Experimental and numerical evaluation of the performance of a photovoltaic panel in a semi-arid climate

Photovoltaic (PV) solar energy is playing an increasingly important role in the global energy mix, thanks to its renewable potential and low environmental impact. However, the performance of PV systems varies considerably according to climatic and geographical conditions, making it essential to select the right technology for the region in question. In this study, the annual performance of a glass-tedlar PV panel was evaluated in a semi-arid climate. Experimental data were compared with the results of a numerical model developed in COMSOL Multiphysics. This model aims to predict the behavior of PV systems in specific environments, offering an economical alternative to the often-costly direct acquisition of technology. The results show that January is the best-performing month, with an average power of 153.4 W (around 61% of nominal power) and a maximum efficiency of 15.5%, in line with the low temperatures. On the other hand, August and October recorded the lowest output, with 132.1 W and 130 W respectively, and a minimum efficiency of 12.9% in August. The good agreement between simulated and experimental data confirms the model’s reliability, which can be adapted to other technologies and climates.

Authors

Institutions

Publication Details

Published
2025-05-15
DOI
https://doi.org/10.1109/iraset64571.2025.11008049
Citations
2
Primary Topic
Solar Thermal and Photovoltaic Systems
Type
article
Field-Weighted Citation Impact
0.73
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Experimental and numerical evaluation of the performance of a photovoltaic panel in a semi-arid climate

Abdellatif Ghennioui, Bachir Benhala, Charaf Hajjaj, Elhadi Baghaz et al.
2 citations
Solar Thermal and Photovoltaic Systems
0.73
article

Experimental and numerical evaluation of the performance of a photovoltaic panel in a semi-arid climate

Abdellatif Ghennioui, Bachir Benhala, Charaf Hajjaj, Elhadi Baghaz, Yassine El Alami, Fatima Ouerradi, Youness Bannour, Hanane Chetnouf
article en
2 citations

Abstract

Photovoltaic (PV) solar energy is playing an increasingly important role in the global energy mix, thanks to its renewable potential and low environmental impact. However, the performance of PV systems varies considerably according to climatic and geographical conditions, making it essential to select the right technology for the region in question. In this study, the annual performance of a glass-tedlar PV panel was evaluated in a semi-arid climate. Experimental data were compared with the results of a numerical model developed in COMSOL Multiphysics. This model aims to predict the behavior of PV systems in specific environments, offering an economical alternative to the often-costly direct acquisition of technology. The results show that January is the best-performing month, with an average power of 153.4 W (around 61% of nominal power) and a maximum efficiency of 15.5%, in line with the low temperatures. On the other hand, August and October recorded the lowest output, with 132.1 W and 130 W respectively, and a minimum efficiency of 12.9% in August. The good agreement between simulated and experimental data confirms the model’s reliability, which can be adapted to other technologies and climates.

Chouaib Doukkali University (MA), Agence pour le Développement et la Réhabilitation de la Ville de Fès (MA), Institut of Research in Solar Energy and New Energies (MA)
Climate action
Openalex Percentile: Top 31%
Solar Thermal and Photovoltaic Systems
0.73
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.