Unsupervised Fault Detection and Analysis for Large Photovoltaic Systems Using Drones and Machine Vision

Moath Alsafasfeh, Ikhlas Abdel-Qader, Bradley Bazuin, Qais Alsafasfeh and Wencong Su
Additional contact information
Moath Alsafasfeh: Electrical and Computer Engineering Department, College of Engineering and Applied Sciences, Western Michigan University, Kalamazoo, MI 49001, USA
Ikhlas Abdel-Qader: Electrical and Computer Engineering Department, College of Engineering and Applied Sciences, Western Michigan University, Kalamazoo, MI 49001, USA
Bradley Bazuin: Electrical and Computer Engineering Department, College of Engineering and Applied Sciences, Western Michigan University, Kalamazoo, MI 49001, USA
Qais Alsafasfeh: Energy Engineering Departments, College of Engineering, Al Hussein Technical University, Amman 25175, Jordan; Sabbatical leave from Tafila Technical University, Department of Electrical power and Mechatronics, Tafila-Jordan
Wencong Su: Department of Electrical and Computer Engineering, University of Michigan-Dearborn, Dearborn, MI 48121, USA

Energies, 2018, vol. 11, issue 9, 1-18

Abstract: One of the most important sources of clean energy in the future is expected to be solar energy which is considered a real time source. Research efforts to optimize solar energy utilization are mainly concentrated on the components of solar energy systems. Photovoltaic (PV) modules are considered the main components of solar energy systems and PVs’ operations typically occur without any supervisory mechanisms, which means many external and/or internal obstacles can occur and hinder a system’s efficiency. To avoid these problems, the paper presents a system to address and detect the faults in a PV system by providing a safer and more time efficient inspection system in real time. In this paper, we proposing a real time inspection and fault detection system for PV modules. The system has two cameras, a thermal and a Charge-Coupled Device CCD. They are mounted on a drone and they used to capture the scene of the PV modules simultaneously while the drone is flying over the solar garden. A mobile PV system has been constructed primarily to validate our real time proposed system and for the proposed method in the Digital Image and Signal Processing Laboratory (DISPLAY) at Western Michigan University (WMU). Defects have been detected accurately in the PV modules using the proposed real time system. As a result, the proposed drone mounted system is capable of analyzing thermal and CCD videos in order to detect different faults in PV systems, and give location information in terms of panel location by longitude and latitude.

Keywords: PV module; real time fault detection; thermal and CCD video processing (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (14)

Downloads: (external link)
https://www.mdpi.com/1996-1073/11/9/2252/pdf (application/pdf)
https://www.mdpi.com/1996-1073/11/9/2252/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:11:y:2018:i:9:p:2252-:d:166079

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().