Design and Planning of Flexible Mobile Micro-Grids Using Deep Reinforcement Learning

no code implementations • 8 Dec 2022 • Cesare Caputo, Michel-Alexandre Cardin, Pudong Ge, Fei Teng, Anna Korre, Ehecatl Antonio del Rio Chanona

The results on a case study for ger communities in Mongolia suggest that mobile nomadic energy systems can be both technically and economically feasible, particularly when considering flexibility, although the degree of spatial dispersion among households is an important limiting factor.

reinforcement-learning Reinforcement Learning (RL)

A Wireless-Assisted Hierarchical Framework to Accommodate Mobile Energy Resources

no code implementations • 19 Sep 2022 • Pudong Ge, Cesare Caputo, Michel-Alexandre Cardin, Anna Korre, Fei Teng

The societal decarbonisation fosters the installation of massive renewable inverter-based resources (IBRs) in replacing fossil fuel based traditional energy supply.