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Multiarea optimal power flow using multiobjective evolutionary algorithm
  • Universidade Federal de Mato Grosso do Sul (UFMS)
  • Universidade Estadual Paulista (UNESP)
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.
Issue Date: 
2009 IEEE Power and Energy Society General Meeting, PES '09.
  • Decomposition methods
  • Evolutionary algorithm
  • Multiarea optimal power flow
  • Multiobjective optimization
  • Discrete variables
  • Multi objective evolutionary algorithms
  • Multi-objective optimization problem
  • Nonlinear constrained optimization problems
  • Objective functions
  • Optimal dispatch
  • Optimal power flow problem
  • Optimal power flows
  • Sub-problems
  • Suboptimal solution
  • Test systems
  • Acoustic generators
  • Constrained optimization
  • Electric load flow
  • Evolutionary algorithms
  • Operations research
  • Potential energy
  • Potential energy surfaces
  • Power electronics
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Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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