A Comparative Study of State-of-the-Art Transmission Expansion Planning Tools

Abstract

In this paper, a novel differential evolution algorithm (DEA) is applied directly to the DC power flow based model to solve the transmission expansion planning (TEP) problem. This paper presents a major development of artificial intelligent (AI) algorithms through application of a DEA to the TEP problem. The effectiveness of the proposed development is initially demonstrated via analysis of the Garver's six-bus test system and the IEEE 25-bus test system within the mathematical programming environment of MATLAB. Analyses are performed using both a DEA and a conventional genetic algorithm (CGA) and a detailed comparative study is presented