Software capable of predicting the size and strength of waves could help double the amount of renewable power taken from the sea, engineers believe.
Wave energy developers have long had their eye on the UK’s south-west coastline, particularly northern Cornwall and the Scilly Isles. It faces the powerful Atlantic swell and has been earmarked for significant EU and UK Government funding to support leading-edge research in the region.
The latest move is a promising two-year experiment to predict wave power that its backers say could double the amount of energy extracted.
Until now, says Exeter’s Dr Markus Mueller, developers have been reliant on Met Office data that predicts average wave lengths and amplitudes in periods of 30-60 minutes, and over relatively long distances. This statistical approach is limited, he says, because every single wave varies from the average.
The research focuses on point absorbers: floating structures, like buoys, with components that move relative to each other in response to the wave. This motion generates energy which can be fed back to the grid.
The team has developed an algorithm that can be run by a processor attached to the point absorber as often as five times per second. It predicts the height of coming waves, allowing the absorber to respond to each wave individually, by fine-tuning the resistance of its inner components in order to collect the maximum energy possible. Critically, it can also be programmed to minimum resistance when waves are too strong, avoiding damage.
Dr George Aggidis of Lancaster University, a leading wave energy engineer, says the research is a positive step forward.
The research is now set to be tested on a larger scale, with further EU funding, and as part of a broader existing partnership with Ocean Power Technologies, a developer of wave energy devices. The prizes could be high. The development of marine energy may be as much as 30 years behind that of wind power, but it has the potential to provide the UK alone with electricity twice over. – Virginia Marsh