Ant Colony Optimization based algorithm to determine the optimum route for overhead power transmission lines

Abstract

Electrical power distribution networks present one of the most essential infrastructure projects. Despite of the vitality of this sector and the huge budgets of their projects, but it is still depends on traditional manual routing techniques which are slow, expensive and inefficient comparing with the current AI revolutionary techniques. Hence, this research presented a novel AI model for optimizing “overhead power transmitting lines” (OHPTL) routing using Ant Colony Optimization (ACO) technique. The proposed technique depends on the core routine (which can generate random and valid routes and estimate their total cost) and searching algorithm (which uses ACO technique to find the optimum route among the generated routes). As a prototype, the proposed technique was codes in “Visual Basic for Applications” VBA, while MS-EXCEL was used to handle the graphical inputs and outputs. The functionality of the technique was validated using three virtual case studies and its optimization capability was tested using a real-life case study. The results showed that the total cost of the optimized route is about 75% of the existing route.