dc.creatorSanches, Danilo Sipoli
dc.creatorJunior, Joao Bosco Augusto London
dc.creatorDelbem, Alexandre Cláudio Botazzo
dc.date.accessioned2014-04-22T19:10:52Z
dc.date.accessioned2018-07-04T16:45:16Z
dc.date.available2014-04-22T19:10:52Z
dc.date.available2018-07-04T16:45:16Z
dc.date.created2014-04-22T19:10:52Z
dc.date.issued2014-05
dc.identifierElectric Power Systems Research, Amsterdam, v. 110, p. 144-153, May 2014
dc.identifierhttp://www.producao.usp.br/handle/BDPI/44571
dc.identifier10.1016/j.epsr.2014.01.017
dc.identifierhttp://www.sciencedirect.com/science/article/pii/S0378779614000212#
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1639906
dc.description.abstractNetwork reconfiguration for service restoration (SR) in distribution systems is a complex optimization problem. For large-scale distribution systems, it is computationally hard to find adequate SR plans in real time since the problem is combinatorial and non-linear, involving several constraints and objectives. Two Multi-Objective Evolutionary Algorithms that use Node-Depth Encoding (NDE) have proved able to efficiently generate adequate SR plans for large distribution systems: (i) one of them is the hybridization of the Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) with NDE, named NSGA-N; (ii) the other is a Multi-Objective Evolutionary Algorithm based on subpopulation tables that uses NDE, named MEAN. Further challenges are faced now, i.e. the design of SR plans for larger systems as good as those for relatively smaller ones and for multiple faults as good as those for one fault (single fault). In order to tackle both challenges, this paper proposes a method that results from the combination of NSGA-N, MEAN and a new heuristic. Such a heuristic focuses on the application of NDE operators to alarming network zones according to technical constraints. The method generates similar quality SR plans in distribution systems of significantly different sizes (from 3860 to 30,880 buses). Moreover, the number of switching operations required to implement the SR plans generated by the proposed method increases in a moderate way with the number of faults.
dc.languageeng
dc.publisherElsevier
dc.publisherAmsterdam
dc.relationElectric Power Systems Research
dc.rightsCopyright Elsevier
dc.rightsrestrictedAccess
dc.subjectLarge-scale distribution system
dc.subjectService restoration
dc.subjectMultiple faults
dc.subjectNode-Depth Encoding
dc.subjectMulti-Objective Evolutionary Algorithms
dc.titleMulti-objective evolutionary algorithm for single and multiple fault service restoration in large-scale distribution systems
dc.typeArtículos de revistas


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