This paper introduces DUBIO, a cloud platform which analyzes the radiometric infrared videos uploaded by drones which patrol large PV plants. Thanks to its artificial vision algorithms, DUBIO does not require any human intervention in selecting and associating the framed PV modules to the corresponding ones in the topology of the plant. DUBIO implements an innovative diagnostic protocol, which evidences the behavior of the module independently from the environmental conditions, i.e., decontextualizes the overheating of each module from the external conditions. By this way, the data automatically computed and collected in a multimedia database provide the O&M technicians with significant information, useful also for studying the ageing trend of each module of the monitored plant. The system, which is currently under a massive test in several plants of Enel Green Power, will constitute a pay for use service cloud platform worldwide available to the O&M market, since the second quarter of 2018.
DUBIO: a fully automatic Drones & cloUd Based Infrared mOnitoring system for large-scale PV plants / Colaprico, Marco; Francesca de Ruvo, Maria; Leotta, Giuseppe; Bizzarri, Fabrizio; Vergura, Silvano; Marino, Francescomaria. - ELETTRONICO. - (2018). (Intervento presentato al convegno IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe, EEEIC/I and CPS Europe 2018 tenutosi a Palermo, Italy nel June 12-15, 2018) [10.1109/EEEIC.2018.8493736].
DUBIO: a fully automatic Drones & cloUd Based Infrared mOnitoring system for large-scale PV plants
Silvano Vergura
;Francescomaria Marino
2018-01-01
Abstract
This paper introduces DUBIO, a cloud platform which analyzes the radiometric infrared videos uploaded by drones which patrol large PV plants. Thanks to its artificial vision algorithms, DUBIO does not require any human intervention in selecting and associating the framed PV modules to the corresponding ones in the topology of the plant. DUBIO implements an innovative diagnostic protocol, which evidences the behavior of the module independently from the environmental conditions, i.e., decontextualizes the overheating of each module from the external conditions. By this way, the data automatically computed and collected in a multimedia database provide the O&M technicians with significant information, useful also for studying the ageing trend of each module of the monitored plant. The system, which is currently under a massive test in several plants of Enel Green Power, will constitute a pay for use service cloud platform worldwide available to the O&M market, since the second quarter of 2018.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
