Optimizing storage operations in transmission-constrained networks for medium-and long-term operation

dc.contributor.authorTejada Arango, Diego Alejandroes-ES
dc.contributor.authorWogrin, Sonjaes-ES
dc.contributor.authorCenteno Hernáez, Efraimes-ES
dc.date.accessioned2017-12-21T15:53:20Z
dc.date.available2017-12-21T15:53:20Z
dc.date.issued13/11/2016es_ES
dc.descriptionCapítulos en libroses_ES
dc.description.abstractes-ES
dc.description.abstractThe main objective is to present a new approach to model the storage operation in the context of Medium-and Long-term Operational Planning (MLTOP). This approach is based on the system-state framework but including transmission constraints. A DC power flow approach is used to represent the transmission network. The methodology is related to clustering techniques usin information such as demand and wind generation per node. Case studies are presented in order to compare the newly proposed methodology and the hourly approach. The results illustrate the computational time reduction without loss of accuracy in the solution.en-GB
dc.description.versioninfo:eu-repo/semantics/publishedVersiones_ES
dc.format.mimetypeapplication/pdfes_ES
dc.identifier.urihttp://hdl.handle.net/11531/24714
dc.keywordses-ES
dc.keywordsen-GB
dc.language.isoen-GBes_ES
dc.publisherInstitute for Operations Research and the Management Sciences (Nashville, Estados Unidos de América)es_ES
dc.rightses_ES
dc.rights.accessRightsinfo:eu-repo/semantics/restrictedAccesses_ES
dc.rights.uries_ES
dc.sourceLibro: INFORMS Anual Meeting - INFORMS 2016, Página inicial: , Página final:es_ES
dc.subject.otherInstituto de Investigación Tecnológica (IIT)es_ES
dc.titleOptimizing storage operations in transmission-constrained networks for medium-and long-term operationes_ES
dc.typeinfo:eu-repo/semantics/bookPartes_ES

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