Hurricane Sandy – 8 to 10 Million Cumulative Power Outages Predicted

Released: 10/30/2012 12:15 PM EDT
Source Newsroom: Johns Hopkins University
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MEDIA ADVISORY: Hurricane Sandy – 8 to 10 million cumulative power outages predicted
An engineer at The Johns Hopkins University is predicting power outages for 8 to 10 million people in the aftermath of Hurricane Sandy.

Please note: A multicolored map of power outage predictions is available. Email acl@jhu.edu.

Newswise — Hurricane Sandy is weakening and moving faster than anticipated. Therefore a computer model developed by an engineer at The Johns Hopkins University is now predicting fewer power outages than initially expected. Seth Guikema is predicting that an overall cumulative total of 8 to 10 million people will lose power in the wake of the hurricane, based on the last storm track and intensity forecast at 2 a.m. EDT on Tuesday, Oct. 30.

It is important to note that the computer model predicts cumulative outages, not peak outages. Cumulative means the total count of anyone who has lost power, versus peak, which is the number of people without power at any one point in time. For instance, in Maryland, the local utility company reported approximately 290,000 cumulative power outages as of 10:30 a.m. on Monday, Oct. 29, but their peak was approximately 210,000 because they were actively restoring outages while new outages were occurring.

Guikema (pronounced Guy-keh-ma) has been tracking Hurricane Sandy since late last week using his computer model, which in the early days of the storm used outage data from 11 hurricanes to estimate the fraction of customers who will lose power, based on expected gust wind speed, expected duration of strong winds greater than 20 meters per second, and population density. As the storm progressed, the model incorporated the actual track of the storm as well as the forecast. The predicted number of outages fluctuated throughout the storm based on the available forecast data.

Guikema’s model may help power companies allocate resources by predicting how many people will be without power and where the most outages will take place, and it provides information that emergency managers can use to better prepare for storms. Guikema, an assistant professor in the Department of Geography and Environmental Engineering at the Johns Hopkins Whiting School of Engineering, says the goal is to restore power faster and save customers money.

To speak to with Guikema contact Amy Lunday at 410-804-2551 or acl@jhu.edu.

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