Award Winnerʼs Article: Machine Learning based and Multi-Agent System based Control and Optimization Approaches for Electric Vehicles, Power Grids, and their Interactions

*Kyushu University

Paradigm shifts on energy generation, consumption, storage, and trading, due to the deep penetration of renewable and distributed energy resources, e.g., solar, electric vehicles, etc., pose significant challenges to the operation and management of current and future energy systems. A solution proposed in this research is a unified framework based on multi-agent system and machine learning for the optimization, control, and prediction of energy networks at different levels to cope with uncertainties and random perturbations. Thus, the stability, robustness, and resiliency of energy systems are enhanced in addition to their autonomy.