Generalized Policy Learning for Smart Grids: FL TRPO Approach

arXiv:2403.18439v1 Announce Type: new
Abstract: The smart grid domain requires bolstering the capabilities of existing energy management systems; Federated Learning (FL) aligns with this goal as it demonstrates a remarkable ability to train models on heterogeneous datasets while maintaining data privacy, making it suitable for smart grid applications, which often involve disparate data distributions and interdependencies among features that hinder the suitability of linear models. This paper introduces a framework that combines FL with a Trust Region Policy Optimization (FL …

abstract applications arxiv capabilities cs.lg data data privacy datasets domain energy energy management federated learning generalized grid making management policy privacy smart systems train type