Wave Energy Resource Assessment and Conversion Technologies

Wave energy represents a vast and largely untapped renewable resource, driven by wind–sea interactions and distant storms. Assessment of this resource relies on a combination of in situ measurements, satellite observations and numerical wave modelling to characterise spatial and temporal variations in wave height, period and direction. Hindcast studies, using advanced spectral wave models, provide long-term datasets that inform estimates of extractable power at coastal and offshore sites. Conversion technologies encompass a diverse array of wave energy converters (WECs), including oscillating water columns, attenuators, point absorbers and overtopping devices. Each design targets specific wave climates and aims to maximise capture width, reliability and survivability under extreme conditions. Recent developments in control strategies, mooring systems and materials science have improved device efficiency and reduced costs. Hybrid systems co-locate wave devices with offshore wind or floating photovoltaics, harnessing complementary resource profiles to smooth output and optimise cable utilisation. Techno-economic analyses are now routinely integrated with resource assessments to produce levelised cost of electricity projections and identify locations where wave energy may become competitive within future energy portfolios. As nations strive towards decarbonisation, coordinated efforts to refine resource characterisation, advance converter technology and streamline supply-chain logistics are critical for elevating wave power to a commercially viable position in the global energy mix.

Research from Nature Portfolio

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Research from all publishers

A recent global techno-economic assessment employed high-resolution hourly wave data and device power matrices to estimate electricity yield and levelised cost of electricity on a regional scale. The study revealed that, although current costs remain above those of established renewables, projected learning rates suggest wave power could approach cost parity with offshore wind by the mid-2030s in regions of high resource intensity. Publicly shared capacity factor datasets now enable more accurate integration of wave generation into energy system models.

Another investigation developed a stochastic optimisation framework for retrofitting existing offshore wind farms with wave energy converters and floating photovoltaic units. By modelling uncertain wave and price inputs via copula-based scenarios, the study demonstrated that hybridisation can enhance economic returns, reduce output variability and better utilise export cables. This approach offers a roadmap for investors seeking to maximise revenue streams from multi-vector offshore installations.

In a regional case study of south-east Australia, a 40-year wave hindcast was conducted using a state-of-the-art unstructured-grid wave model. The analysis detailed long-term trends in wave power, seasonal variability and extreme events, identifying coastal hotspots for WEC deployment. Application of nine device types at fourteen locations highlighted the trade-off between mean energy yield and seasonal stability, informing site-specific technology selection and deployment strategies.

Wave Energy Resource Assessment and Conversion Technologies publication trend

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

Technical terms

Wave energy converter (WEC): A device that transforms the mechanical energy of waves into electrical power, encompassing various architectures such as point absorbers, attenuators and overtopping systems.

Levelised cost of electricity (LCOE): The average net present cost of electricity generation per unit of output over the lifetime of a technology, incorporating capital, operational and maintenance expenses.

Capacity factor: The ratio of actual energy output over a period to the maximum possible output if a device operated at full rated power continuously.

Hindcast: A retrospective simulation using historical meteorological data within a numerical wave model to reconstruct past wave climates for resource assessment.

References

1. Techno-economic assessment of global and regional wave energy resource potentials and profiles in hourly resolution. Applied Energy (2024).
2. Stochastic optimization framework for hybridization of existing offshore wind farms with wave energy and floating photovoltaic systems. Journal of Cleaner Production (2024).
3. A high-resolution wave energy assessment of south-east Australia based on a 40-year hindcast. Renewable Energy (2023).