AI in Energy Systems
AI in Energy Systems
Artificial intelligence in energy systems enables intelligent decision-making, automation, and optimization across the energy value chain. AI applications include load forecasting, fault detection, predictive maintenance, and energy trading optimization. Machine learning algorithms analyze large datasets to improve system performance and reliability. AI supports renewable energy forecasting, grid stability, and demand response. By enhancing efficiency and reducing operational costs, AI accelerates the transition to smart and sustainable energy systems. Its role is increasingly critical in managing complex, data-driven energy networks.
Committee Members
Dai Yeun Jeong
Asia Climate Change Education Center, Korea, Republic of
Scott Kelly
University of Cambridge, United Kingdom
Deinar Agudelo Ortiz
Natural Motos sas, Colombia IEFC 2026 Speakers
Ricson Chude
Association of Energy Engineers, United States
Saim Memon
Sanyou London Pvt Ltd, United Kingdom
Sabine Rode
University of Lorraine, France
Vladimir Chigrinov
Hong Kong University of Science and Technology, Hong KongSubmit your abstract Today
Title : The autonomy curve: The impact of ai on energy systems
Scott Kelly, University of Cambridge, United Kingdom
Title : Energy performance of world’s first vacuum insulated heatable curtain for realistic energy-loss reduction with mild radiant heating
Saim Memon, Sanyou London Pvt Ltd, United Kingdom
Title : Transforming waste plastic into renewable hydrogen: A review of progress, challenges, and future directions through pyrolysis, distillation, and hydrotreatment process
Nur Hassan, Central Queensland University, Australia
Title : Why should nature be conserved
Dai Yeun Jeong, Asia Climate Change Education Center, Korea, Republic of
Title : Inclusive energy transition through productive small-scale mobility: Natural gas and LPG solutions for two- and three-wheel transport
Deinar Agudelo Ortiz, Natural Motos sas, Colombia
Title : Micro grid of power electronics, renewable energy storage, and collaboration opportunities
Mustafa Ergin Sahin, RTE University, Turkey