Resource Allocation Method for Collaborative Inspection of Distribution Lines by Vehicles and Unmanned Aerial Vehicles Considering Path-scheduling Feedback

WU Kunxiao; YIN Yuhan; LIU Xiaoyi; ZHENG Jianyong; MEI Fei

doi:10.7500/AEPS20260302008

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Resource Allocation Method for Collaborative Inspection of Distribution Lines by Vehicles and Unmanned Aerial Vehicles Considering Path-scheduling Feedback

Application Research | 更新时间：2026-09-22

- Resource Allocation Method for Collaborative Inspection of Distribution Lines by Vehicles and Unmanned Aerial Vehicles Considering Path-scheduling Feedback
- Automation of Electric Power Systems Vol. 50, Issue 18, Pages: 166-175(2026)
- 作者机构：
  
  1.东南大学电气工程学院，江苏省南京市 210096
  2.河海大学电气与动力工程学院，江苏省南京市 210024
- 作者简介：
- 基金信息：
  
  National Key R&D Program of China(2022YFE0140600);State Grid Jiangsu Electric Power Co., Ltd(J2025048)
- DOI：10.7500/AEPS20260302008
  CLC：
- Received：02 March 2026，
  
  Revised：2026-06-28，
  
  Online First：03 July 2026，
  
  Published：25 September 2026
- 稿件说明：
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邬昆晓,印宇涵,刘笑一等.考虑路径-调度反馈的车机协同配电线路巡检资源配置方法[J].电力系统自动化,2026,50(18):166-175.

WU Kunxiao,YIN Yuhan,LIU Xiaoyi,et al.Resource Allocation Method for Collaborative Inspection of Distribution Lines by Vehicles and Unmanned Aerial Vehicles Considering Path-scheduling Feedback[J].Automation of Electric Power Systems,2026,50(18):166-175.
邬昆晓,印宇涵,刘笑一等.考虑路径-调度反馈的车机协同配电线路巡检资源配置方法[J].电力系统自动化,2026,50(18):166-175. DOI： 10.7500/AEPS20260302008.

WU Kunxiao,YIN Yuhan,LIU Xiaoyi,et al.Resource Allocation Method for Collaborative Inspection of Distribution Lines by Vehicles and Unmanned Aerial Vehicles Considering Path-scheduling Feedback[J].Automation of Electric Power Systems,2026,50(18):166-175. DOI： 10.7500/AEPS20260302008.

摘要

针对配电线路车辆-无人机协同巡检中资源配置与协同调度强耦合以及难以兼顾效率与资源利用的问题，提出一种资源配置与执行调度联动优化方法。首先，构建资源配置与路径调度的统一建模框架，将无人机数量与驻车点布局由先验参数转化为优化变量；然后，在双层多目标进化框架下，由外层进行资源配置搜索，内层完成车辆路径规划与无人机任务调度，并基于执行结果构建资源配置反馈评价机制，实现资源配置与执行调度的联动优化；最后，通过典型配电巡检场景、工程应用场景及无人机失效工况验证所提方法性能。结果表明，所提方法在降低系统总作业时间的同时，可有效抑制资源冗余。相较于非支配排序遗传算法Ⅱ，总作业时间与综合代价分别降低约3.7%和5.4%，资源冗余率由11.6%降低至8.0%；在高比例无人机失效条件下，系统恢复调度代价仍保持稳定增长，验证了所提方法的有效性与鲁棒性。

Abstract

To address the strong coupling between resource allocation and collaborative scheduling in collaborative inspection of distribution lines by vehicles and unmanned aerial vehicles (UAVs)

and the difficulty in balancing operational efficiency and resource utilization

this paper proposes a joint optimization method for resource allocation and execution scheduling. First

a unified modeling framework for resource allocation and path scheduling is constructed

in which the number of UAVs and the layout of parking points are transformed from a priori parameters into optimization variables. Then

within a bi-level multi-objective evolutionary framework

the outer level performs resource allocation search

while the inner level handles vehicle routing and UAV task scheduling. Based on the execution results

a feedback evaluation mechanism for resource allocation is established to achieve joint optimization between resource allocation and execution scheduling. Finally

the performance of the proposed method is verified through typical distribution inspection scenarios

engineering application scenarios

and UAV failure conditions. Results demonstrate that the proposed method reduces the total operation time while effectively suppressing resource redundancy. Compared with the non-dominated sorting genetic algorithm Ⅱ

the total operation time and comprehensive cost are reduced by approximately 3.7% and 5.4%

respectively

and the resource redundancy rate decreases from 11.6% to 8.0%. Under high UAV failure ratios

the system recovery scheduling cost increases steadily

which validates the effectiveness and robustness of the proposed method.

关键词

Keywords

references

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