The challenge

In the most extreme storm events, a utility’s storm response team is tasked with appropriately allocating resources in advance of the event to allow for provision and positioning of crews. And other utilities may request mutual aid to adequately address the resulting outages.

However, predicting the number of expected outages and the resources needed to restore power is extraordinarily difficult because of the complexity of weather forecasts and the interaction with vegetation and utility infrastructure.

The solution

E Source Storm Insight is a real-time, data-driven, outage-prediction system that uses a mechanistic approach to model when and where outages will occur. The modeling approach is comprehensive, collaborative, and configured specifically to the utility to build each of the fundamental mechanisms for outage risk into the data-driven model.

Rather than relying on weather forecasts alone, Storm Insight builds a model on data that incorporates the relative risk from vegetation, various infrastructure types and conditions, terrain, geography, and inspection history before integrating high-resolution numerical weather prediction model outputs. The model forecasts nonweather causes as well as weather events for a more accurate and reliable total outage prediction. This approach predicts expected daily system-wide outages up to five days before storm impact and hourly location-specific outages up to 24 hours before storm impact.

Storm Insight’s comprehensive approach delivers a more accurate prediction of expected outages, which enhances utilities’ ability to prepare for storms and make response decisions. Better preparation and storm response planning can improve reliability metrics, decrease costs associated with inaccurate allocation of resources, and improve customer satisfaction through faster restoration times. Even with the innate variability of the weather, Storm Insight provides location and impact predictions up to five days out with less variance and greater accuracy than current forecasting approaches.

The results

Using Storm Insight, a northeastern utility improved its outage prediction accuracy by 30% three days in advance of a storm. Armed with information from Storm Insight, the utility put the right levels of staffing in place, appropriately secure or deploy mutual aid, and implement a data-driven response plan. This accuracy prompted the utility’s leadership to deploy Storm Insight at its other operating companies to support storm readiness and operations at an enterprise level.

Effectively manage storm-related outages with Storm Insight