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

Continuously expanding deployments of distributed power-generation systems (DPGSs) are
transforming the conventional centralized power grid into a mixed distributed electrical …

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

This paper proposes attention enabled multi-agent deep reinforcement learning (MADRL)
framework for active distribution network decentralized Volt-VAR control. Using the …

With the massive deployment of microgrids (MGs) and energy communities, various
stakeholders have been involved in distribution networks. Due to the underdeveloped …

Distribution systems are growing rapidly in size and complexity with increased penetrations
of distributed energy resources (DER) and electric vehicles (EVs), leading to operational …

In order to solve the voltage violation problem caused by high penetration of photovoltaic
(PV) units in distribution power networks, this paper proposes a double-layer voltage control …

This paper provides a survey of studying complex network theory for modern smart grid
applications. A brief overview of complex network theory will be explored first. Topological …

Environmental and sustainability concerns have caused a recent surge in the penetration of
distributed energy resources into the power grid. This may lead to voltage violations in the …

This paper investigates the situation awareness issue of power system with massive
measured data. To address this issue, first, a graph-theory-based network partitioning …