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Vehicle routing for the last mile of power system restoration [electronic resource].

Published:
Washington, D.C. : United States. Dept. of Energy, 2010.
Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy.
Additional Creators:
Los Alamos National Laboratory, United States. Department of Energy, and United States. Department of Energy. Office of Scientific and Technical Information
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Summary:
This paper studied a novel problem in power system restoration: the Power Restoration Vehicle Routing Problem (PRVRP). The goal of PRVRPs is to decide how coordinate repair crews effectively in order to recover from blackouts as fast as possible after a disaster has occurred. PRVRPs are complex problems that combine vehicle routing and power restoration scheduling problems. The paper proposed a multi-stage optimization algorithm based on the idea of constraint injection that meets the aggressive runtime constraints necessary for disaster recovery. The algorithms were validated on benchmarks produced by the Los Alamos National Laboratory, using the infrastructure of the United States. The disaster scenarios were generated by state-of-the-art hurricane simulation tools similar to those used by the National Hurricane Center. Experimental results show that the constraint-injection algorithms can reduce the blackouts by 50% or more over field practices. Moreover, the results show that the constraint-injection algorithm using large neighborhood search over a blackbox simulator provide competitive quality and scales better than using a MIP solver on the subproblems.
Report Numbers:
E 1.99:la-ur-10-07867
E 1.99: la-ur-10-7867
la-ur-10-7867
la-ur-10-07867
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Note:
Published through SciTech Connect.
11/23/2010.
"la-ur-10-07867"
" la-ur-10-7867"
Power Systems Computation Conference ; August 22, 2011 ; Stockholm, Sweden.
Bent, Russell W; Van Hentenryck, Pascal; Coffrin, Carleton.
Funding Information:
AC52-06NA25396
View MARC record | catkey: 14756840