Ingeteam Uses Drones for Enhanced Solar PV Plant Performance

At an operational level, the project will lead to improved panel inspection, shorter measurement-taking and post-processing times, while minimizing operation and maintenance costs and maximizing the service life of the plant.

Ingeteam is involved in a research project focused on optimizing PV plant performance with the use of drones. This new system is directed at meeting the main challenge faced by solar PV plants: The need to achieve high returns in order to compete against other sources of energy, both renewable and fossil.

The first drone-based inspection service is set to be launched in the course of next year. The drone is equipped with in-built sensors, algorithms to detect and classify potential causes of reduced panel performance (damage, soiling or deterioration), other algorithms to provide reliable, robust indicators of the technical and economic performance of the system, and an application to optimize maintenance activities.

At an operational level, the project will lead to improved panel inspection, shorter measurement-taking and post-processing times, while minimizing operation and maintenance costs and maximizing the service life of the plant.

The project is named SCARAB and is headed by Ingeteam, with the participation of the University of Castilla La Mancha. It is set to be completed by the end of 2019 and has a budget of 648,510 euros, co-financed by the Ministry of Economy and Competitiveness and ERDF funds as part of the Spanish Program for Research, Development and Innovation, directed at meeting the Challenges of Society, within the framework of the Spanish Plan for Scientific and Technical Investigation and Innovation 2013-2016.

At a technical level, the project focuses on the development of new technologies, in two areas. Firstly, the monitoring and processing of signals for the inspection and automatic fault detection in PV panels through the use of more efficient sensors. Secondly, the use of information technologies to develop advanced fault classification algorithms, estimate PV plant status and optimize maintenance strategies.