Multi-objective Constrained Optimal Power Flow Based on Enhanced Ant Colony System Algorithm

This article proposes Enhanced Ant Colony System (EACS) algorithm to solve the Optimal Power Flow (OPF) problem. The EACS algorithm is an optimization technique inspired by the movements of real ant colonies to identify the optimum solutions of massive optimization problems. A local and global pheromone update has been used to enhance the ant colony system. Three objective functions are preferred as a single objective function, such as fuel cost, voltage stability index and emission. The weighted sum method was used to find the solution for different multi-objective function cases like minimization of fuel cost with voltage stability index and minimization of emission with voltage stability index. To determine the equality of the proposed algorithm, it has been tested on the IEEE-30 bus system. The EACS provides good results when compared with other methods in the literature.