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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
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    References listed on IDEAS

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    1. Su, Xiaoning & Liu, Pengfei & Mei, Yingdan & Chen, Jiaru, 2023. "The role of rural cooperatives in the development of rural household photovoltaics: An evolutionary game study," Energy Economics, Elsevier, vol. 126(C).
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