Modern power grids are fast evolving with the increasing volatile renewable generation,
distributed energy resources (DERs) and time-varying operating conditions. The DERs …

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 …

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 …

Microgrids (MG) have recently attracted great interest as an effective solution to the
challenging problem of distributed energy resources' management in distribution networks …

The widespread penetration of inverter-based resources has profoundly impacted the
electrical stability of power systems (PSs). Deepening grid integration of photovoltaic and …

Distribution systems are integrating a growing number of distributed energy resources and
converter-interfaced generators to form active distribution networks (ADNs). Numerous …

This article proposes a model-based deep reinforcement learning (DRL) method to design
emergency control strategies for short-term voltage stability problems in power systems …

The risk of transmission overload (TO) in power grids is increasing with the large-scale
integration of intermittent renewable energy sources. An effective online preventive control …

As power systems are undergoing a significant transformation with more uncertainties, less
inertia and closer to operation limits, there is increasing risk of large outages. Thus, there is …

This chapter gives a brief introduction to the history of deep learning and the associated
concepts. One step further, various deep learning applications in the area of power systems …