Seasonal Performance Comparison of Four Electrical Models of Monocrystalline PV Module Operating in a Harsh Environment

To accurately predict the performance of a photovoltaic (PV) system, it is necessary to assess the effectiveness and accuracy of the methods used in modeling PV cells. This paper presents and analyzes the performance of a monocrystalline PV module (SYP80S-M) installed in outdoor operation conditions in Adrar, Algeria. The monthly experimental results are compared with those calculated by four different methods: single(fourand five-parameter) and double-diode (seven-parameter) model. The monthly average performance ratio, efficiency, and output energy were calculated and compared based on year data. Statistical analysis shows good correspondence of all models with the experimental monthly average energy data. However, the results reveal that the double-diode seven-parameter model outperforms the other models with 99.55% forecasting accuracy. In general, the accuracy of the models increases during hot months with the root-mean-square error (RMSE) varying between 2.2 and 4.4 and mean bias error (MBE) lower than 2.1, while RMSE values are higher at 4.5 and those of MBE exceed 0.37 for the cold months.