Active Distribution

Active distribution systems, characterized by high penetration of distributed energy resources and smart devices, are the focus of intense research aimed at optimizing their operation and enhancing resilience. Current efforts leverage deep reinforcement learning (DRL), often employing actor-critic architectures and techniques like quantile regression, to manage voltage and reactive power, optimize energy storage system dispatch, and improve overall network efficiency. These advancements address challenges like limited observability and computational burden, ultimately aiming to improve grid stability, reliability, and the integration of renewable energy sources.