A novel multi-objective optimizer for handling reactive power

Author

Medina, Miguel A. ; Ramirez, J.M. ; Coello, Carlos A. Coello

Author_Institution

Electr. Eng. Dept., CINVESTAV - Guadalajara, Guadalajara, Mexico

fYear

2013

fDate

16-20 June 2013

Firstpage

1

Lastpage

6

Abstract

A novel population-based optimization algorithm for solving a reactive power handling problem is proposed. The algorithm mimics the interaction between the teacher and students. The searching process is broken down in two parts: the Teacher Phase and the Learner Phase. This paper proposes a multi-objective teaching learning algorithm based on decomposition (MOTLA/D). The proposed method is validated on a 190-buses test system, and it is compared with respect to a decomposition-based multi-objective evolutionary algorithm (MOEA/D), which represents a state-of-the-art algorithm.

Keywords

optimisation; reactive power; search problems; MOEA/D; MOTLA/D; decomposition-based multiobjective evolutionary algorithm; learner phase; multiobjective optimizer; multiobjective teaching learning algorithm based on decomposition; population-based optimization algorithm; reactive power handling problem; teacher phase; Generators; Indexes; Optimization; Power system stability; Reactive power; Stability criteria; Vectors; Optimization; Power system planning; Reactive power;

fLanguage

English

Publisher

ieee

Conference_Titel

PowerTech (POWERTECH), 2013 IEEE Grenoble

Conference_Location

Grenoble

Type

conf

DOI

10.1109/PTC.2013.6652098

Filename

6652098