Powered by OpenAIRE graph
Found an issue? Give us feedback

HIPERWIND

HIghly advanced Probabilistic design and Enhanced Reliability methods for high-value, cost-efficient offshore WIND
Funder: European CommissionProject code: 101006689 Call for proposal: H2020-LC-SC3-2020-RES-RIA
Funded under: H2020 | RIA Overall Budget: 4,103,640 EURFunder Contribution: 3,999,640 EUR
visibility
download
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
OpenAIRE UsageCountsDownloads provided by UsageCounts
52
46
Description

The core challenge addressed in this project is the advancement of the entire modelling chain spanning basic atmospheric physics to advanced engineering design in order to lower uncertainty and risk for large offshore wind farms. The five specific objectives of the HIPERWIND project are to: 1) improve the accuracy and spatial resolution of met-ocean models; 2) develop novel load assessment methods tailored to the dynamics of large offshore fixed bottom and floating wind turbines; 3) develop an efficient reliability computation framework; 4) develop and validate the modelling framework for degradation of offshore wind turbine components due to loads and environment; and 5) prioritize concrete, quantified measures that result in LCOE reduction of at least 9% and market value improvement of 1% for offshore wind energy. The requirements for advanced modelling and development of basic scientific solutions necessitates the strong involvement from academic partners (DTU, ETH, and UiB) and research organizations (IFPEN, DNVGL, and EPRI) and potential end users (EDF) to supply relevant operational data for model validation, provide access to cutting edge industrial environment and to open up exploitation pathways beyond TRL5 toward eventual commercialisation. HIPERWIND employs multi-scale atmospheric flow and ocean modelling, creating a seamless connection between models of phenomena on mesoscale level and those on wind farm level, with the aim of reducing uncertainty in load predictions, and broadening the range of scenarios for which adequate load predictions are possible. Improved modelling of environmental conditions, improved load predictions, better reliability assessment and lower uncertainty, cost efficient design and operating strategies, and lower O&M costs will yield a projected 9% decrease in the Levelized Cost of Energy (LCOE) and 1% increase in the market value of offshore wind by the conclusion of the project.

Data Management Plans
  • OpenAIRE UsageCounts
    Usage byUsageCounts
    visibility views 52
    download downloads 46
  • 52
    views
    46
    downloads
    Powered byOpenAIRE UsageCounts
Powered by OpenAIRE graph
Found an issue? Give us feedback

Do the share buttons not appear? Please make sure, any blocking addon is disabled, and then reload the page.

All Research products
arrow_drop_down
<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=corda__h2020::266effeaa63d3516ac2068866af453c6&type=result"></script>');
-->
</script>
For further information contact us at helpdesk@openaire.eu

No option selected
arrow_drop_down