Real Power Loss Reduction by Ant Colony Search Algorithm - Lenin, Kanagasabai (International Journal of Computer Sciences and Engineering, 2019)
The paper presents Ant colony search Algorithm (ACSA) for solving optimal reactive power problem. ACSA algorithms are developed based on the observation of foraging behavior of real ants. Although they are almost blind animals with very simple individual capacities, they can find the shortest route between their nest(s) and a source of food without using visual cues. They are also capable of adapting to changes in the environment; finding a new shortest path once the old one is no longer feasible due to a new obstacle. The studies by ethnologists reveal that such capabilities are essentially due to what is called pheromone trails, which ants use to communicate information among individuals regarding path and to decide where to go. During their trips a chemical trail (pheromone) is left on the ground. The pheromone guides other ants towards the target point. Furthermore, the pheromone evaporates over time. If many ants choose a certain path and lay down pheromones, the quantity of the trail increases and thus this trail attracts more and more ants. Each ant probabilistically prefers to follow a direction rich in pheromone rather than a poorer one. Proposed algorithm has been tested in standard IEEE 300 bus system and simulation results reveals about the better performance of the proposed algorithm in reducing the real power loss.