Abstract
Estimation of single-diode and two-diode solar cell parameters by using chaotic optimization approach (COA) is addressed. The proposed approach is based on the use of experimentally determined current-voltage (I-V) characteristics. It outperforms a large number of other techniques in terms of average error between the measured and the estimated I-V values, as well as of time complexity. Implementation of the proposed approach on the I-V curves measured in laboratory environment for different values of solar irradiation and temperature prove its applicability in terms of accuracy, effectiveness and the ease of implementation for a wide range of practical environment conditions. The COA-based parameter estimation is, therefore, useful for PV power converter designers who require fast and accurate model for PV cell/module.
Highlights
The contribution of solar energy in total electric energy production is growing constantly
diode model (DDM) considers the composite effect of the neutral region of the junction, and, models the solar cells more accurately [3]
Of all the proposed techniques, none excels in terms of accuracy and efficiency with respect to others. This was our main incentive for doing research in this field. We propose both accurate and efficient parameter optimization of solar cell single-diode model (SDM) and DDM through chaotic optimization approach (COA)
Summary
The contribution of solar energy in total electric energy production is growing constantly. Recent research [7] on the usage of datasheet values for solar cell parameter estimation shows that current-voltage characteristic is not unique when designers focus on three datasheet points (open circuit, short circuit and maximum power). This was our main incentive for doing research in this field We propose both accurate and efficient parameter optimization of solar cell SDM and DDM through chaotic optimization approach (COA). Unlike methods proposed in [16,33,41,65,66,67], this paper will use COA based on Logistic map for solar cell parameter estimation.
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