Online Training Course on Machine Learning, Agent-based Systems, and Optimization in Power and Energy

Event date: 14:00 – 19:15 (WEST) Friday 3^rd July, 2020

This online training course is divided in two parts: Machine Learning and Agent-based Systems in Power and Energy, and Evolutionary Optimization Methods and Applications in Power and Energy. The first part will be presented by Professor Zita Vale (Full Professor at ISEP/P.Porto), Professor Carlos Ramos (Full Professor at ISEP/P.Porto), Dr. Tiago Pinto (Invited Professor at ISEP/P.Porto), and Dr. Pedro Faria (Invited Professor at ISEP/P.Porto) considering their work developed under MAS-Society project. The second part will be presented by Dr. João Soares, Dr. Pedro Faria (Invited Professor at ISEP/P.Porto), and Dr. Fernando Lezama, considering their work developed under CENERGETIC, and COLORS projects. This training course is online and free of charge. The participants who attend will receive certification.

Abstract

This training course covers machine learning, agent-based systems, and evolutionary optimization methods in power and energy systems.
In this context, in Part I, regards a general overview of machine learning methods and the application of multi-agent systems for simulation and emulation in power and energy. Then, Part I, demonstrates two particular cases using machine learning and multi-agent systems, considering electricity market negotiations, and energy management in a farm microgrid.
The Part II, of this training course, regards optimization techniques in the scope of smart grid paradigms. The optimization techniques consist of heuristic and metaheuristic approaches, including evolutionary algorithms. Then, it will be demonstrated a practical experimentation and case studies in smart grid optimizations.
In this training course, each part consists of case studies and practical experimentation as examples of applications of machine learning, agent-based systems, and optimization in power and energy systems.

Free but mandatory registration: here.

More details about the program can be found here.