SOURCE-LINKED INTELLIGENCE

Farm-noise: AI-based optimization to minimise tidal turbine noise and the impact on marine fauna

CORDIS · observation · Publication date unknown

the extracted physical insight, accurate surrogate models for turbines and associated acoustics will be developed to enable optimization of farms that minimize noise while ensuring energy production. Machine learning based reinforcement learning methodologies will be used to optimize and control the trade-off between energy production and noise emission. Compromises between energy and sound generation will finally be reached automatically for specific sites taking into account ambient conditions and local fauna. The expected research results will not only provide theoretical and methodological support for the design and silent operation of large tidal farms but also promote the ecological sustainability of the tidal industry. The outcomes and impacts will be maximized and disseminated to various communities by peer-reviewed articles, conferences, workshops and outreach activities, etc. acoustic; tidal turbine; large eddy simulation; surrogate; reinforcement learning; machine learning; optimization and design; marine animals; noise emission

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recordType

award

status

SIGNED

region

EU

value

181152.96

unit

EUR