dc.creatorLopez, J
dc.date2018-01-11T16:47:06Z
dc.date2018-01-11T16:47:06Z
dc.date2017-05-01
dc.dateinfo:eu-repo/date/embargoEnd/2022-01-01 0:00
dc.date.accessioned2018-03-14T20:32:00Z
dc.date.available2018-03-14T20:32:00Z
dc.identifier8858950
dc.identifierhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85018773392&doi=10.1109%2fTPWRS.2016.2613544&partnerID=40&md5=787155b4a760f12d09358dc291d3a161
dc.identifierhttp://dspace.ucuenca.edu.ec/handle/123456789/29002
dc.identifier10.1109/TPWRS.2016.2613544
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1135904
dc.descriptionThis paper proposes a risk-based mixed integer quadratically-constrained programming model for the long-term VAr planning problem. Risk aversion is included in the proposed model by means of regret-based optimization to quantify the load shedding risk because of a reactive power deficit. The expected operation and expansion costs of new installed reactive power sources and load shedding risk are jointly minimized. Uncertainty in the active and reactive load demands has been included in the model. An ?-constraint approach is used to characterize the optimal efficient frontier. Also, discrete tap settings of tap-changing transformers are modeled as a set of mixed integer linear equations which are embedded into an ac optimal convex power flow. Computational results are obtained from a realistic South and South-East Brazilian power system to illustrate the proposed methodology. Finally, conclusions are duly drawn.
dc.languageen_US
dc.publisherINSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS INC.
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightshttp://creativecommons.org/licenses/by-nc-sa/3.0/ec/
dc.sourceinstname:Universidad de Cuenca
dc.sourcereponame:Repositorio Digital de la Universidad de Cuenca
dc.sourceIEEE Transactions on Power Systems
dc.subjectDiscrete tap settings
dc.subjectload shedding
dc.subjectmulti-objective
dc.subjectquadratically-constrained
dc.subjectregret optimization
dc.subjectrisk
dc.subjectuncertainties
dc.titleA Multiobjective Minimax Regret Robust VAr Planning Model
dc.typeArtículos de revistas


Este ítem pertenece a la siguiente institución