A review of federated learning in renewable energy applications: Potential, challenges, and future directions

Federated learning has recently emerged as a privacy-preserving distributed machine learning approach. Federated learning enables collaborative training of multiple clients and entire fleets without sharing the involved training datasets. By preserving data privacy, federated learning has the potential to overcome the lack of data sharing in...

Future emerging technologies in the wind power sector: A European perspective

This paper represents an expert view from Europe of future emerging technologies within the wind energy sector considering their potential, challenges, applications and technology readiness and how they might evolve in the coming years. These technologies were identified as originating primarily from the academic sector, some start-up...