IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v18y2025i11p2909-d1670140.html
   My bibliography  Save this article

A Two-Stage Planning Method for Rural Photovoltaic Inspection Path Planning Based on the Crested Porcupine Algorithm

Author

Listed:
  • Xinyu He

    (PowerChina Jiangxi Hydropower Engineering Bureau Co., Ltd., Nanchang 330000, China)

  • Xiaohui Yang

    (School of Information Engineering, Nanchang University, Nanchang 330031, China)

  • Shaoyang Chen

    (PowerChina Jiangxi Hydropower Engineering Bureau Co., Ltd., Nanchang 330000, China)

  • Zihao Wu

    (School of Information Engineering, Nanchang University, Nanchang 330031, China)

  • Xianglin Kuang

    (PowerChina Jiangxi Hydropower Engineering Bureau Co., Ltd., Nanchang 330000, China)

  • Qi Zhou

    (School of Information Engineering, Nanchang University, Nanchang 330031, China)

Abstract

Photovoltaic (PV) energy has become a pillar of clean energy in rural areas. However, its extensive deployment in regions with geographically dispersed locations and limited road conditions has made efficient inspection a significant challenge. To address these issues, this study proposes a multi-regional PV inspection path planning method based on the crested porcupine optimization (CPO) algorithm. This method first employs a hybrid optimization framework combining a genetic algorithm, Simulated Annealing, and Fuzzy C-Means Clustering (GASA-FCM) to divide PV power stations into multiple regions, adapting to their dispersed distribution characteristics. Subsequently, the CPO algorithm is used to calculate obstacle-avoidance paths, replacing the Euclidean distance in the traditional Traveling Salesman Problem (TSP) with adaptive rural road constraint conditions to better cope with the geographical complexity in real-world scenarios. The simulation results verify the advantages of this method, achieving significantly shorter path lengths, higher computational efficiency, and stronger stability compared to the traditional solutions, thereby improving the efficiency of rural PV inspection. Moreover, the proposed framework not only provides a practical inspection strategy for rural PV systems but also offers a solution to the Multiple-Depot Multiple Traveling Salesmen Problem (MDMTSP) under constrained conditions, expanding its application scope in similar scenarios.

Suggested Citation

  • Xinyu He & Xiaohui Yang & Shaoyang Chen & Zihao Wu & Xianglin Kuang & Qi Zhou, 2025. "A Two-Stage Planning Method for Rural Photovoltaic Inspection Path Planning Based on the Crested Porcupine Algorithm," Energies, MDPI, vol. 18(11), pages 1-18, June.
  • Handle: RePEc:gam:jeners:v:18:y:2025:i:11:p:2909-:d:1670140
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/18/11/2909/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/18/11/2909/
    Download Restriction: no
    ---><---

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:18:y:2025:i:11:p:2909-:d:1670140. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.