University Researchers Pinpoint Expected Hurricane-Related Power Outages
- By Dian Schaffhauser
Researchers from Johns Hopkins University and Texas A&M University have developed a computer model for predicting power outages in advance of a hurricane, based on analysis they've done from Hurricane Katrina and four other storms. The model provides estimates of how many outages will occur across a region as a hurricane is approaching.
The information provided by the model will enable utilities to manage crew levels for doing repairs to restore power after the storm.
The collaboration involved Seth Guikema, an assistant professor of geography and environmental engineering at Johns Hopkins and formerly of Texas A&M; Steven Quiring, an assistant professor of geography at Texas A&M; and Seung-Ryong Han, who was Guikema's doctoral student at Texas A&M and is now based at Korea University. The research, funded by a Gulf Coast utility company that wishes to remain anonymous, is published in the current issue of the journal Risk Analysis.
In developing the model, the researchers looked at damage data from five hurricanes: 1995's Dennis, which generated 4,800 power outages; 1997's Danny, with 620 outages; 1998's Georges, with 1,075 outages; 2004's Ivan, with 13,500 outages; and 2005's Katrina, with more than 10,000 outages.
According to a statement describing the work, the research focused on two common challenges. When a hurricane is approaching, an electric power provider must decide how many repair crews to request from other utilities, a decision that may cost the provider millions of dollars. The utility also must decide where to locate these crews within its service areas to enable fast and efficient restoration of service after the hurricane ends. The researchers say that having accurate estimates prior to the storm's arrival of how many outages will exist and where they'll occur will allow utilities to better plan their crew requests and crew locations.
"If the power company overestimates, it has spent a lot of unnecessary money," Quiring said. "If it underestimates, the time needed to restore power can take several extra days or longer, which is unacceptable to them and the people they serve. So these companies need the best estimates possible, and we think this study can help them make the best possible informed decision."
More accurate models "provide a much better basis for preparing for restoring power after the storm," Guikema said, "The goal is to restore power faster and save customers money."
Dian Schaffhauser is a writer who covers technology and business for a number of publications. Contact her at firstname.lastname@example.org.