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Facilitating a smoother transition to Renewable Energy with AI (AI4Renewables)

Joyjit Chatterjee · Nina Dethlefs



With rapidly rising carbon emissions globally, it is the need of the hour to transition to clean energy sources – such as wind, solar etc. However, renewable energy sources like wind turbines are complex engineering systems that regularly suffer from operational inconsistencies and failures, leading to downtimes and energy production short of the full potential. AI can help support the operations & maintenance (O&M) of such energy systems, helping predict incipient failures and also suggesting maintenance actions to fix/avert faults. This can help bring down O&M costs as well as reduce downtimes and increase availability of the energy systems.

At present, there is very limited focus on leveraging AI in the renewables domain. This social will aim to emphasise the opportunities (e.g. fault prediction, suggesting O&M activities, power forecasting etc.) and challenges (e.g. data confidentiality in the industry, lack of historical failure data etc.) in applying AI for smoother transition to clean energy, with various avenues such as transfer learning and natural language generation to ensure trustworthy and reliable decision support. The social will focus on a short presentation from the organisers, followed by a panel discussion from invited experts on AI for renewable energy followed by open Q/A on first day, and a fully informal/friendly socialising discussion on second day.

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