S06 - Smart Renewable Energies: Advancing AI Algorithms in the Renewable Energy industry

• Dr. David Guijo-Rubio, University of Cordoba (Spain).
• Dr. Jorge Perez-Aracil, Universidad de Alcalá (Spain).
• Dr. Pedro A. Gutierrez, University of Cordoba (Spain).
• Dr. Sancho Salcedo- Sanz, University of Alcalá (Spain).

The field of Artificial Intelligence (AI) encompasses a wide range of modern techniques and algorithms that have proven to be highly effective in addressing complex tasks and improving learning optimization methods. Various industries have embraced AI techniques to solve practical problems, highlighting the technology's potential to automate processes across diverse sectors. In addition to the development of cleaner energy strategies, the Renewable Energy industry has gained significant importance due to the increasing digitalization of its operations and assets. Consequently, machine learning tasks such as classification, clustering, prediction, and complex optimization problems, have been applied to tackle emerging energy-related challenges.

In response to this increase, there has been a significant rise in research activity focused on AI-powered applications in the Renewable Energy industry in recent years. These applications encompass a wide range of areas, such as forecasting the quantity of resources, designing energy-efficient systems, implementing novel solutions in Smart Grids, and developing strategies to integrate renewable energy sources into traditional energy systems, among others.

This Special Session focusses on the application of AI-based methods to challenges associated with Renewable Energy, encompassing a wide spectrum of topics that include both novel algorithmic developments and groundbreaking applications with AI at their foundation. We invite submissions that either introduce new algorithms aimed at energy challenges or present established algorithms that offer effective solutions to complex, real-world renewable energy problems. Additionally, this session is open to works that explore alternative uses of AI in areas closely linked to Renewable Energy, such as issues pertaining to renewable energy sources (like wind, solar, and marine), the architecture of microgrids and smart grids (integrating both renewable and conventional generation), as well as Renewable Energy management and policymaking, if they leverage AI algorithms.

The topics of interest include, but are not limited to:

• AI techniques and algorithmic tools for Renewable Energy problems (Machine Learning, Deep Learning, Soft Computing, Heuristic Optimization, etc.).
• Approaches and uses of digital tools (e.g., digital twins) across various industrial domains.
• Renewable Energy consumption characterization and forecasting.
• Detection of non-technical losses in Renewable Energy distribution networks.
• Data collection, accessibility, integrity, and utilization to enhance digitalization, and its effect on improving energy efficiency and lowering greenhouse gas emissions in specific industries.
• Problems related to Renewable Energy (wind, solar, marine, etc.).
• Intelligent Grid Management: AI in Smart Grids and Microgrids.
• Renewable Energy efficiency in industrial systems and assets.
• Analysis of the impact of Climate change on renewable energy systems.
• Other applications that have a close connection with the Renewable Energy domain.