Identification of Photovoltaic Module Parameters for Simulation Application
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Date
2024-07-15
Journal Title
Journal ISSN
Volume Title
Publisher
University of M'sila
Abstract
EN
The increasing global demand for renewable energy solutions has intensified research into optimizing
photovoltaic (PV) systems. Accurate modeling of PV modules is essential for predicting their
performance and enhancing the efficiency of solar energy systems. This dissertation addresses the
identification and extraction of key PV module parameters using Particle Swarm Optimization (PSO)
within the single diode model. The study focuses on extracting five critical parameters: diode ideality
factor (n), series resistance (Rs), shunt resistance (Rsh), photocurrent (Iph), and reverse saturation
current (I0). The PSO algorithm, inspired by social behaviors of birds flocking or fish schooling,
optimizes this process by minimizing errors between experimental data and the model. Validation
using experimental data under various conditions highlights PSO’s effectiveness in precise parameter
identification, enhancing the reliability of PV simulations. The research provides practical guidelines for
implementing PSO in PV parameter extraction, contributing to the advancement and broader adoption
of solar energy systems.
Description
Keywords
Photovoltaic - Parameters identification- single-diode model- PSO algorithm.