Identification of Photovoltaic Module Parameters for Simulation Application

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dc.contributor.authorZEROUAK Manal
dc.contributor.authorBEHLOULI Imane
dc.contributor.authorENC/ Amar GUICHI
dc.date.accessioned2024-07-15T09:00:38Z
dc.date.available2024-07-15T09:00:38Z
dc.date.issued2024-07-15
dc.description.abstractEN 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.
dc.identifier.urihttps://dspace.univ-msila.dz/handle/123456789/43747
dc.language.isoen
dc.publisherUniversity of M'sila
dc.relation.ispartofseries2024
dc.subjectPhotovoltaic - Parameters identification- single-diode model- PSO algorithm.
dc.titleIdentification of Photovoltaic Module Parameters for Simulation Application
dc.typeThesis

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