Wave Energy Conversion Technologies

Wave energy capture harnesses the oscillatory motion of ocean waves to generate electricity through specialised devices known as wave energy converters (WECs). These vary in form and scale, encompassing point absorbers that float and heave with individual power take-off (PTO) units, oscillating water columns (OWCs) that drive air turbines, attenuators aligned with wave direction, overtopping devices capturing and releasing seawater, and emerging terminator or hybrid systems. Hydrodynamic design underpins energy-capture efficiency, demanding precise modelling of wave–structure interactions, mooring dynamics and fluid non-linearity. Integration of advanced numerical methods—from potential-flow theory to Reynolds-Averaged Navier-Stokes (RANS) and Large-Eddy Simulation (LES) models—has enhanced predictive accuracy, though at rising computational cost. Innovations in PTO mechanisms, such as hydraulic, pneumatic or direct-drive electrical generators, aim to improve energy smoothing and reliability under variable sea states. Concurrently, control strategies and co-design approaches optimise power output and device survival, adapting damping and phase control to sea conditions. Resource assessment and site selection now increasingly benefit from machine-learning forecasts, refined by high-resolution wave models. Despite significant global wave resource potential, commercial deployment remains nascent owing to high capital expenditure, maintenance challenges in harsh marine settings and grid-integration complexities. Collaborative frameworks spanning academia, industry and policymakers are essential to mature technology readiness, reduce costs, and align with coastal protection or multi-use platforms. Ongoing research continues to elevate understanding of hydrodynamics, material resilience, control integration and resource forecasting, laying the foundation for viable wave energy farms contributing to renewable energy portfolios worldwide.

Research from Nature Portfolio

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Research from all publishers

Recent analyses of oscillating water columns have advanced computational modelling by benchmarking diverse CFD approaches, including RANS and LES, against experimental data to resolve fluid-structure interactions more faithfully and guide efficient OWC design. Reviews of control technology underline the pivotal role of optimal and robust control strategies, data-driven model identification and co-design principles in maximising power capture while safeguarding device integrity in stochastic sea states. Emerging studies in machine learning and deep learning have demonstrated enhanced wave-energy forecasting and automated optimisation of PTO parameters, yielding improved convergence rates in device configuration and more accurate short-term resource predictions essential for grid dispatch and operational planning.

Wave Energy Conversion Technologies publication trend

The graph below shows the total number of articles in wave energy conversion technologies across all publications each year (not limited to Nature Index journals).

Technical terms

Wave Energy Converter (WEC): A system that transforms the mechanical energy of ocean waves into electricity.

Oscillating Water Column (OWC): A type of WEC in which wave-induced water motion compresses and decompresses an air chamber to drive a turbine.

Power Take-Off (PTO): The mechanism or subsystem that converts mechanical motion of a WEC into electrical energy, often via hydraulic, pneumatic or direct-drive systems.

Computational Fluid Dynamics (CFD): Numerical methods and algorithms for simulating fluid flow and wave–structure interactions in WEC design.

Control Co-Design: An integrated approach that concurrently develops mechanical design and control strategies to optimise WEC performance and reliability.

References

1. A review of computational methods for studying oscillating water columns – the Navier-Stokes based equation approach. Renewable and Sustainable Energy Reviews (2023).
2. Empowering wave energy with control technology: Possibilities and pitfalls. Annual Reviews in Control (2023).
3. A review of machine learning and deep learning applications in wave energy forecasting and WEC optimization. Energy Strategy Reviews (2023).
4. Ocean Wave Energy Converters: Status and Challenges. Energies (2018).
5. Mathematical Modelling of Mooring Systems for Wave Energy Converters—A Review. Energies (2017).
6. Point Absorber Wave Energy Harvesters: A Review of Recent Developments. Energies (2018).