Tuesday, October 20, 2009
Researchers say they can predict hurricane-related power outages
Johns Hopkins University: Using data from Hurricane Katrina and four other destructive storms, researchers from Johns Hopkins and Texas A&M universities say they have found a way to accurately predict power outages in advance of a hurricane. Their approach provides estimates of how many outages will occur across a region as a hurricane is approaching.
The information provided by their computer models has the potential to save utilities substantial amounts of money, savings that can then be passed on to customers, the researchers say. In addition, appropriate crew levels and placements can help facilitate rapid restoration of power after the storm.
The study was a collaborative effort involving 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. Their work, which was funded by a Gulf Coast utility company that wishes to remain anonymous, is published in the current issue of the journal Risk Analysis.
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. Having accurate estimates, prior to the storm’s arrival, of how many outages will exist and where they will occur will allow utilities to better plan their crew requests and crew locations, the researcher say.
What makes the research team’s computational approach unique and increases its accuracy, Guikema and Quiring say, is the combination of more detailed information about the storm, the area it is impacting and the power system of the area, together with more appropriate statistical models….
Boats shoved against the shore and damaged during Hurricane Ivan in downtown Pensacola, Florida, October, 2004. shot by Bill Koplitz of FEMA
The information provided by their computer models has the potential to save utilities substantial amounts of money, savings that can then be passed on to customers, the researchers say. In addition, appropriate crew levels and placements can help facilitate rapid restoration of power after the storm.
The study was a collaborative effort involving 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. Their work, which was funded by a Gulf Coast utility company that wishes to remain anonymous, is published in the current issue of the journal Risk Analysis.
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. Having accurate estimates, prior to the storm’s arrival, of how many outages will exist and where they will occur will allow utilities to better plan their crew requests and crew locations, the researcher say.
What makes the research team’s computational approach unique and increases its accuracy, Guikema and Quiring say, is the combination of more detailed information about the storm, the area it is impacting and the power system of the area, together with more appropriate statistical models….
Boats shoved against the shore and damaged during Hurricane Ivan in downtown Pensacola, Florida, October, 2004. shot by Bill Koplitz of FEMA
Subscribe to:
Post Comments (Atom)
No comments:
Post a Comment