A fast and reliable sequential service restoration (SSR) methodology is necessary to
enhance the resilience of the distribution system (DS) after an outage. However, traditional …

Threats against power grids continue to increase, as extreme weather conditions and
natural disasters (extreme events) become more frequent. Hence, there is a need for the …

In this study, a machine learning based method is proposed for creating synthetic eventful
phasor measurement unit (PMU) data under time-varying load conditions. The proposed …

Ice storms have a wide range of impacts on power systems ranging from long outage times
to major equipment failures. The diverse spatiotemporal characteristics of ice storms create …

Traditional power grid systems have become obsolete under more frequent and extreme
natural disasters. Reinforcement learning (RL) has been a promising solution for resilience …

One of the most critical challenges for modern power systems is to reliably supply electricity
to its consumers during and in the aftermath of natural disasters. As our dependence on …

This study presents the design of an electric vehicle (EV)-grid integration hardware test-bed
to implement smart EV charging algorithms. The proposed test-bed allows for creating …

Over the last decades, great efforts and investments have been made to increase the
integration level of renewable energy resources in power grids. The New York State has set …

Natural disaster events are increasing around the globe in frequency, duration, and severity,
thanks to the changing climate. Such incidents, eg, severe weather events such as …

We deliver the first analysis of the 2021 cold spell in Texas which combines temperature
dependent load estimates with temperature dependent estimates of power plant outages to …