Learning tidal currents

Completed

Renewable Energy Sources(Ocean Energy)

Basic and strategic applied research

PHYSICAL SCIENCES AND MATHEMATICS (Applied Mathematics)

Not Cross-cutting

Dr T Adcock
Engineering Science
University of Oxford

Standard

EPSRC

22 June 2015

21 December 2016

18 months

£98,208

Energy

South East

NC : Engineering

Dr T Adcock, Engineering Science, University of Oxford

Dr M A Osborne, Engineering Science, University of Oxford

Project Contact, The UK Hydrographic Office
Project Contact, E.ON E&P UK Ltd

Tides occur due to the changing gravitational movement of the Moon and Sun relative to the Earth. As astronomical movements are highly predictable the tides should also be predictable. This is one of the key advantages of tidal stream energy (a rapidly developing source of renewable energy). The existing methods which are used to predict tidal movements perform very well for predicting water levels and slow moving currents, but often perform very badly on fast flowing tidal streams of the type in which we areinteresting in placing tidal turbines. This project will address this by applying methods from the machine learning community to the analysis of fast flowing tidal streams. This will produce an algorithm which will allow users from the oceanographic and tidal energy community to greatly improve the prediction of tidal currents at any point indefinitely far into the future. Thus a robustprediction of the performance of tidal stream turbines can be obtained. In the rapidly growing area of tidal stream energy, accurate knowledge of the tidal currents is vital for: robust predictions of energy yield; for the calculation of loads and the design of the turbine; and to give confidence to investors

20/07/15