Abstract
The maintenance of photovoltaic systems is critical to ensure the reliability of the solar power plants. The increasing extension of the plants requires novel data acquisition technologies to improve the maintenance efficiency. Unmanned aircraft vehicles equipped with thermographic cameras lead to the reduction of maintenance costs and operational risks. The main contribution of this paper is a novel approach for increasing the effectiveness of aerial inspections, ensuring the measurement of all panels with a required accuracy, reducing time and energy consumption. This methodology is based on the identification of the field of view and the point of interests for photovoltaic aerial inspections. An original optimizing model is developed to find the points of inspection. Particle swarm optimization and genetic algorithms are employed to obtain the waypoints and inspection routes. These algorithms provide good results for operation parameters, including height, view angles, waypoints and route optimization. The approach is proved and validated through a real solar plant inspection. The methodology has been demonstrated to be adequate for the case study, ensuring high-quality inspection with an optimised resource consumption.
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