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dc.contributor.authorPloussard, Quentines-ES
dc.contributor.authorOlmos Camacho, Luises-ES
dc.contributor.authorRamos Galán, Andréses-ES
dc.date.accessioned2016-10-18T12:05:43Z
dc.date.available2016-10-18T12:05:43Z
dc.identifier.urihttp://hdl.handle.net/11531/14215
dc.description.abstractes-ES
dc.description.abstractThis article provides a novel technique to represent in a reduced, or compact, way short term uncertainty in Transmission Expansion Planning (TEP). Uncertainty reduction is handled by means of "snapshot selection". Instead of taking into account all the possible operational states and their associated optimal power flow, a reduced group of them is selected that is representative of all the states that should have an influence on investment decisions. Considering this reduced group of operational states should lead to the same investment decisions as if all the snapshots in the target year were considered. Original operational states are compared in the space of the benefits produced by potential reinforcements considered, which are relevant drivers for investment decisions. The benefits produced by these potential reinforcements are computed based on the incremental change in operation costs resulting from their installation. A clustering algorithm is used to group together those operational states where similar line benefits are realized. Our algorithm has been tested on a modified version of the standard IEEE 24 bus system. The method produces very promising results and proves to be more efficient than other snapshot selection methods used until now.en-GB
dc.format.mimetypeapplication/pdfes_ES
dc.language.isoen-GBes_ES
dc.rightses_ES
dc.rights.uries_ES
dc.titleA short term uncertainty reduction technique for transmission expansion planning based on line benefitses_ES
dc.typeinfo:eu-repo/semantics/workingPaperes_ES
dc.description.versioninfo:eu-repo/semantics/draftes_ES
dc.rights.accessRightsinfo:eu-repo/semantics/restrictedAccesses_ES
dc.keywordses-ES
dc.keywordsClustering, Dimension Reduction, Integer linear programming, Transmission Expansion Planning, Uncertaintyen-GB


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