dc.contributor | Universidade Federal de Mato Grosso do Sul (UFMS) | |
dc.contributor | Universidade Estadual Paulista (Unesp) | |
dc.date.accessioned | 2014-05-27T11:24:34Z | |
dc.date.accessioned | 2022-10-05T18:19:53Z | |
dc.date.available | 2014-05-27T11:24:34Z | |
dc.date.available | 2022-10-05T18:19:53Z | |
dc.date.created | 2014-05-27T11:24:34Z | |
dc.date.issued | 2009-12-17 | |
dc.identifier | 2009 IEEE Power and Energy Society General Meeting, PES '09. | |
dc.identifier | http://hdl.handle.net/11449/71483 | |
dc.identifier | 10.1109/PES.2009.5275236 | |
dc.identifier | 2-s2.0-71849103813 | |
dc.identifier | 0614021283361265 | |
dc.identifier.uri | http://repositorioslatinoamericanos.uchile.cl/handle/2250/3920668 | |
dc.description.abstract | In this work the multiarea optimal power flow (OPF) problem is decoupled into areas creating a set of regional OPF subproblems. The objective is to solve the optimal dispatch of active and reactive power for a determined area, without interfering in the neighboring areas. The regional OPF subproblems are modeled as a large-scale nonlinear constrained optimization problem, with both continuous and discrete variables. Constraints violated are handled as objective functions of the problem. In this way the original problem is converted to a multiobjective optimization problem, and a specifically-designed multiobjective evolutionary algorithm is proposed for solving the regional OPF subproblems. The proposed approach has been examined and tested on the RTS-96 and IEEE 354-bus test systems. Good quality suboptimal solutions were obtained, proving the effectiveness and robustness of the proposed approach. ©2009 IEEE. | |
dc.language | eng | |
dc.relation | 2009 IEEE Power and Energy Society General Meeting, PES '09 | |
dc.rights | Acesso aberto | |
dc.source | Scopus | |
dc.subject | Decomposition methods | |
dc.subject | Evolutionary algorithm | |
dc.subject | Multiarea optimal power flow | |
dc.subject | Multiobjective optimization | |
dc.subject | Discrete variables | |
dc.subject | Multi objective evolutionary algorithms | |
dc.subject | Multi-objective optimization problem | |
dc.subject | Nonlinear constrained optimization problems | |
dc.subject | Objective functions | |
dc.subject | Optimal dispatch | |
dc.subject | Optimal power flow problem | |
dc.subject | Optimal power flows | |
dc.subject | Sub-problems | |
dc.subject | Suboptimal solution | |
dc.subject | Test systems | |
dc.subject | Acoustic generators | |
dc.subject | Constrained optimization | |
dc.subject | Electric load flow | |
dc.subject | Evolutionary algorithms | |
dc.subject | Operations research | |
dc.subject | Potential energy | |
dc.subject | Potential energy surfaces | |
dc.subject | Power electronics | |
dc.title | Multiarea optimal power flow using multiobjective evolutionary algorithm | |
dc.type | Trabalho apresentado em evento | |