Thermal Image Analysis for Fault Detection and Diagnosis of PV Systems
Abstract
This research presents thermal image analysis for Fault Detection and Diagnosis (FDD) of Photovoltaic (PV) Systems. The traditional manual approach of PV inspection is generally more time-consuming, more dangerous, and less accurate than the modern approach of PV inspection using Aerial Thermography (AT). Thermal image analysis conducted in this research will contribute to utilizing thermography and UAVs for PV inspection by providing a more accurate and cost-efficient diagnosis of PV faults. In this research, PV module inspection was achieved through two steps: (i) PV monitoring and (ii) PV Fault Detection and Diagnosis (FDD). In the PV monitoring stage, PV cells were monitored by aerial thermography. In this stage, the thermal data was acquired for the next step. In the PV FDD stage, hot spot phenomenon and the condition of the PV modules were detected and measured. The FDD stage was conducted in three steps: (i) fault detection, (ii) fault isolation, and (iii) fault identification. The fault detection stage determined whether the PV module has an abnormal condition. Next, in the fault isolation stage, the location and the area of possible hot spots were identified. Lastly, the number of the hot spots were counted in the fault identification stage. The proposed research will help with the problems of the modern PV inspection and, eventually, contribute to the performance of PV power generation.
Degree
M.Sc.
Advisors
Springer, Purdue University.
Subject Area
Aerospace engineering|Alternative Energy|Condensed matter physics|Energy|Physics|Robotics|Transportation
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