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All Journal Mechatronics, Electrical Power, and Vehicular Technology
Mandal, Sharmistha
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Electrical & Electronics Engineering

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Journal : Mechatronics, Electrical Power, and Vehicular Technology

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Enhanced solar PV cell parameter identification via particle swarm optimization (PSO) with weighted objective function Ghosh, Bikshan; Mandal, Sharmistha
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 16, No 1 (2025)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/j.mev.2025.1033

Abstract

This work aims to identify the parameters of solar photovoltaic (PV) cells, which can then be used for modeling PV systems and designing controllers. The dynamic equation governing correlation among current and voltage at the output terminals of a solar cell is predominantly dependent on different parameters of the single diode model (SDM) or double diode model (DDM) representation of that solar PV cell. Without easy access to this information, accurately modeling PV systems for further studies becomes difficult. So, to identify those parameters with greater accuracy and less complexity, particle swarm optimization (PSO) in conjunction with the weighted objective function (WOF) has been proposed in this paper. This proposition of multi-objective optimization with a metaheuristic algorithm is found to give very satisfactory results while reducing any further modification in conventional PSO and with faster convergence.
Co-Authors Ghosh, Bikshan