A new white paper, “Unlocking AI’s Potential for the Energy Transition Through Open Source“, from LF Energy explores. the state of AI readiness in the energy industry, use cases for AI within energy systems, initiatives to increase AI adoption for energy, and the impact and promise of open source for accelerating this work.
As the global energy sector undergoes a critical transformation driven by decarbonization, digitalization, and decentralization, artificial intelligence (AI) has emerged as a key enabler for optimizing energy systems. This paper demonstrates how open source innovation is essential to accelerate AI adoption in the energy industry and deliver on its promises.
Central to the findings are that energy stakeholders must adopt a strategic approach to AI readiness by:
- Establishing robust data governance to enable AI innovation and deployment
- Investing in digital twins and data platforms based on open source shared components to support AI initiatives
- Supporting open, realistic datasets to fuel AI model development with third-party innovators and researchers
- Promoting AI literacy in the organization and workforce to help power systems make the most of AI tools and technologies and support AI experts in navigating and understanding energy-specific knowledge and challenges
The paper was compiled by LF Energy Director of Ecosystem, AI & Energy Systems Alexandre Parisot, with contributions from Lucian Balea (RTE), Gus Chadney (Centre for Net Zero), Sheng Chai (Centre for Net Zero), Boris Dolley (RTE), Virginie Dordonnat (RTE), Abder Elandaloussi (Southern California Edison), Mital Kanabar (GE), David Lamers (Alliander), Vincent Lefieux (RTE), Francois Miralles (Hydro-Quebec), Camille Pache (RTE), and Pedro Vergara Barrios (TU Delft).
