Development of a novel solar PV module model for reliable power prediction under real outdoor conditions

Manish Kumar, Prashant Malik, Rahul Chandel and Shyam Singh Chandel

Renewable Energy, 2023, vol. 217, issue C

Abstract: Accurately predicting and validating the power output of commercial solar PV power plants, remains an important research topic despite numerous studies already conducted. The precision and reliability of power prediction depends on the accuracy of the solar cell parameter values used in the model. A novel analytical technique has been developed in this study for PV power prediction, which employs one and two diode models with 3, 5, and 7 parameters. This new model only requires the manufacturer sheet data and has been validated through indoor and outdoor experiments. The performance of an experimental PV system is evaluated using the proposed solar cell models under varying irradiance and temperature levels. Additionally, the predicted output solar power was experimentally validated under real outdoor conditions in India with higher accuracy. The 7-parameter solar cell model is found to be the most accurate with the least RMSE of 0.02, followed by the 5 and 3-parameter models with RMSEs of 0.04 and 0.07, respectively. Compared to previous methods, the present new model predicts PV power with higher accuracy and lower percentage error. Finally, the study also identifies follow-up photovoltaic research areas.

Keywords: Solar energy; Photovoltaics; Solar cell parameters; PV module model; Solar power prediction (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:217:y:2023:i:c:s0960148123011394

DOI: 10.1016/j.renene.2023.119224

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