A Review of Federated Learning in Energy Systems. (arXiv:2208.10941v1 [cs.CR])

With increasing concerns for data privacy and ownership, recent years have
witnessed a paradigm shift in machine learning (ML). An emerging paradigm,
federated learning (FL), has gained great attention and has become a novel
design for machine learning implementations. FL enables the ML model training
at data silos under the coordination of a central server, eliminating
communication overhead and without sharing raw data. In this paper, we conduct
a review of the FL paradigm and, in particular, compare the types, …

energy federated learning review systems