Soft open points (SOPs) are power electronic devices that are usually placed at normally
open points of electricity distribution networks to provide flexible power control to the …

With the growing integration of distributed energy resources (DERs), flexible loads, and
other emerging technologies, there are increasing complexities and uncertainties for …

With the increasing penetration of renewable energy and flexible loads in smart grids, a
more complicated power system with high uncertainty is gradually formed, which brings …

This paper presents a problem in power networks that creates an exciting and yet
challenging real-world scenario for application of multi-agent reinforcement learning …

With large-scale integration of renewable generation and distributed energy resources,
modern power systems are confronted with new operational challenges, such as growing …

This paper proposes a novel model-free/data-driven centralized training and decentralized
execution multi-agent deep reinforcement learning (MADRL) framework for distribution …

The high penetration of intermittent renewable energy resources in active distribution
networks (ADN) results in a great challenge for the conventional Volt-Var control (VVC). This …

In this paper, we propose a safe deep reinforcement learning (SDRL) based method to solve
the problem of optimal operation of distribution networks (OODN). We formulate OODN as a …

Active distribution networks are being challenged by frequent and rapid voltage violations
due to renewable energy integration. Conventional model-based voltage control methods …

Effective detection of fault in rolling bearings with a limited amount of data is essential for the
safe operation of electric machines. This article proposes a novel meta-learning-enabled …