of the NVIDIA Inception program, and the project leverages NVIDIA Omniverse for digital twin visualization and NVIDIA Warp for simulation and modeling.

"For us, AI is not simply a software layer that we add to our technology, it is an opportunity to fundamentally improve how we understand, design, predict and ultimately operate wave energy systems," said Inna Braverman, Founder and CEO of Eco Wave Power.

Inna Braverman, Founder and CEO of Eco Wave Power

What Makes Wave Energy a Challenging Engineering Problem?

Wave energy is notoriously difficult to harness because it combines multiple complex variables simultaneously. The ocean presents constantly changing conditions, from calm days to violent storms, and the equipment must withstand enormous structural forces while efficiently capturing energy. This is where the digital twin approach becomes valuable.

"Wave energy is a particularly challenging engineering problem because it combines complex free-surface fluid dynamics, structural motion, and highly variable environmental 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," explained PD Dr.-Ing. habil. Stefan Adami, Co-Founder and General Manager of AI engineering GmbH.

PD Dr.-Ing. habil. Stefan Adami, Co-Founder and General Manager of AI engineering GmbH

By creating a virtual model that mirrors the real-world behavior of wave energy systems, engineers can test thousands of scenarios, optimize designs, and predict performance without building expensive physical prototypes. This accelerates the development cycle and reduces costs.

How Could This Scale Across Different Locations?

A key objective of the partnership is determining how the digital twin can be adapted to different project locations. This is crucial for Eco Wave Power's global expansion strategy. Wave conditions vary dramatically depending on geography, seasonal patterns, and local ocean dynamics. By building machine learning models that understand these variations, the company could transfer engineering knowledge and operational insights more efficiently as it expands into new markets.

Eco Wave Power is expanding globally with projects planned in Portugal, Taiwan, and India, representing a project pipeline of 404.7 megawatts. The ability to rapidly adapt designs and operational strategies to new locations could be the difference between successful deployment and costly delays.

"As our projects grow from pilot installations toward megawatt-scale deployment, we believe Digital Twins and AI can help us learn faster, optimize more efficiently, and transfer knowledge from one project to the next," concluded Braverman.

Inna Braverman, Founder and CEO of Eco Wave Power

Why Is This Timing Critical for Data Center Infrastructure?

The timing of this partnership reflects a broader crisis in data center infrastructure. While companies like Nvidia are racing to produce more AI chips, the infrastructure to power those chips is lagging dangerously behind. Grid connection delays can stretch as long as 24 months in some emerging markets and more than eight years in major developed markets, according to consultancy Pivotale AI. This bottleneck is forcing hyperscalers to explore alternative power sources urgently.

During 2026, Eco Wave Power's technology was featured twice in keynote presentations by NVIDIA Founder and CEO Jensen Huang, and the company was featured in an NVIDIA corporate blog exploring the longer-term potential for ocean-powered data centers. This high-profile visibility signals that major players in the AI industry are taking wave energy seriously as part of the solution to the power crisis.

The convergence of AI-powered optimization and renewable energy infrastructure represents a novel approach to solving one of technology's most pressing challenges. By using artificial intelligence to make wave energy systems smarter and more predictable, Eco Wave Power is positioning ocean waves as a viable renewable power source for the data centers that power the AI revolution itself.