Last month, as Hurricane Isaac drenched Louisiana, nearly half of the state's homes—more than 900,000 customers—lost power. In late June, a line of severe storms moved across the Upper Midwest and Mid-Atlantic regions, leaving nearly 4 million power customers without electricity. In many cases, electricity wasn't restored for days.
But what if utility companies had been able to more accurately predict the potential impact of those storms on their customers? What if they knew in advance how many people would lose power, and where? Seth Guikema, a Johns Hopkins School of Engineering researcher who specializes in risk assessment and risk management, wants to give utilities the tools to answer those complex questions. He is working to develop a data model that uses weather forecasts, U.S. Census records, and other variables to estimate power outages.
More on Guikema's work, from an article on The Baltimore Sun's Maryland Weather blog:
Read more from The Baltimore Sun
"We have this model we can run for any hurricane that's going to impact us from Texas up through Maine," Guikema said.
The idea is the researchers can work with any utility or emergency response agency along that stretch of coast to help them better prepare for storm-related outages, he said.