基于改进SSA的单阵列光伏清洁机器人路径规划

高瑜; 李杰; 田海波; 朱一轩; 杨浩南; 马创

doi:10.19912/j.0254-0096.tynxb.2025-0373

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太阳能学报 ›› 2026, Vol. 47 ›› Issue (7) : 457-464. DOI: 10.19912/j.0254-0096.tynxb.2025-0373

基于改进SSA的单阵列光伏清洁机器人路径规划

高瑜^1,2, 李杰¹, 田海波², 朱一轩¹, 杨浩南¹, 马创¹

作者信息 +

PATH PLANNING OF SINGLE-ARRAY PHOTOVOLTAIC CLEANING ROBOT BASED ON IMPROVED SSA

Gao Yu^1,2, Li Jie¹, Tian Haibo², Zhu Yixuan¹, Yang Haonan¹, Ma Chuang¹

Author information +

文章历史 +

摘要

为更高效地清洁光伏组件,对光伏组件清洁机器人的路径规划进行研究,提出一种基于改进麻雀算法（HASSA）的移动机器人路径规划方法。引入Halton序列来改善种群分布不均匀的问题,设计一个动态因子对发现者和追随者数量进行自适应调整来提升麻雀算法的寻优能力。构建清洁机器人路径规划模型,并考虑实际情况重新构造适应度值函数。将改进的麻雀算法应用于求解光伏清洁路径规划问题中,进行仿真实验对多种算法展开横向对比。实验结果表明,HASSA所得到的路径综合性能最好。最后进行实地实验,证明该方法在光伏清洁路径规划问题上相较于传统算法具有一定的优越性。

Abstract

To improve the cleaning efficiency of photovoltaic modules, this study investigates path planning for a photovoltaic cleaning robot and proposes a mobile robot path-planning method based on an improved sparrow search algorithm （HASSA）. A Halton sequence is introduced to alleviate the non-uniform distribution of the initial population, and a dynamic factor is designed to adaptively adjust the numbers of discoverers and followers, thereby enhancing the optimization capability of the sparrow search algorithm. A path-planning model for the cleaning robot is established, and the fitness value function is reconstructed by considering practical operating conditions. The improved sparrow search algorithm is then applied to the photovoltaic cleaning path-planning problem, and simulation experiments are conducted to compare its performance with that of several other algorithms. The results show that the path obtained by HASSA achieves the best overall path performance. Finally, field experiments are carried out, and the results indicate that the proposed method performs better than conventional algorithms in photovoltaic cleaning path planning.

导出引用

高瑜, 李杰, 田海波, 朱一轩, 杨浩南, 马创. 基于改进SSA的单阵列光伏清洁机器人路径规划[J]. 太阳能学报. 2026, 47(7): 457-464 https://doi.org/10.19912/j.0254-0096.tynxb.2025-0373

Gao Yu, Li Jie, Tian Haibo, Zhu Yixuan, Yang Haonan, Ma Chuang. PATH PLANNING OF SINGLE-ARRAY PHOTOVOLTAIC CLEANING ROBOT BASED ON IMPROVED SSA[J]. Acta Energiae Solaris Sinica. 2026, 47(7): 457-464 https://doi.org/10.19912/j.0254-0096.tynxb.2025-0373

