%0 Journal Article
%@ 0038092X
%A Rasool, F.
%A Drieberg, M.
%A Badruddin, N.
%A Mahinder Singh, B.S.
%D 2017
%F scholars:9271
%I Elsevier Ltd
%J Solar Energy
%K Extraction; Irradiation; Parameter extraction; Photovoltaic cells, Accurate modeling; Data-sheet values; Datasheet; Five parameters; Maximum power point; Parallel resistance; Single mechanisms; Solar PV panels, Iterative methods, accuracy assessment; data set; irradiation; model test; modeling; parameter estimation; parameterization; photovoltaic system; solar power; solar radiation
%P 519-530
%R 10.1016/j.solener.2017.05.078
%T PV panel modeling with improved parameter extraction technique
%U https://khub.utp.edu.my/scholars/9271/
%V 153
%X An accurate model of the PV panel is useful to predict its behavior at all operating points for various applications. However, most of the manufacturers provide datasheet values at only open circuit point, short circuit point and maximum power point. Single mechanism five parameters (1M5P) model which contains a series and parallel resistance is presented. The model has five unknown parameters which need to be extracted. In this paper, the parameter extraction technique is improved for accuracy, simplicity and practicability. It requires minimum amount of data from the datasheet and does not require any complex iteration. The accuracy of the model with improved parameter extraction technique (IPET) is firstly validated with datasheet in the controlled irradiation environment. Secondly it is also compared under real-time uncontrolled irradiation environment in order to check the practicability of the model. Finally, the experiment for uncontrolled irradiation environment is carried out on three operating point's i.e. maximum power point and two half power points to verify the accuracy of the model over the wider operating range. The results of the model with IPET are in good agreement with both datasheet and experimental results with difference of less than 5. It also shows significant improvement in accuracy when compared to the existing models. © 2017 Elsevier Ltd
%Z cited By 35