柔性直流输电线路车–机协同巡检的双层优化方法

邬昆晓; 郭涛; 张敬; 郑鑫; 郑建勇; 沙浩源; 梅飞

doi:10.19783/j.cnki.pspc.260202

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柔性直流输电线路车–机协同巡检的双层优化方法

工程应用 | 更新时间：2026-07-27

- 柔性直流输电线路车–机协同巡检的双层优化方法
- A bi-level optimization method for vehicle-UAV collaborative inspection of VSC-HVDC transmission lines
- 电力系统保护与控制 2026年54卷第13期
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- DOI：10.19783/j.cnki.pspc.260202
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- 纸质出版：2026
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邬昆晓, 郭涛, 张敬, 等. 柔性直流输电线路车–机协同巡检的双层优化方法[J]. 电力系统保护与控制, 2026,54(13).

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).
邬昆晓, 郭涛, 张敬, 等. 柔性直流输电线路车–机协同巡检的双层优化方法[J]. 电力系统保护与控制, 2026,54(13). DOI： 10.19783/j.cnki.pspc.260202.

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.

关键词

Keywords

references

RAFAEL S, LUCIANA A, ALESSANDRO V, et al. Matheuristics for multi-UAV routing and recharge station location for complete area coverage[J]. Sensors, 2021, 21(5).

MENG Bin, LU Na, WANG Qingqi, et al. The progress and trend of UAV power line inspection: a bibliometrics-based visualization analysis[J]. Recent Advances in Electrical Electronic Engineering, 2025, 18(8): 1188-1204.

LI Y, DONG X, DING Q, et al. Improved A-STAR algorithm for power line inspection UAV path planning[J]. Energies, 2024, 17: 53-64.

YANG L, FENG X, FENG X, et al. Measurement equipment inspection path planning and optimization based on quantum annealing algorithm[J]. International Journal of High Speed Electronics and Systems, 2025, 35(3).

ZHANG H, GUO C, ZHAI D, et al. Application of improved crown porcupine optimizer in UAV path planning based on dynamic weighted JAYA-CPO attack strategy[J]. Protection and Control of Modern Power Systems, 2025, 10(6): 101-127.

XU C, LI Q, ZHOU Q, et al. Power line-guided automatic electric transmission line inspection system[J]. IEEE Transactions on Instrumentation and Measurement, 2022, 71.

LI Kun, YAN Xinxin, HAN Ying. Multi-mechanism swarm optimization for multi-UAV task assignment and path planning in transmission line inspection under multi-wind field[J]. Applied Soft Computing, 2024, 150.

WANG Y, LIU X, ZHOU W, et al. Global-local hybrid path planning and path point tracking control for unmanned surface vehicles[J]. IEEE/ASME Transactions on Mechatronics, 2026, 31(2): 1987-1998.

HUANG S, HOU M, YUAN X, et al. Learn once plan arbitrarily (LOPA): dynamic observation-based deep reinforcement learning method for global path planning in mountainous terrain environment[J]. IEEE Transactions on Artificial Intelligence, 2026, 7(2): 1168-1184.

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.

ZHANG M, XU Y, YU X, et al. M-SIALNS for air-ground collaborative inspection: spatio-temporal conflict mitigation in complex bi-layer networks[J]. IEEE Transactions on Intelligent Transportation Systems, 2026, 27(3): 3530-3545.

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