Sensing Cloud Optimization to Solve ED of Units with Valve-Point Effects and Multi-fuels

dc.contributor.author Fonte,P en
dc.contributor.author Cláudio Monteiro en
dc.contributor.author Fernando Maciel Barbosa en
dc.date.accessioned 2017-12-14T16:52:19Z
dc.date.available 2017-12-14T16:52:19Z
dc.date.issued 2013 en
dc.description.abstract In this paper a solution to an highly constrained and non-convex economical dispatch (ED) problem with a meta-heuristic technique named Sensing Cloud Optimization (SCO) is presented. The proposed meta-heuristic is based on a cloud of particles whose central point represents the objective function value and the remaining particles act as sensors "to fill" the search space and "guide" the central particle so it moves into the best direction. To demonstrate its performance, a case study with multi-fuel units and valve- point effects is presented. en
dc.identifier.uri http://repositorio.inesctec.pt/handle/123456789/4113
dc.language eng en
dc.relation 4911 en
dc.rights info:eu-repo/semantics/openAccess en
dc.title Sensing Cloud Optimization to Solve ED of Units with Valve-Point Effects and Multi-fuels en
dc.type conferenceObject en
dc.type Publication en
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