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The prioritization of restoration actions after large power system outages plays a key role in how quickly power can be restored. It has been shown that fast and intuitive heuristics for restoration prioritization most often result in…
Thunderstorm-driven power outages are difficult to predict because most storms do not cause damage, convective processes occur rapidly and chaotically, and the available public data are noisy and incomplete. Severe convective storms now…
In this study, we evaluate the effects of natural disasters on the stock (market) values of firms located in the affected counties. We are able to measure the change in stock prices of the firms affected by the 2021 Texas winter storm. To…
The estimation of resilience and the determination of inequality growth after a disaster is often difficult. In this study, specific indicators were developed to analyze resilience, and the trajectories of resilience were compared. Energy…
This research explores the potential to analyze bank card payments and ATM cash withdrawals in order to map and quantify how people are impacted by and recover from natural disasters. Our approach defines a disaster-affected community's…
Extreme temperature outages can lead to not just economic losses but also various non-energy impacts (NEI) due to significant degradation of indoor operating conditions caused by service disruptions. However, existing resilience assessment…
Real-time forecasting is important to the society. It uses continuous data streams to update forecasts for sustained accuracy. But the data source is vulnerable to attacks or accidents and the dynamics of forecasting failure and recovery…
Prediction of power outages caused by convective storms which are highly localised in space and time is of crucial importance to power grid operators. We propose a new machine learning approach to predict the damage caused by storms. This…
Climate change significantly increases risks to power systems, exacerbating issues such as aging infrastructure, evolving regulations, cybersecurity threats, and fluctuating demand. This paper focuses on the utilization of Grid Enhancing…
Due to the limitation of data availability, traditional power load forecasting methods focus more on studying the load variation pattern and the influence of only a few factors such as temperature and holidays, which fail to reveal the…
Recovery of society after a large scale disaster generally consists of two phases, short- and long-term recoveries. The main goal of the short-term recovery is to bounce the damaged system back to the operating standards enabling residents…
We describe some bulk statistics of historical initial line outages and the implications for forming contingency lists and understanding which initial outages are likely to lead to further cascading. We use historical outage data to…
Catastrophic failures have momentous impact in many scientific and technological fields but remain challenging to understand and predict. One key difficulty lies in the burstiness of rupture phenomena, which typically involve a series of…
The ability to measure and track the speed and trajectory of a community's post-disaster recovery is essential to inform resource allocation and prioritization. The current survey-based approaches to examining community recovery, however,…
During hurricane seasons, emergency managers and other decision makers need accurate and `on-time' information on potential storm surge impacts. Fully dynamical computer models, such as the ADCIRC tide, storm surge, and wind-wave model take…
Modeling power-grid systems has got a major importance in present days as transformation to renewable energy sources requires the complete re-design of energy transmission. Renewable energy sources can be located quite far from their…
Atlantic Canada faces significant hurricane threats from damaging winds and coastal flooding that are projected to intensify under climate change. This study adopts a two-stage framework. First, the evolution of wind and coastal-flood…
Space weather poses an important but under-quantified threat to critical infrastructure, the economy, and society. While extreme geomagnetic storms are recognized as potential global catastrophes, their socio-economic impacts remain poorly…
Knowledge of time-variant functionality of real-world physical, social, and engineered networks is critical to the understanding of the resilience of networks facing external perturbations. The majority of existing studies, however, focus…
The planning and operation of renewable energy, especially wind power, depend crucially on accurate, timely, and high-resolution weather information. Coarse-grid global numerical weather forecasts are typically downscaled to meet these…