Cable path optimization and conflict detection of transmission lines based on multi-agent system

With the continuous expansion of power grid scale and increasing complexity, rational planning of transmission line paths to avoid conflicts with topography, buildings and other facilities has become a key issue in power planning and design. In this paper, a hierarchical multi-agent system (MAS) architecture is proposed, which includes environmental awareness layer, agent decision-making layer and coordination and optimization layer, so as to realize intelligent planning of transmission line cable path. A distributed path optimization algorithm based on Multi-Agent Systems (MAS-DPOA) was further designed, incorporating the advantages of the Ant Colony Algorithm (ACA) and Genetic Algorithm (GA). This approach achieves rapid path optimization through the collaborative search by agents and genetic operations. Meanwhile, a distributed conflict detection mechanism based on MAS (MAS-CDCM) was proposed, utilizing the local sensing capabilities and communication mechanisms of agents to detect and report conflicts in real-time. Through the case study analysis of a 220kV transmission line in a mountainous area in southwestern China, the results show that compared with traditional methods, the MAS-DPOA method can reduce path length by 12.5%, decrease tower base costs by 18%, and increase conflict detection accuracy to 96%. It significantly reduces the volume of engineering work and minimizes social impact, offering an efficient and accurate solution for transmission line route planning with promising application prospects.