中图分类号： TM914.4

参考文献

[1] 陈帅, 黄敏, 缪全诚. 碳中和背景下光伏新能源产业高质量发展策略研究[J]. 现代工业经济和信息化, 2023, 13(7): 196-198.
Chen S, Huang M, Miao Q C.Study on the strategy of high quality development of photovoltaic new energy industry in the context of carbon neutrality[J]. Modern Industrial Economy and Informationization, 2023, 13(7): 196-198.
[2] 陈喜军, 艾琳, 司俊龙. 2025年中国光伏发电行业发展现状与展望[J]. 水力发电, 2026, 52(5): 1-6.
Chen X J, Ai L, Si J L.Current status and prospects of China's photovoltaic power generation industry in 2025[J]. Water Power, 2026, 52(5): 1-6.
[3] International Renewable Energy AgencY (IRENA). Future of solar photovoltaic: deployment, investment, technology, grid integration and socio-economic aspects (a global energy transformation: paper)[R]. Abu Dhabi: International Renewable Energy Agency, 2019:1-73.
[4] Kazem H A, Chaichan M T.Experimental analysis of the effect of dust's physical properties on photovoltaic modules in Northern Oman[J]. Solar Energy, 2016, 139: 68-80.
[5] Tang S X, Xing Y, Chen L, et al.Review and a novel strategy for mitigating hot spot of PV panels[J]. Solar Energy, 2021, 214: 51-61.
[6] 宁会峰, 程荣展, 王伟志, 等. 积灰对光伏发电的影响及除尘效果实验研究[J]. 太阳能学报, 2020, 41(11): 120-125.
Ning H F, Cheng R Z, Wang W Z, et al.Experimental study on influence of dust accumulation on photovoltaic power generation and dust removal effect[J]. Acta Energiae Solaris Sinica, 2020, 41(11): 120-125.
[7] 王永强. 基于无人机及机器视觉的光伏电站 “热斑效应” 检测系统研究[J]. 科技视界, 2019, 9(15): 53, 15.
Wang Y Q. Research on detection system of “hot spot effect” of photovoltaic power station based on UAV and machine vision[J]. Science & Technology Vision, 2019, 9(15): 53, 15.
[8] 林志鸿, 曾飞, 王哲, 等. 灰尘对光伏电站发电性能的影响[J]. 科技创新与应用, 2022, 12(12): 90-93.
Lin Z H, Zeng F, Wang Z, et al.Influence of dust on power generation performance of photovoltaic power station[J]. Technology Innovation and Application, 2022, 12(12): 90-93.
[9] Asbayou A, Smestad G P, IsmaiL I, et al. Electro-optical model of soiling effects on photovoltaic panels and performance implications[J]. Energy Engineering, 2024, 121(2): 243-258.
[10] Jaafar S S, Maarof H A, Salh R T, et al.Non-uniform dust distribution effect on photovoltaic panel performance[J]. Renewable Energy and Sustainable Development, 2023, 9(1): 1-10.
[11] Rusănescu C O, Rusănescu M, Istrate I A, et al.The effect of dust deposition on the performance of photovoltaic panels[J]. Energies, 2023, 16(19): 6794.
[12] 徐晨阳, 周全民, 王春旭, 等. 光伏板智能清洁机器人设计与实现[J]. 机床与液压, 2024, 52(11): 13-19.
Xu C Y, Zhou Q M, Wang C X, et al.Design and implementation of an intelligent cleaning robot for photovoltaic panels[J]. Machine Tool & Hydraulics, 2024, 52(11): 13-19.
[13] 高敬业, 孙慧平, 汪金芝. 太阳能光伏板清洁机器人自适应路径规划控制系统设计[J]. 机械设计与制造工程, 2023, 52(6): 87-90.
Gao J Y, Sun H P, Wang J Z.Design of adaptive path planning control system for solar photovoltaic panel cleaning robot[J]. Machine Design and Manufacturing Engineering, 2023, 52(6): 87-90.
[14] 王建军, 王金鑫, 张晨, 等. 清洁机器人光伏电站复杂地形动态路径规划方法研究[J]. 凿岩机械气动工具, 2023, 49(4): 10-18, 27.
Wang J J, Wang J X, Zhang C, et al.Research on dynamic path planning method for cleaning robots of photovoltaic power plants in complicated topography[J]. Rock Drilling Machinery & Pneumatic Tools, 2023, 49(4): 10-18, 27.
[15] 李翠明, 吴新民, 龚俊. 光伏组件清洁机器人真实地形的路径规划[J]. 太阳能学报, 2022, 43(1): 341-347.
Li C M, Wu X M, Gong J.Path planning of real terrain for solar panel cleaning robot[J]. Acta Energiae Solaris Sinica, 2022, 43(1): 341-347.
[16] 刘雪燕. 沙漠光伏电池板清洗机器人的路径规划研究和设计[J]. 光源与照明, 2021(6): 67-68.
Liu X Y.Research and design of path planning for cleaning robot of photovoltaic panel in desert[J]. Lamps & Lighting, 2021(6): 67-68.
[17] 张晓倩, 黄磊, 石雨婷, 等. 基于多目标优化的改进蚁群路径规划算法[J]. 现代制造工程, 2023(11): 40-46.
Zhang X Q, Huang L, Shi Y T, et al.Improved ant colony path planning algorithm based on multi-objective optimization[J]. Modern Manufacturing Engineering, 2023(11): 40-46.
[18] Xue J K, Shen B.A novel swarm intelligence optimization approach: sparrow search algorithm[J]. Systems Science & Control Engineering, 2020, 8(1): 22-34.
[19] 张月栋, 莫愿斌. 改进的麻雀搜索算法及其求解旅行商问题[J]. 计算机系统应用, 2022, 31(2): 200-206.
Zhang Y D, Mo Y B.Improved sparrow search algorithm and its application in TSP[J]. Computer Systems & Applications, 2022, 31(2): 200-206.
[20] Bangyal W H, Batool H, Rauf H T, et al.An improved particle swarm optimization algorithm with Chi-square mutation strategy[J]. International Journal of Advanced Computer Science and Applications, 2019, 10(3): 481-491.
[21] 唐延强, 李成海, 宋亚飞, 等. 自适应变异麻雀搜索优化算法[J]. 北京航空航天大学学报, 2023, 49(3): 681-692.
Tang Y Q, Li C H, Song Y F, Et al. Adaptive mutation sparrow search optimization algorithm[J]. Journal of Beijing University of Aeronautics and Astronautics, 2023, 49(3): 681-692.