Rapid Tidal Flow Forecasting for Marine Energy Resource Assessment

Lead Research Organisation: National Oceanography Centre
Department Name: Science and Technology


Developing renewable energy such as tidal turbines requires in-depth assessment of a potential project site to understand suitability, potential energy production as well as impact on the environment. The exploitability of a site is mainly assessed by a combination of extensive field surveys with numerical modelling, which is expensive. Due to budget limitations, critical financial and technical decisions are made on a restricted sample of data leading to high level of risk and uncertainties.

Here we aim to mitigate the issue of data scarcity by fusing established tidal flow analysis techniques with machine learning tools. The new tool will 'learn', from verified gauge data, the best way to temporally extend short-duration spatial survey data to make maps of tidal potential that can directly inform either more spatially targeted surveying, or assessments for optimal siting of tidal stream devices.

The tool aims to make surveying potential sites cheaper by targeted adaption of the survey campaign and more robust analysis of the data than is currently practiced.

This is a proof-of-concept study. The outcomes include assessing whether the tool has sufficient commercial merit to be developed further via a NERC follow-on call.

Planned Impact

If successful the intention is to develop the tool into a licence-able software product. It is envisaged that MarynSol will act as the primary licence partner, enabled by this project to offer a novel, and highly cost effective approach to the design and execution of tidal energy site surveys. NOVA Innovation Ltd will benefit from the results and knowledge gained through the practical development of the tool on their Islay site, and if successful, into the future through the application of the tool and techniques to enable more cost effective and lower risk site development for their portfolio of projects.

Once proven and commercialised, the software could ultimately enable a step change in survey practices across the sector.

The final product is anticipated to be a powerful software tool based on an innovative approach providing guidance on where and when to carry out surveys of potential exploitation sites for tidally-driven renewable energy. At this stage the aim is to deliver the proof-of-concept study. One of the primary outcomes includes assessing whether the technique has sufficient commercial benefit to be developed further with a follow-on call.


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Description We discovered that machine learning can be effectively used to synthesis observed tidal currents to better make predictions about tidal energy yields
Exploitation Route We proposed a NERC Follow-on project to take the idea further, towards commercialisation, but were unsuccessful in the competition.
Sectors Aerospace, Defence and Marine,Energy

Description These techniques developed have been implemented in a smart phone app to deliver coastal tidal prediction globally. Previously the predictions were for the NW European seas only.
First Year Of Impact 2019
Sector Aerospace, Defence and Marine,Leisure Activities, including Sports, Recreation and Tourism
Impact Types Societal,Economic,Policy & public services

Description marynsol 
Organisation MarynSol Ltd
Country United Kingdom 
Sector Private 
PI Contribution Machine learning algorithms to extrapolate tidal current survey data both spatially and temporally, in order to inform the placement of possible tidal stream devices.
Collaborator Contribution Marine surveys of tidal currents from unmanned autonomous vehicles in regions of potential tidal energy extraction.
Impact Too early
Start Year 2018