A research project connecting adverse weather and climate with AI and renewables
How to we best assess current and future hot spots vulnerable to impacts of adverse weather and climate (change) on renewable and energy infrastructure? How to best use physics, physical-numerical models, and AI tools to approach future challenges on the renewable infrastructure?
Our approach
ENGAGE
Focus on interaction with stakeholders and users
to tackle possible current and future vulnerable hot spots of renewable infrastructure under adverse weather.
DEVELOP
Develop physics-informed machine learning algorithms
to detect adverse weather for renewable infrastructure in weather forecasts and climate scenarios.
RISK AWARNESS
Estimate and quantify the effect of adverse weather
for renewable infrastructure of events, changes in intensity, shift of (current/future) location of hot spots.
WANT TO ENGAGE WITH US?
Renewable energy, risks, and adverse weather can affect all of us. Do be able to provide accurate and precice information on current and future risks, we need to know what you feel are adverse events prone for risking your renewable infrastructure.
Statistics
14.000 hydropower, +300 wind farms, 7.000 km cables
€ 1 billion annual costs caused by adverse weather in Austria
87% of energy production in Austria through renewables