Investigation of the Temperature Effect on the Electrical Parameters of a Photovoltaic Module at Ouargla City

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Abstract To predict the I-V characteristics of the photovoltaic module, five parameters photovoltaic model Abstract: To predict the I-V characteristics of the photovoltaic module, five parameters photovoltaic model was utilized. The most influential parameters in the photovoltaic module are the solar irradiance level (E) and the temperature (T). The present research was conducted due to the high-temperature values in Ouargla city (can reach 60 °C in the hot season), which will affect remarkably the installed PV installations in this region. The experimental was done in several days cause the investigation need a constant irradiance values with different temperature. The temperature of a photovoltaic module varies according to other conditions, the temperature measurements made on the rear face of the PV module may not be indicative due to a temperature gradient in the material of the rear face of the module. Unfortunately, photovoltaic systems manufacturers do not take into consideration these environmental circumstances which negatively influence the module parameters and yielded deterioration in the system efficiency. The aim of this paper is to investigate the effect of the temperature term on the electrical performances such as the open circuit voltage (Voc), short circuit current (Isc), optimal power (Pm) and Fill Factor. The temperature distribution is non-uniform temperature on the surface of PV modules joined to that of the quality of temperature measurements affects the values of temperature coefficients found. To validate a model allows the researcher to get approximately the I-V characteristic similar to the experiment values. It use the conventional technique (Newton Raphson method) and it was compared by an artificial intelligent method which is the PSO technique, the five parameters estimated (Iph, Is, Rs, Rp, n). This proposed approach can be utilized to model any marketable PV module based on given datasheet parameters only. Statistical indicators were adopted to evaluate the performance of the proposed models; where the relative error of the PSO method comes more less the conventional method.