Distribution Network Path Planning Combining A * and Ant Colony Optimization Algorithm

In response to the problem of traditional path planning methods being difficult to find optimal solutions in complex environments, this study takes a certain area in Shaoxing City as an example and proposes a distribution network path planning method that combines the A algorithm and ant colony optimization algorithm (ACO). This area has diverse terrain and environmental features. By combining the fast optimization characteristics of algorithm A* with the global search capability of ant colony optimization algorithm, the aim is to improve the economic efficiency and reliability of the power grid. The experimental results show that this method effectively reduces planning difficulty and cost, and enhances the reliability of power supply. Future research will focus on optimizing algorithm parameters, improving search efficiency, and exploring algorithm fusion to develop optimization solutions that adapt to dynamic environments and support the operation of modern distribution networks.