New Accurate Model to Estimate Maximum Power of Photovoltaic Modules and Arrays

Bencherif, M.; Benouaz, T.

doi:10.7569/jsee.2014.629504

Cited by 1 publication

(1 citation statement)

References 13 publications

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“…Several methods have been developed for the prediction of the electrical output of PV modules using single diode model (SDM) under various indoor and outdoor conditions. Benchrif et al 2 presented an approach for directly predicting MPP for power tracking in PV arrays. This approach takes into account the effect of solar cell resistances.…”

Section: Introductionmentioning

confidence: 99%

An accurate analytical model for predicting the maximum power of photovoltaic module operating outdoor under varying conditions

Benahmida

Maouhoub

Tifidat

et al. 2022

Intl J of Energy Research

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Summary One of the crucial study areas for renewable energy is the output power prediction of photovoltaic (PV) generators under various operating situations. Accurate prediction of maximum power is important for the control and design of grid‐connected PV systems. In this study, a new analytical model of voltage and current at maximum power point in relation to temperature and solar irradiation has been proposed to predict the maximum power of PV modules operating from dawn to dusk under real outdoor environmental conditions. Real‐time monitoring values of PV module temperature and solar irradiation have been used to optimize the analytical model parameters during one reference day and then to forecast the maximum power of the PV module for all other days. To validate our proposed analytical model, experimental data recorded by National Renewable Energy Laboratory for three PV modules from single‐crystalline silicon, multi‐crystalline silicon, and amorphous silicon/crystalline silicon heterojunction with intrinsic thin‐layer technologies have been used. Real‐time experimental and optimized characteristic using the proposed model of voltage at maximum power has been compared to three other analytical models in one reference day. The results have shown a good agreement and the normalized error has not exceeded 1%. Furthermore, the comparison of experimental and predicted curves of peak power point in two other arbitrary days has shown a good agreement and the NRMSE values have not exceeded 0.92%.

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Section: Introductionmentioning

confidence: 99%