Journal
ENERGY
Volume 159, Issue -, Pages 842-856Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2018.06.194
Keywords
Photovoltaic (PV) systems; Failure detection (PD); Generalized likelihood ratio test (GLRT); Weighted GLRT (WGLRT); Multiscale
Categories
Funding
- NPRP grant from the Qatar National Research Fund [NPRP9-330-2-140]
Ask authors/readers for more resources
This paper proposes an improved statistical failure detection technique for enhanced monitoring capabilities of PV systems. The proposed technique offers reduced false alarm and missed detection rates compared to the generalized likelihood ratio test (GLRT)by taking in to consideration the nature of the GLRT statistics and applying a multiscale representation. The multiscale nature of the data provides better robustness to noises and better monitoring quality. The effectiveness of the proposed multiscale weighted GLRT (MS-WGLRT) method in detecting failures is evaluated using a set of synthetic and simulated PV data where the developed chart is used for detecting single and multiple failures (e.g., Bypass, Mix and Shading failures). Moreover, a set of real-data was used in order to prove the effectiveness of the proposed technique in detecting partial shading faults. All results show that the MS-WGLRT method offers better fault detection performances compared to the classical WGLRT and conventional GLRT charts. (C) 2018 Elsevier Ltd. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available