Optimal Transmission Expansion Planning Using Ant Colony Optimization

Abstract

This paper proposes the application of ant colony optimization (ACO) to solve a static transmission expansion planning(STEP) problem based on a DC power flow model. The major objective is to minimize the investment cost of transmission linesadded to an existing network in order to supply the forecasted load as economically as possible and subject to many systemconstraints i.e. the power balance, the generation requirements, line connections and thermal limits. The Garver's six-buses system, isanalyzed to appraise the feasibility of the ACO. The experimental results obtained by ACO are compared to those obtained by theconventional approaches of the Genetic Algorithm (GA), and the Tabu Search (TS) algorithm. The results show that the ACOmethod outperforms other methods in convergence characteristic and computational efficiency.