dc.creatorArruda, Elcio Franklin de
dc.creatorKagan, Nelson
dc.creatorRIBEIRO, Paulo F.
dc.date.accessioned2012-10-19T01:41:10Z
dc.date.accessioned2018-07-04T14:49:32Z
dc.date.available2012-10-19T01:41:10Z
dc.date.available2018-07-04T14:49:32Z
dc.date.created2012-10-19T01:41:10Z
dc.date.issued2010
dc.identifierIEEE TRANSACTIONS ON POWER DELIVERY, v.25, n.2, p.831-842, 2010
dc.identifier0885-8977
dc.identifierhttp://producao.usp.br/handle/BDPI/18165
dc.identifier10.1109/TPWRD.2009.2036922
dc.identifierhttp://dx.doi.org/10.1109/TPWRD.2009.2036922
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1614961
dc.description.abstractThis paper presents a new methodology to estimate harmonic distortions in a power system, based on measurements of a limited number of given sites. The algorithm utilizes evolutionary strategies (ES), a development branch of evolutionary algorithms. The main advantage in using such a technique relies upon its modeling facilities as well as its potential to solve fairly complex problems. The problem-solving algorithm herein proposed makes use of data from various power-quality (PQ) meters, which can either be synchronized by high technology global positioning system devices or by using information from a fundamental frequency load flow. This second approach makes the overall PQ monitoring system much less costly. The algorithm is applied to an IEEE test network, for which sensitivity analysis is performed to determine how the parameters of the ES can be selected so that the algorithm performs in an effective way. Case studies show fairly promising results and the robustness of the proposed method.
dc.languageeng
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.relationIeee Transactions on Power Delivery
dc.rightsCopyright IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.rightsrestrictedAccess
dc.subjectEvolutionary algorithms
dc.subjectevolutionary strategy
dc.subjectharmonic distortion
dc.subjectpower quality (PQ)
dc.subjectstate estimation
dc.titleHarmonic Distortion State Estimation Using an Evolutionary Strategy
dc.typeArtículos de revistas


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