A Causal-Driven Hierarchical Decentralised Federated Learning Framework for Resilient Load Forecasting in Distributed Microgrids
Modern microgrids require distributed intelligence and edge computing to handle variable demand and renewable generation, but heterogeneity, communication limits, and privacy hinder centralised forecasting. This paper proposes a causally guided hierarchical decentralised federated learning (H-DFL) framework for resilie...