InGaP

Journal Title, Volume, Page:

Solid State Sciences, Volume 8, Issue 5,Pages 556-559

Year of Publication:

2006

Link:

http://www.sciencedirect.com/science/article/pii/S1293255806000069

Authors:

H.S. Hilal

An-Najah N. University, P.O. Box 7, Nablus, West Bank, Palestine

Current Affiliation:

Department of Chemistry, An-Najah N. University, Nablus, PO Box 7, West Bank, Palestine

[email protected]

A. Cheknane

Unité de Recherche des Matériaux et Energies Renouvelables, Université Abou Bakr Belkaid Tlemcen, Algérie

J.P. Charles

MOPS, SUPELEC, 2 rue Edouard Belin, 57070 Metz, France

B. Benyoucef

Unité de Recherche des Matériaux et Energies Renouvelables, Université Abou Bakr Belkaid Tlemcen, Algérie

G. Campet

CNRS, Université Bordeaux I, Château Brivazac, Ave du Dr. A. Schweitzer, 33600 Pessac, France

Preferred Abstract (Original):

One of the important parameters, that commonly affect solar cell performances, is the series resistance. Such effect becomes more pronounced when working under higher illumination intensities due to higher generated photocurrents. Therefore, it is necessary to predict series resistance effects under such conditions. To know more about the series resistance effect and its interpretation, InGaP based solar cell performances were investigated, using high solar concentration levels (73.36 X, 201.19 X). To facilitate the prediction of series resistance effect, as a function of insolation level, a computerised analytical model, using neural network, is presented.

SERIES RESISTANCE MEASUREMENT AND PREDICTION

An-Najah Staff

Modelling and Simulation of Ingap Solar Cells Under Solar Concentration: Series Resistance Measurement and Prediction