Shading fault detection in a grid-connected PV system using vertices principal component analysis

Rouani, Lahcene and Harkat, Mohamed Faouzi and Kouadri, Abdelmalek and Mekhilef, Saad (2021) Shading fault detection in a grid-connected PV system using vertices principal component analysis. Renewable Energy, 164. pp. 1527-1539. ISSN 0960-1481, DOI

Full text not available from this repository.


Partial shading severely impacts the performance of the photovoltaic (PV) system by causing power losses and creating hotspots across the shaded cells or modules. Proper detection of shading faults serves not only in harvesting the desired power from the PV system, which helps to make solar power a reliable renewable source, but also helps promote solar versus other fossil fuel electricity-generation options that prevent making climate change targets (e.g. 2015's Paris Agreement) achievable. This work focuses primarily on detecting partial shading faults using the vertices principal component analysis (VPCA), a data-driven method that combines the simplicity of its linear model and the ability to consider the uncertainties of the different measurements of a PV system in an interval format. Data from a grid connected monocrystalline PV array, installed on the rooftop of the Power Electronics and Renewable Energy Research Laboratory (PEARL), University of Malaya, Malaysia, have been used to train the VPCA model. To prove the effectiveness of this VPCA method, four partial shading patterns have been created. The obtained performance has, then, been tested against a regular PCA. In addition to its ability to acknowledge the uncertainty of a PV system, the VPCA method has shown an enhanced performance of detecting partial shading fault in comparison with the standard PCA. Also, included in the article is an extension of the contribution plot diagnosis-based method, of the Q-statistic, to the interval-valued case aiming to pinpoint the out-of-control variables. (c) 2020 Published by Elsevier Ltd.

Item Type: Article
Funders: la Direction Generale de la Recherche Scientifique et du Developpement Technologique, Algeria (DGRSDT) (A01L08UN350120200002)
Uncontrolled Keywords: Photovoltaic system (PV); Partial shading; Fault detection; Fault diagnosis; Principal component analysis (PCA); Interval-valued PCA
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Engineering
Depositing User: Ms. Juhaida Abd Rahim
Date Deposited: 01 Apr 2022 03:43
Last Modified: 01 Apr 2022 03:43

Actions (login required)

View Item View Item