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dc.contributor.authorFitiwi Zahlay, Destaes-ES
dc.contributor.authorCuadra García, Fernandoes-ES
dc.contributor.authorOlmos Camacho, Luises-ES
dc.contributor.authorRivier Abbad, Michel Luises-ES
dc.contributor.authorPérez Arriaga, José Ignacioes-ES
dc.date.accessioned2016-01-15T11:26:24Z
dc.date.available2016-01-15T11:26:24Z
dc.date.issued2013-05-27es_ES
dc.identifier.urihttp://hdl.handle.net/11531/5507
dc.descriptionCapítulos en libroses_ES
dc.description.abstractes-ES
dc.description.abstractThe expected deployment of massive renewable energy sources (RES, mainly of wind and solar) at a continental or even intercontinental level creates very complex transmission expansion planning (TEP) problems. Both the size of the system and the level of uncertainty are huge. Solving a TEP problem for such big networks under high levels of uncertainty demands an exceptionally huge computational effort when using reasonably precise models. Conventional modeling approaches and solution strategies cannot be directly reproduced in this case due to their computational limitations. In this paper, we show a systematic way of approaching the problem, which deals both with modeling and with solution strategy aspects. We formulate the TEP problem as a two period stochastic linear programming problem characterized by common investment decisions to all scenarios in the first period and scenario-dependent decisions in the second period. In order to make it tractable, we devise a solution strategy based on decomposing the problem into successive optimization phases. Each phase uses the results of the previous one to reduce the search space. This reduction in complexity allows each phase to use more complex models with a similar computational load. Each optimization phase could be defined and solved as an independent problem, thus, allowing the use of specific decomposition techniques, or parallel computation when possible. A modified Garver’s system is used to illustrate the methodologies. Test results from IEEE-300 bus system show that the proposed solution strategy is very effective. And, integrating the proposed solution strategy in the solution process contributes to a significant reduction in computational effort while fairly maintaining optimality of the solution.en-GB
dc.format.mimetypeapplication/pdfes_ES
dc.language.isoen-GBes_ES
dc.publisherIEEE Pes (Estocolmo, Suecia)es_ES
dc.rightses_ES
dc.rights.uries_ES
dc.sourceLibro: IEEE 10th International conference on the european energy market - EEM2013, Página inicial: , Página final:es_ES
dc.subject.otherInstituto de Investigación Tecnológica (IIT)es_ES
dc.titleA formulation for large-scale transmission expansion planning problem and a solution strategyes_ES
dc.typeinfo:eu-repo/semantics/bookPartes_ES
dc.description.versioninfo:eu-repo/semantics/publishedVersiones_ES
dc.rights.accessRightsinfo:eu-repo/semantics/restrictedAccesses_ES
dc.keywordses-ES
dc.keywordsTransmission expansion planning, stochastic programming, renewable energy sources, solution strategyen-GB


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