A bi-level optimization method for vehicle-UAV collaborative inspection of VSC-HVDC transmission lines

WU Kunxiao; GUO Tao; ZHANG Jing; ZHENG Xin; ZHENG Jianyong; SHA Haoyuan; MEI Fei

doi:10.19783/j.cnki.pspc.260202

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A bi-level optimization method for vehicle-UAV collaborative inspection of VSC-HVDC transmission lines

更新时间：2026-07-27

- A bi-level optimization method for vehicle-UAV collaborative inspection of VSC-HVDC transmission lines
- Power System Protection and Control Vol. 54, Issue 13, (2026)
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- DOI：10.19783/j.cnki.pspc.260202
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- Published：2026
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WU Kunxiao, GUO Tao, ZHANG Jing, et al. A bi-level optimization method for vehicle-UAV collaborative inspection of VSC-HVDC transmission lines[J]. Power System Protection and Control, 2026, 54(13).
DOI：

WU Kunxiao, GUO Tao, ZHANG Jing, et al. A bi-level optimization method for vehicle-UAV collaborative inspection of VSC-HVDC transmission lines[J]. Power System Protection and Control, 2026, 54(13). DOI： 10.19783/j.cnki.pspc.260202.

摘要

针对柔性直流输电线路大规模、高频次车 - 机协同巡检作业效率偏低，车辆路径、无人机调度、电池分配高度耦合的难题，提出路径 - 能量协同双层嵌套优化框架。首先构建包含驻车决策、无人机作业半径、路径能耗的多目标统一约束优化模型；其次设计外层路径优化、内层能量调度联动的双层协同结构，以内层调度结果反馈修正外层车辆路径与资源配置；最后依托典型柔直线路巡检场景仿真验证。结果表明该算法 15–25 次迭代即可完成主要收敛，最优总作业时间 182 min，电池利用率 92.3%；相比现有协同方案总作业时长缩短 13.2%~25.3%，在巡检规模扩张、无人机续航变化场景下具备良好可扩展性与工程实用性。

Abstract

To address the efficiency limitations of vehicle-unmanned aerial vehicle (UAV) collaborative operations in large-scale and high-frequency inspections of VSC-HVDC transmission lines

this paper proposes a path-energy coordinated bi-level nested optimization framework to address the strong coupling among vehicle route planning

UAV task scheduling

and battery resource allocation. First

a unified multi-objective constrained optimization model is established

in which vehicle parking decisions

UAV operational range

and path-dependent energy consumption are incorporated into a single decision-making framework

thereby enabling coordinated modeling of route planning and energy allocation. Second

a bi-level optimization structure with collaborative evolution between outer-layer route optimization and inner-layer energy scheduling is constructed. The execution results of the inner-layer tasks are fed back to refine the outer-layer path search and resource allocation

thereby achieving coordinated optimization among vehicle routing

UAV task assignment

and battery scheduling. Finally

simulation studies are conducted based on a typical VSC-HVDC transmission line inspection scenario. The results show that the proposed method achieves major convergence within 15-25 iterations

reduces the total operation time to 182 min

and attains a battery utilization rate of 92.3%. Compared with existing collaborative optimization methods

the proposed method reduces the total operation time by 13.2%~25.3% and maintains good scalability and engineering applicability under expanded inspection scales and varying UAV endurance conditions.

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references

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CAI Lei, LI Jiliu, WANG Kai, et al. Optimal allocation and route design for station-based drone inspection of large-scale facilities[J]. Omega, 2025, 130.

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