Long-term path planning with optimal deployment of a charging station for monitoring photovoltaic solar farms

• Published in: Scientific reports Vol. 14; no. 1; pp. 17279 - 15
• Main Authors: Huang, Yong, Chen, Zhiyan, Chu, Jing, Wang, Haoran, Sun, Siliang
• Format: Journal Article
• Language: English
• Published: England Nature Publishing Group 27.07.2024; Nature Publishing Group UK; Nature Portfolio
• Subjects: Algorithms; Automation; Linear programming; Nonlinear programming; Photovoltaics; Solar energy; Solar farms; Surveillance; Temporal logic; Unmanned aerial vehicles
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-024-68160-w

Quadrotor technology has become increasingly important in the field of photovoltaic (PV) solar farm monitoring, but short battery life is one of the primary factors limiting its further application. To address above issue, this study proposes a linear temporal logic (LTL)-based path planning algorithm that considers the need for charging together with multiple visits to PV equipments, a single visit to communication equipment, and the avoidance of restricted regions, which enables the long-term monitoring of PV solar farms. Particularly, the location of a charging station can be determined optimally and efficiently by a heuristic algorithm based on the nonlinear programming and branch and bound (NLP-BB) algorithm. The simulation results indicate that the proposed method effectively solves the long-term monitoring path planning problem that is coupled with the optimal deployment of the charging station.