TIGER Data Collection and Survey Best Practice Report 2022
Data collection, modelling and resource assessment are key stages in the planning of any tidal energy project. This report forms part of the Tidal Stream Industry Energiser (TIGER) project, seeking to support the development of the tidal energy industry. It provides a summary of relevant international standards and other industry guidelines, reviewing a range of methodologies for conducting site assessments.
The best practice for data collection as baseline for tidal resource assessment and engineering design are presented with a focus towards comprehensive site surveys, rather than early-stage initial scoping studies. The report will be a guide to data collection for industry practitioners and researchers, as well as involved stakeholders, investors and decision-makers.
The report emphasises that the requirements and conditions for every tidal energy project are different. The data collection, modelling and assessment processes should be carefully planned, considering site and project specific factors. Expert knowledge is essential to ensure that high-quality data is collected and that the resource assessment is suitable for the project. The cost of data collection campaigns, both financially and in terms of project time, can be significant and a balance needs to be struck when deciding on the scope of marine operations and data measurement campaigns.
Data sharing between institutions and projects can have significant benefits to projects, helping to keep costs down and improving output. The mutual sharing of resources offers improvements that may be beyond the investment potential of a single project. It can be equally beneficial to the industry for pilot projects to provide ‘lessons learnt’ reports following completion.
Numerical simulation is essential for all but the smallest projects and the methodologies employed in site assessment are discussed. All modelled and measured data will contain uncertainties, which should be understood to assign appropriate confidence to key performance indicators, such as Annual Energy Production (AEP) and Levelised cost of electricity (LCOE).