dc.date.accessioned2019-07-18T16:30:09Z
dc.date.accessioned2022-10-18T22:27:56Z
dc.date.available2019-07-18T16:30:09Z
dc.date.available2022-10-18T22:27:56Z
dc.date.created2019-07-18T16:30:09Z
dc.date.issued2018
dc.identifierhttp://hdl.handle.net/10533/236329
dc.identifier1150488
dc.identifierWOS:000440089900006
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/4467662
dc.description.abstractA model predictive power system stabilizer is proposed in this paper to damp power oscillations in an electric power system (EPS). The design of the stabilizer is optimal in the sense that its parameters are determined by using off-line particle swarm optimization (PSO) technique. The proposed methodology is applied to an EPS composed by a single machine connected to an infinite bus (SMIB). The analysis is performed through a small signal stability analysis, deriving incremental equations linearized around an operating point. The results obtained by the proposed method are compared with a conventional power system stabilizer, also optimized by PSO. Through numerous computer simulations under different operating conditions and perturbations on the SMIB, it was possible to establish some advantages of the proposed technique as compared with the conventional technique. Keywords. Author Keywords:Electrical and electronics power systems; Power system stabilizer (PSS); Predictive power system stabilizer (PPSS); Model predictive control (MPC); Particle swarm optimization (PSO); Simulation systems
dc.relationhttps://doi.org/10.4995/riai.2018.10056
dc.relation10.4995/riai.2018.10056
dc.relationinfo:eu-repo/grantAgreement//1150488
dc.relationinfo:eu-repo/semantics/dataset/hdl.handle.net/10533/93477
dc.relationinstname: Conicyt
dc.relationreponame: Repositorio Digital RI2.0
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/3.0/cl/
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Chile
dc.titlePower System Stabilizer based on Model Predictive Control
dc.typeArticulo


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