Optimal reactive power planning using evolutionary algorithms: a comparative study for evolutionary programming, evolutionary strategy, genetic algorithm, and linear programming

Author

Lee, Kwang Y. ; Yang, Frank F.

Author_Institution

Dept. of Electr. Eng., Pennsylvania State Univ., University Park, PA, USA

Volume

13

Issue

1

fYear

1998

fDate

2/1/1998 12:00:00 AM

Firstpage

101

Lastpage

108

Abstract

This paper presents a comparative study for three evolutionary algorithms (EAs) to the optimal reactive power planning (ORPP) problem: evolutionary programming, evolutionary strategy, and genetic algorithm. The ORPP problem is decomposed into P- and Q-optimization modules, and each module is optimized by the EAs in an iterative manner to obtain the global solution. The EA methods for the ORPP problem are evaluated against the IEEE 30-bus system as a common testbed, and the results are compared against each other and with those of linear programming

Keywords

genetic algorithms; linear programming; power system planning; reactive power; IEEE 30-bus system; P-optimization modules; Q-optimization modules; evolutionary algorithms; evolutionary programming; evolutionary strategy; genetic algorithm; linear programming; optimal reactive power planning; power system; Cost function; Evolutionary computation; Genetic algorithms; Genetic programming; Investments; Linear programming; Optimization methods; Power system planning; Reactive power; System testing;

fLanguage

English

Journal_Title

Power Systems, IEEE Transactions on

Publisher

ieee

ISSN

0885-8950

Type

jour

DOI

10.1109/59.651620

Filename

651620