Diego Cerrai, assistant professor of civil and environmental engineering and interim director of the Eversource Energy Center (EEC), has received a National Science Foundation (NSF) Faculty Early Career Development Program grant (CAREER) Award. 

This award will support Cerrai’s research aimed at deepening our understanding of snow and ice accretion on infrastructure. This understanding, in turn, enables the development of models capable of forecasting its occurrence, and accurately predicting power outages and their restoration during winter storms  

Over the past four years, Cerrai has been collaborating with NASA to gather data on winter precipitation. Specifically, measuring the amount and density of falling snow and the number of particles of rain or snow present in a given volume.  

At the same time, Cerrai’s research team was running simulations using weather and storm impact models, looking at where they diverged from these observations. That’s where challenges started to emerge – existing observations only include measurements of density of snow on the ground, not of falling snow. But snow on the ground gets compacted over time, meaning measurements right after a storm can be very different from later measurements.  

“The first step is to fix those inconsistencies and biases and make sure that the quantities that the weather model predict match the observation we collect,” Cerrai says.  

After improving the characterization of snow density in weather models, through this CAREER Award, Cerrai will use this more refined information to model snow and ice accretion on power infrastructure.  

“The goal here is to predict snow and ice accretion on power lines, because those are very correlated to power outages,” Cerrai says.   

This will, in turn, enable the development of a more accurate outage prediction model. 

“The UConn Outage Prediction Model (OPM) still exhibits significant errors in advance of some specific winter storms,” Cerrai says. “This may hinder proper preparation from utility companies. An under allocation of crews and resources may result in delays in power outage restoration.” 

Eversource Energy, Dominion Energy, Avangrid, and Exelon have already used the UConn OPM.  

Cerrai says the CAREER Award will help him improve the accuracy of the model and expand its application to more utility companies.  

In tandem with improving the accuracy of the OPM, Cerrai has been developing a restoration model. This model will use data on snow density and other precipitation measurements alongside OPM forecasts and restoration priorities dictated by the power companies to estimate the time to power outage restoration.  

One of the key challenges restoration models face currently is that they do not account for road conditions, which have a big impact on how quickly crews can move.  

“Right now, we use the speed limit to predict how fast the crews move,” Cerrai says. “But in winter, you can have blocked roads, and you can have snow on the roads. So, for accurate forecasts it is absolutely necessary to model the road conditions.”  

One goal of the model is to reduce disparities between how long customers in rural areas versus towns wait for their power to be restored.  

“We will look at if we can change or suggest new prioritization strategies to make sure that customers in towns and customers in rural areas will not experience big differences in restoration,” Cerrai says. 

Another segment of this grant will enable the development of a course where Cerrai will train decision-makers and utility company employees on how to use storm impact and restoration models.  

“I will teach this course to make sure these new tools will be passed to the utilities, and to make sure they will have the most recent information in terms of technology that is available out there,” Cerrai says.