Multiarea optimal power flow using multiobjective evolutionary algorithm

• Autor(a) principal: Amorim, E. A.
• Data de Publicação: 2009
• Outros Autores: Lima, F. G M, Romero, R. [UNESP], Mantovani, J. R S [UNESP]
• Tipo de documento: Artigo de conferência
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1109/PES.2009.5275236; http://hdl.handle.net/11449/71483
• topic: 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

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.