We propose a storm damage model that utilizes a combination of weather parameters such as high winds and lightning to determine the strength of the incoming storm and ascertain the risk associated with it at various time horizons. We combine this information with non-weather data such as vegetation, utility asset records, and other variables to develop an application that predicts and visualizes the threat of a severe weather event as it comes through a service territory. Our model includes alerting as well as advanced predictive analytical capabilities to best assess the impact of the storm on the assets within its path.
Our advanced storm damage assessment application is based on a simple asset threat index application for utilities, using exclusive weather forecast data and the utility's own asset data. It uses advanced statistical modelling and predictive analytics to determine the impact of weather, the geographical location of the corresponding assets within the utility's service territory, and other variables.
The storm damage assessment model allows utilities to map all parts of their service territory impacted by forecasted severe weather so they can reduce costs and improve the speed of restoration to their customers. Furthermore, they can use this information to enhance communication with customers. This model can also help mitigate damage in the future by identifying key risk areas in a utility's service territory for hardening against future severe weather. It can be integrated into their operations and decision-support systems to help them derive maximum benefit from weather-based predictive solutions, which will have a positive impact on their performance in the long-term.
Turning weather forecasts into data a utility can take specific action on, such as asset damage management, has benefits in long term planning (hardening), short term planning (crew management), and ongoing operations workflows.