AN APPLICATION OF THE HIGHLY OPTIMIZED TOLERANCE MODEL TO ELECTRICAL BLACKOUTS

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Abstract
The recently proposed Highly Optimized Tolerance (H.O.T.) model [Carlson & Doyle, 1999, 2000], which aims to describe the statistics of robust complex systems in uncertain environments, is compared with data from the Western United States (W.S.C.C.) power distribution system. We use for comparison a 15-year record of all power outages occurring on the grid, measured in the size of megawatts lost and the number of customers without service. In applying the model to the power grid data, we find that the problem of determining how the resources in the system scale with event size is nontrivial given the assumptions of the model and the information about how the power grid actually operates. Further, we observe that the model agrees closely with the W.S.C.C. data for the megawatts but not the customers, and consequently propose that the assumption in the model of optimal resource distribution is not valid in general when more than one measure of event size is used. A modified H.O.T. model which allows for resource misallocation is introduced and we find that this model can be made to fit both data sets reasonably well.

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