facilitating a smoother transition to Renewable Energy with AI


25th and 27th April 2022 (11 am - 1 pm GMT)

two-days of learning, fun and networking - with artificial intelligence and SUSTAINABILITY enthusiasts from across the world

To join our social as an attendee, you would need to be a registered participant at ICLR 2022 - see details here. Join us here - The entire event will be digital and take place on Zoom.

Background of the event

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. This 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 the first day (25th April, 11 am - 1 pm GMT). We would have a fully informal/friendly socialising session on challenges and opportunities in energy transition, along with an invited talk on the role of AI in climate change mitigation - on the second day (27th April, 11 am - 1 pm GMT). See full schedule of the event here.

the social will focus on building a stronger community that is passionate about applying ai for improved availability and reliability of renewable energy sources

key themes OF the social

  • The need of the hour in transitioning to low-carbon energy sources for realising the United Nations' SDGs - particularly SDG 7 (Affordable and Clean Energy).

  • The practical challenges faced by the renewable energy industry - high costs in operations & maintenance (O&M), unexpected failures and downtimes, varying availability and intermittent power production (e.g. during snow, low-wind speed etc.), energy storage costs, challenges in integration with the electric grid and so on.

  • How can AI help - from a sustainability perspective as well as an industrial perspective? The potential for digitalization to be a disruptive game-changer in the renewable energy domain - thus providing affordable and reliable energy to households and industries in global cities and communities.

  • Why do we not see much AI in the renewables domain? Challenges including data availability and quality, lack of transparency in black-box natured AI models (especially deep learners) and issues in deploying models for real-time decision support in the industry etc.

  • Potential for leveraging Explainable AI techniques and knowledge transfer mechanisms - what role can natural language generation, transfer learning, deep reinforcement learning techniques etc. play beyond current practices in using predictive AI models e.g. for power forecasting and fault prediction?

  • Ethical and moral concerns in applying AI in the renewables domain - widening of digital divide between the developing and developed world, environmental effect of training large-scale AI models etc.

  • What would be a viable roadmap to see more AI in the future in the renewables domain - role of industry, academia and governments to work hand-in-hand, large-scale sharing of open data, focus on Explainable AI, greater knowledge exchange between the developing and developed world etc.

eminent panellists

For more details about our invited panellists and their background and experience in sustainablity - please see here.

Dr. Natalia Efremova

Lecturer in digital economy, Queen Mary University of London and CTO at Deep Planet, UK


Clym Stock-Williams

Manager of Performance Analysis and Improvements at Vattenfall, Netherlands


Dr. Shruti Kulkarni

Senior Data Scienctiat Deloitte, Belgium


Alexandra Klang

Chairperson of the board, United Nations Association Malmö and Sustainability Consultant at Exceed, Sweden


Dr. Ravi Pandit

Lecturer (Assistant Professor) in Instrumentation and AI at Cranfield University, UK



For more details about our invited speakers, and their background and experience in sustainablity - please see here.

Marcus Voß

AI Expert and Intelligence Architect at Birds on Mars, Germany and Community Lead for Buildings & Transport at Climate Change AI



Dr. Joyjit Chatterjee

Data Scientist (KTP Associate) at Reckitt and University of Hull, UK

Email: j.chatterjee@hull.ac.uk


Dr. Nina Dethlefs

Senior Lecturer and Director of Research in Computer Science at University of Hull, UK

Email: n.dethlefs@hull.ac.uk


The foundation of this event will be based on our track-record in leveraging AI for O&M of renewable energy sources, particularly wind energy. We are applying AI and machine learning techniques to help solve problems in sustainability and environmental research. We are part of the EPSRC Aura CDT on Offshore Wind and the Environment, and work closely with the industry (ORE Catapult, Siemens Gamesa etc.), and we have a strong interest in the digitalisation of offshore wind. As part of this, we use AI to improve operations and maintenance of wind turbines to improve their reliability and usability as an alternative to fossil fuel-based energy sources. We achieve this through detailed and explainable fault forecasting and the automatic generation of maintenance strategies from expert knowledge sources. Our sustainability research has been published in leading journals and conferences/workshops, both in wind energy as well as AI.

Through the ICLR2022 socials platform, we hope to bring together people from across the globe to join us and socialise, make friends, develop collaborations and openly network amongst themselves and the invited experts from industry and academia. We envisage that this can help to accelerate the realisation of a smoother transition to renewables with AI.

We look forward to welcoming you at the event!