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Research on adaptive collaborative dispatch optimization algorithms for drones in distribution networks.

Xiangdong Zu1, Jiaxing Fu2, Hai Zhao3

  • 1Electric Power Research Institute of State Grid East Inner Mongolia Electric Power Co., Ltd., Inner Mongolia Autonomous Region, hohhot, 010010, China. 17814315298@163.com.

Scientific Reports
|July 7, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces an Adaptive Ant Colony Optimization Algorithm with Elite Strategy (AACOES) for efficient multi-UAV power line inspection scheduling. The AACOES algorithm enhances convergence speed and solution quality, outperforming other methods in complex environments.

Keywords:
AACOESAnt colony optimizationFlight path planningUnmanned aerial vehicle

Related Experiment Videos

Area of Science:

  • Robotics and Automation
  • Operations Research
  • Artificial Intelligence

Background:

  • Power line inspection is critical for grid stability.
  • Traditional inspection methods are inefficient and hazardous.
  • Multi-UAV systems offer a promising solution for enhanced inspection efficiency.

Purpose of the Study:

  • To develop an advanced optimization algorithm for multi-UAV collaborative power line inspection scheduling.
  • To address practical constraints such as UAV flight dynamics, battery life, and wind conditions.
  • To improve the speed and global search capability of existing ant colony optimization algorithms.

Main Methods:

  • Proposed an Adaptive Ant Colony Optimization Algorithm with Elite Strategy (AACOES).
  • Incorporated an elite strategy and adaptive adjustment factors to optimize pheromone updates.
  • Developed a scheduling optimization model considering real-world operational constraints.

Main Results:

  • AACOES demonstrated superior performance compared to Particle Swarm Optimization, Genetic Algorithms, and traditional Ant Colony Optimization.
  • Achieved significant improvements in single-unit performance and total flight distance.
  • Exhibited more stable convergence and effectiveness in complex environments.

Conclusions:

  • AACOES provides an efficient and reliable technical approach for multi-UAV collaborative inspection scheduling.
  • The algorithm is well-suited for practical applications like power line inspections.
  • Validated effectiveness and practicality in complex, real-world scenarios.