This paper focuses on a powerful and comprehensive overview of Deep Learning (DL)
techniques on Distribution Automation System (DAS) applications to provide a complete …

Distribution service restoration plays a vital role in mitigating the adverse impacts of power
outages stemming from extreme weather conditions. With incentives toward reducing the …

A new multiagent system (MAS) design for fault location, isolation, and restoration in power
distribution systems (PDSs) is presented. When there is a fault in the PDS, MAS quickly …

Although reinforcement learning (RL) is suitable for highly uncertain systems, the
applicability of this class of algorithms to medical treatment may be limited by the patient …

Self-healing capability is a critical factor for a resilient distribution system, which requires
intelligent agents to automatically perform service restoration online, including network …

Optimal power management of shipboard power system for failure mode (OPMSF) is a
significant and challenging problem considering the safety of system and person. Many …

To facilitate the integration of distributed energy resources and improve existing operational
strategies, power distribution systems have seen a rapid proliferation of deep reinforcement …

Energy and economy are increasing the relationship over the years, where the energy
becomes a significant resource to keep a country developing, and it supports its economy …

This paper addresses the load restoration problem after power outage events. Our primary
proposed methodology is using multi-agent deep reinforcement learning to optimize the …

This paper presents a novel distributed reconfiguration strategy to enable the secure and
reliable operation of the zonal shipboard power system (SPS). To adapt to the latest …