Transmission network expansion planning under an improved genetic algorithm

Abstract

This paper describes the application of an improved genetic algorithm (IGA) to deal with the solution of the transmission network expansion planning (TNEP) problem. Genetic algorithms (GAs) have demonstrated the ability to deal with nonconvex, nonlinear, integer-mixed optimization problems, like the TNEP problem, better than a number of mathematical methodologies. Some special features have been added to the basic genetic algorithm (GA) to improve its performance in solving the TNEP problem for three real-life, large-scale transmission systems. Results obtained reveal that GAs represent a promising approach for dealing with such a problem. In this paper, the theoretical issues of GA applied to this problem are emphasized.