电力应急系统灾前灾后无人机巡检航迹最优规划算法研究

陈 彩娜¹, 谭 明¹, 郑 松源¹, 张 壮领¹, 潘 歧深¹, 戴 宪华²
1、广东省广州市海珠区琶洲大道 63 号
2、中山大学深圳校区

摘要

在电力系统巡检维护领域，传统人工巡检因设备增多和环境复杂，暴露出效率低、风险大等问题。虽传统路径优
化有成果，但综合考虑电力设备重要性和历史数据时仍有提升空间。本文融合旅行商问题求解的启发式算法，结合电力设
备优先级和历史受灾数据，构建更全面的巡检路径优化模型，保障关键设备优先巡检。仿真实验显示，该模型在实际电力
系统巡检中应用价值高，能降本增效，提升巡检安全性与可靠性。

关键词

路径规划；启发式算法；无人机巡检

参考

[1] 刘智勇 , 赵晓丹 , 祁宏昌 , 李艳飞 . 新时代无人机电

力巡检技术展望 [J]. 南方能源建设 ,2019, 6(4): 1-5.

[2]Shi, L., Mehrooz, G., & Jacobsen, R. H. (2021, June).

Inspection path planning for aerial vehicles via sampling-based

sequential optimization. In 2021 International Conference on

Unmanned Aircraft Systems (ICUAS) (pp. 679-687). IEEE.

[3]Cai, L., Li, J., Wang, K., Luo, Z., & Qin, H. (2024).

Optimal allocation and route design for station-based drone

inspection of large-scale facilities. Omega, 103172.

[4]Ait Saadi, A., Soukane, A., Meraihi, Y., Benmessaoud

Gabis, A., Mirjalili, S., & Ramdane-Cherif, A. (2022). UAV path

planning using optimization approaches: A survey. Archives of

Computational Methods in Engineering,29(6),4233-4284.

[5]Saeed, R. A., Omri, M., Abdel-Khalek, S., Ali, E. S., &

Alotaibi, M. F. (2022). Optimal path planning for drones based on

swarm intelligence algorithm. Neural Computing and Applications,

34(12):10133-10155.

[6] HUANG Yuhao, HAN Chao, ZHAO Minghui, DU

Qiankun, WANG Shigang. Multi-Objective Optimization Strategy

of Trajectory Planning for Unmanned Aerial Vehicles Considering

Constraints of Safe Flight Corridors[J]. Journal of Shanghai

Jiaotong University,2022,56(8): 1024-1033

[7] 李 保 胜 . Review of UAV Path Planning Algorithms in

3D Environment. Computer Science and Application. (2022). 12.

1363-1370.

[8] 王成皓 ; 裴慧坤 ; 王振华 ; 徐坤 . 无人机多机多作业

协同电力巡检路径规划研究 [J]. 微型电脑应用，2023，39

（05）：119-122.

[9] 赵子丰 . 风电场 5G 无人机巡检技术与路径优化设计

[J]. 粘接 , 2023, 50(7):184-188.

[10] Jiang, S., Jiang, W., Huang, W., & Yang, L. (2017).

UAV-based oblique photogrammetry for outdoor data acquisition

and offsite visual inspection of transmission line. Remote Sensing,

9(3), 278.