Experimental characterization of photovoltaic systems using sensors based on MicroLab card: Design, implementation, and modeling

Dris Ben hmamou, Mustapha Elyaqouti, Samia Achouch, Brahim Ydir, El hanafi Arjdal, Driss Saadaoui, Amine Ajdour, Souad Lidaighbi, Imade Choulli, Abdelfattah Elhammoudy and Hafida Idrissi Azami

Renewable Energy, 2024, vol. 223, issue C

Abstract: In the most case, the manufacturer measure electrical or thermal parameters under environment conditions that are artificial in the laboratory scale and rarely occur in reality outside. Therefore, the characterization of photovoltaic modules under dynamic environmental conditions will be an essential phase to go forward with renewable energy technology. In this study an experimental setup, uses sensors (current, voltage and temperature) interfaced with a MicroLab data acquisition card, was developed with low-cost to measure current-voltage and power-voltage curves of the PV modules under dynamic environmental conditions. In addition to on-site measurement of meteorological parameters like solar irradiance, temperature, humidity and wind speed, spatial modeling of the conditions was performed using the WRF weather model. A performance-based experimental method for PV module characterization under dynamic conditions was presented along with suitable modeling tools. The obtained results indicate that the evolutionary algorithms proved effective for parameter extraction of the three common electrical models single diode, double diode and triple diode, from experimental module test data and MLBSA algorithm successfully modeled the experimental I–V curves, showing good agreement with measured current, voltage and power values based on statistical metrics.

Keywords: Experimental measurement; Microlab cart; Current-voltage characteristics; Evolutionary algorithms; Dynamic environmental conditions; Weather research and forecasting model (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:223:y:2024:i:c:s0960148124001149

DOI: 10.1016/j.renene.2024.120049

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