A novel hybrid numerical with analytical approach for parameter extraction of photovoltaic modules

Abstract

• A Novel hybrid approach analytical/Numerical technique is proposed and validated. • The minimum value of ARE is obtained using our model and equal to 1.14%. • The obtained RMSE is 0.0031 A , it’s considered as the smallest among the values found by other model. • Low computational time is carried using our Hybrid approach compared with the others models. • The parameter extraction method is superior in terms of accuracy and convergence. Building an accurate mathematical model of photovoltaic modules is an essential issue for providing reasonable analysis, control and optimization of photovoltaic energy systems. Therefore, this study provides a new accurate model of photovoltaic Panels based on single diode Model. In this case, the proposed model is the link between two models which are the ideal model and the resistance network. All parameters are estimated based on hybrid Analytical/Numerical approach: three parameters photocurrent, reverse saturation current and ideality factor are obtained using an Analytical approach based on the datasheet provided by the manufacturer under Standard Test Conditions. The series and shunt resistances are obtained by using a Numerical approach similar to the Villalva's method in order to achieve the purpose of modeling the resistance network part. Our model is tested with data from the manufacturer of three different technologies namely polycrystalline, Mono-crystalline silicon modules and thin-film based on Copper Indium Diselenide, and for more accurate performance evaluation we are introducing the Average Relative Error and the Root Mean Square Error. The simulated Current-Voltage and Power-Voltage curves are in accordance with experimental characteristics, and there is a strong agreement between the proposed model and the experimental characteristics. The computation time is 0.23 s lower than those obtained using others approach, and all obtained results under real environment conditions are also compared with different models and indicated that the proposed model outperforms the others approach such as villalva’s and kashif’s method.