Deep Reinforcement Learning in a Multi-Agent System for Defining Electric Vehicle Load Management Actions

The DemIA Chair, in collaboration with the PhD programme in Artificial Intelligence at the University of Salamanca, has organised a seminar entitled ‘Deep Reinforcement Learning in a Multi-Agent System for Defining Electric Vehicle Load Management Actions’.

A unique opportunity to explore how AI is transforming energy management and electric mobility. This seminar delves into one of the cutting-edge areas of current research, combining deep reinforcement learning, multi-agent systems and real-time optimisation. It is particularly recommended for those working in or with an interest in AI, distributed systems or the energy transition.

The session will be led by Carlos Ernani da Veiga, M.Eng., a lecturer in the Department of Electrical Engineering at the Federal Institute of Santa Catarina (IFSC), a researcher with extensive experience in intelligent systems applied to power grids and energy optimisation.

During the seminar, an innovative approach based on deep reinforcement learning will be presented for managing electric vehicle charging in multi-user environments, integrating the individual characteristics of each user to make optimal decisions in real time.