Leveraging Artificial Intelligence and Genetic Algorithms for Enhanced Techno-Economic Conductor Selection in Power Transmission Systems

The selection of overhead conductors is a critical decision that defines the CAPEX and OPEX of transmission lines. However, when talking about joint optimization, that is, reaching a joint optimization between conductor-structure is computationally expensive due to the need to mechanically validate each conductor alternative in specialized software. This work presents a novel methodology, already implemented and validated, that overcomes this barrier through the use of Artificial Intelligence (AI), genetic algorithms and robotic automation using Python.