Skip to main content
SpringerLink
Log in

Automatic Zoning Optimization Path Planning Method for UAV Inspection Path in Photovoltaic Power Station

  • Conference paper
  • First Online:
Proceedings of the 2nd International Conference on Internet of Things, Communication and Intelligent Technology (IoTCIT 2023)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 1197))

  • 68 Accesses

Abstract

The application of unmanned aerial vehicle (UAV) inspection is gradually popularized in photovoltaic power stations, but the existing UAV inspection planning methods are currently strongly limited by the application scenarios and consumes a large amount of manual work. To ameliorate this, an automatic zoning optimization path planning method for UAV inspection path in photovoltaic power station is proposed in this paper. For any application scenario or scale of the power station, the whole station inspection path can be generated systematically according to the actual layout information and inspection requirements of the photovoltaic power station, with no need to swap the batteries manually halfway. The method includes following steps, waypoint coordinates determination, hangar location and jurisdiction demarcation, flight zoning and path optimization. Moreover, dynamic planning and hybrid ecological symbiosis algorithm is carried out in hangar location selection and inspection path planning. The application case of an 80MW photovoltaic power plant in East China shows that the hybrid symbiotic organism search path planning algorithm performances greater stability at different power station scales. The proposed zoning optimization path planning method can be highly adapted to any power station distribution specificity and reduce the length of the inspection path in the whole station by 37.98%–68.4%, compared to the manual path planning scheme.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 299.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 379.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Snapshot of global PV markets 2023. https://iea-pvps.org/snapshot-reports/snapshot-2023. Accessed 2023

  2. Operation and Maintenance Best Practice Guidelines Version 5.0. https://www.solarpowereurope.org/insights/thematic-reports/o-and-m-best-practice-guidelines-version-5-0. Accessed 2021

  3. Quater, P.B., Grimaccia, F., Leva, S., et al.: Light Unmanned Aerial Vehicles (UAVs) for cooperative inspection of PV plants. IEEE J. Photovolt. 4(4), 1107–1113 (2014)

    Article  Google Scholar 

  4. Ding, Y., Cao, R., Liang, S., et al.: Density-based optimal UAV path planning for photovoltaic farm inspection in complex topography. In: 2020 Chinese Control and Decision Conference (CCDC), Hefei, China, pp. 3931–3936 (2020)

    Google Scholar 

  5. Wu, Y.: Collection Line Optimization Method for Offshore Wind Farm Based on Hybrid Symbiotic Organism Search Algotithm. North China Electric Power University, Beijing (2020)

    Google Scholar 

  6. Dong, M., Wu, C., Hou, F., et al.: Shortest path based simulated annealing algorithm for dynamic facility layout problem under dynamic business environment. Expert Syst. Appl. 36(8), 11221–11232 (2009)

    Article  Google Scholar 

  7. Shanthi, A.V.K., Mohankumar, G.: A novel approach for automated test path generation using TABU search algorithm. Int. J. Comput. Appl. 48(13), 28–34 (2012)

    Google Scholar 

  8. Zhang, W., Gong, X., Han, G., et al.: An improved ant colony algorithm for path planning in one scenic area with many spots. IEEE Access 5, 13260–13269 (2017)

    Article  Google Scholar 

  9. Ezugwu, A.E., Prayogo, D.: Symbiotic organisms search algorithm: theory, recent advances and applications. Expert Syst. Appl. 119, 184–209 (2019)

    Article  Google Scholar 

  10. Wang, W., Liu, G., Wen, W.: Study of a self-escape hybrid discrete particle swarm optimization for TSP. J. Comput. Appl. 08, 143–144+195 (2007)

    Google Scholar 

Download references

Acknowledgement

The work was supported in part by Zhejiang Province ‘Jianbin’ ‘Lingyan’ R&D Plan (2023C04041).

Author information

Authors and Affiliations

  1. Zhejiang Provincial Key Laboratory of Solar Energy Utilization and Energy Saving Technology, Zhejiang Baima Lake Laboratory Co., Ltd., Hangzhou, 311121, Zhejiang, China

    Waner Ding, Ling Hong, Yiwen Wu, Qu Shen, Qinchen Zhu, Jianwu Zhou, Rongmin Wu & Chunhui Shou

  2. Zhejiang Zheneng Zhongmei Zhoushan Coal and Electricity Co., Ltd., Zhoushan, 316131, Zhejiang, China

    Xiaoming Zhang & Jie Yu

Authors
  1. Waner Ding
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xiaoming Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ling Hong
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jie Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yiwen Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Qu Shen
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Qinchen Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Jianwu Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Rongmin Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Chunhui Shou
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Chunhui Shou .

Editor information

Editors and Affiliations

  1. Central South University, Changsha, Hunan, China

    Jian Dong

  2. School of Information Engineering, Shenzhen University, Shenzhen, Guangdong, China

    Long Zhang

  3. School of Information and Control Engineering, China University of Mining and Technolog, Xuzhou, Jiangsu, China

    Deqiang Cheng

Rights and permissions

Reprints and permissions

Copyright information

© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Ding, W. et al. (2024). Automatic Zoning Optimization Path Planning Method for UAV Inspection Path in Photovoltaic Power Station. In: Dong, J., Zhang, L., Cheng, D. (eds) Proceedings of the 2nd International Conference on Internet of Things, Communication and Intelligent Technology. IoTCIT 2023. Lecture Notes in Electrical Engineering, vol 1197. Springer, Singapore. https://doi.org/10.1007/978-981-97-2757-5_10

Download citation

  • DOI: https://doi.org/10.1007/978-981-97-2757-5_10

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-97-2756-8

  • Online ISBN: 978-981-97-2757-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation