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Dynamic active and reactive power compensation in distribution networks with batteries: A day-ahead economic dispatch approach

dc.contributor.authorMontoya, Oscar Danilo
dc.contributor.authorGil-González, Walter
dc.date.accessioned2020-10-30T15:04:43Z
dc.date.available2020-10-30T15:04:43Z
dc.date.issued2020-06-08
dc.date.submitted2020-10-28
dc.identifier.citationMontoya, O. and Gil-González, W., 2020. Dynamic active and reactive power compensation in distribution networks with batteries: A day-ahead economic dispatch approach. Computers & Electrical Engineering, 85, p.106710.spa
dc.identifier.issn0045-7906
dc.identifier.urihttps://hdl.handle.net/20.500.12585/9506
dc.description.abstractThis paper focuses on the problems of optimal operation of battery energy storage systems (BESSs) in distributed networks from a nonlinear programming (NLP) point of view. This proposal contains the active and reactive power capabilities of the voltage source converters that interface with the BESS independently, which implies that the BESSs have the possibility to work as dynamic energy compensators over all the four quadrants. Two radial distribution networks have been used to validate the proposed NLP model. This model has been arrived at by using the general algebraic modeling system (GAMS) optimization package. Artificial neural networks (ANN) are also employed for short-term forecasting of renewable generation based on wind and photo-voltaic sources. Numerical results show that the inclusion of reactive power capabilities of batteries reduces the daily operational cost of the network as compared to the classical unity power factor operation approach. All the simulations are made considering Colombian utility typical curves.spa
dc.format.mimetypeapplication/pdfspa
dc.language.isoengspa
dc.sourceComputers & Electrical Engineering; vo. 85 (2020)spa
dc.titleDynamic active and reactive power compensation in distribution networks with batteries: A day-ahead economic dispatch approachspa
datacite.rightshttp://purl.org/coar/access_right/c_14cbspa
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85spa
dc.identifier.urlhttps://www.sciencedirect.com/science/article/abs/pii/S0045790620305656
dc.type.driverinfo:eu-repo/semantics/articlespa
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersionspa
dc.identifier.doi10.1016/j.compeleceng.2020.106710
dc.subject.keywordsBattery energy storage systemspa
dc.subject.keywordsDistribution networksspa
dc.subject.keywordsDynamic active and reactive power compensationspa
dc.subject.keywordsNonlinear programming modelspa
dc.subject.keywordsDay-ahead economic dispatchspa
dc.rights.accessRightsinfo:eu-repo/semantics/closedAccessspa
dc.identifier.instnameUniversidad Tecnológica de Bolívarspa
dc.identifier.reponameRepositorio Universidad Tecnológica de Bolívarspa
dc.publisher.placeCartagena de Indiasspa
dc.type.spaArtículospa
dc.audiencePúblico generalspa
dc.publisher.sedeCampus Tecnológicospa
oaire.resourcetypehttp://purl.org/coar/resource_type/c_2df8fbb1spa
dc.publisher.disciplineIngeniería Eléctricaspa


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