Advancing Power System Services With Privacy-Preserving Federated Learning Techniques: A Review
Ran Zheng,
Andreas Sumper,
Monica Aragüés-Peñalba
et al.
Abstract:Digitalization has enabled the potential for artificial intelligence techniques to lead the power system to a sustainable transition by extracting the data generated by widely deployed edge devices, including advanced sensing and metering. Due to the increasing concerns about data privacy, federated learning has attracted much attention and is emerging as an innovative application for machine learning solutions in the power and energy sector. This paper presents a holistic analysis of federated learning applic… Show more
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