Leveraging Artificial Intelligence for Enhancing Power Grid Resilience to Extreme Weather Events: Applications and Challenges

The increasing frequency and magnitude of weather-related extreme events in recent years have severely impacted power grids. Examples of these extreme events include wildfires, heat waves, hurricanes, tornadoes, storms, flooding, etc. Extreme weather disturbances have rendered this critical infrastructure susceptible to disruption, risking essential services from health care to transportation. An important objective for many power utilities is to improve resilience and avoid widespread outages when faced with extreme events. The resilience goal of utility companies is to minimize the duration and magnitude of power outages and enable the rapid recovery of service after an outage event. For this purpose, various preventive and restorative resilience actions are required that can focus on adaptation plans as well as restoration plans that utilities can adopt to restore power to customers in an optimized fashion. However, one of the significant challenges that utilities face is to effectively handle large amounts of data from different sectors and utilize the data in an effective and optimized fashion for making resilience decisions and actions. This article discusses the data management practices required by electric power utilities to improve grid resilience and elaborates the applications of artificial intelligence (AI) for the enhanced resilience of electric power grids. The data management and AI applications are discussed from the perspective of preventive and mitigative actions on different power grid sectors, like generation, transmission, and distribution. The article concludes by summarizing the gaps in grid resilience research and technologies.