Clean energy transition 16

AI and Digitalization as Enablers of the Clean Energy Transition

Dr. Qianwen Xu, KTH Royal Institute of Technology, Sweden




   03:00 p.m  04:30 p.m
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Luxembourg Learning Centre
7, Ënnert den Héichiewen, 4361 Esch-sur-Alzette

Room: Ellipse


The urgent global shift towards clean energy systems presents a complex array of challenges, including integrating renewable sources, maintaining grid stability, and managing distributed energy resources efficiently. In this lecture, Prof. Xu will delve into the transformative potential of AI and digitalization in the clean energy sector. She will present an overview of the challenges in integrating renewable energy sources into existing grids from the AI’s perspective, including variability, demand management, and grid stability. Highlighting the role of advanced technologies and will explore how AI can optimize energy production and distribution, improving the efficiency and reliability of renewable energy systems. The lecture will cover key AI applications, including predictive analytics for forecasting energy demands, machine learning algorithms for grid optimization, and the deployment of digital twins to simulate and enhance the performance of renewable energy sources. Aimed at professionals and students interested in the nexus of technology and environmental sustainability, this lecture will offer a comprehensive insight into the current and future impact of digital technologies on facilitating a smoother transition to clean energy systems.

  1. Introduction to the Clean Energy Transition: Challenges and Opportunities
  2. The Role of AI in Integrating Renewable Energy Sources
  3. Machine Learning Algorithms for Grid Optimization and Stability
  4. Predictive Analytics for Energy Demand Forecasting and Management
  5. Digital Twins: Enhancing Renewable Energy System Performance


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